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Micro Computer Tomography for medical device and pharmaceutical packaging analysis
Journal of Pharmaceutical and Biomedical Analysis 108 (2015) 38–48
Contents lists available at ScienceDirect
Journal of Pharmaceutical and Biomedical Analysis journal homepage: www.elsevier.com/locate/jpba
Review
Micro Computer Tomography for medical device and pharmaceutical packaging analysis Florine Hindelang, Raphael Zurbach, Yves Roggo ∗ Complaint and Counterfeit Department, Quality Control for Commercial Bulk Products, F. Hoffmann-La Roche Ltd, Wurmisweg, CH-4303 Kaiseraugst, Switzerland
a r t i c l e
i n f o
Article history: Received 9 December 2014 Received in revised form 21 January 2015 Accepted 22 January 2015 Available online 9 February 2015 Keywords: X-ray microtomography Medical device Defect detection Quality control 3D imaging
a b s t r a c t Biomedical device and medicine product manufacturing are long processes facing global competition. As technology evolves with time, the level of quality, safety and reliability increases simultaneously. Micro Computer Tomography (Micro CT) is a tool allowing a deep investigation of products: it can contribute to quality improvement. This article presents the numerous applications of Micro CT for medical device and pharmaceutical packaging analysis. The samples investigated confirmed CT suitability for verification of integrity, measurements and defect detections in a non-destructive manner. © 2015 Elsevier B.V. All rights reserved.
Contents 1. 2.
3.
4.
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Material and method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Micro CT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1. General principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2. Factors influencing X-ray imaging process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1. Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2. Analyzed samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1. Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2. Reconstruction and image analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Verification and measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1. Material/assembly checks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2. Quality control (testing technique) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.3. Integrity checks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.4. Shadow live imaging for quick internal integrity checks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Detection of defects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1. Defects detection inside mechanical devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2. Defects detection inside electronic devices and metrology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3. Defects detection of pharmaceutical packagings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
∗ Corresponding author at: F. Hoffmann-La Roche Ltd, Wurmisweg, Building 250, CH-4303 Kaiseraugst, Switzerland. Tel.: +41 061 68 81 336. E-mail addresses: fl[email protected] (F. Hindelang), [email protected] (R. Zurbach), [email protected] (Y. Roggo). http://dx.doi.org/10.1016/j.jpba.2015.01.045 0731-7085/© 2015 Elsevier B.V. All rights reserved.
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1. Introduction Over the last 25 years and since the invention of the first CT-scanner prototype by Hounsfield in 1969 [1,2], computer technology has greatly improved, allowing details in the reconstructed images with pixel sizes in the nanometer range [3]. Micro Computer Tomography nowadays applies to many domains such as biology [4,5], taxonomy [6], paleontology [7], geology [8–10], material science [11], medicine or automotive industry [12]. It has been involved in the pharmaceutical industry to help understand and improve the development and manufacturing processes of medicine during Quality by Design studies [13]. Indeed Micro CT allows a direct observation on the impact of physical parameters set during the drug elaboration (cracks, surface defects, or internal failures). Currently drugs are directly designed within medical devices and delivered by mean of physical, mechanical, or thermal means. Those mechanisms could also encounter defects or technical problems. The CT systems are convenient for testing both internal and external structures of objects without contact, by carrying out nondestructive 3D measurements. That is why this technique can also be applied to medical device and pharmaceutical packaging that until now have been otherwise impossible to visualize without opening them, thus leading to a possible damage and loss of structure information. This article presents the suitability of Micro CT system for the analysis of medical devices and pharmaceutical packaging. Objects can be virtually handled for a variety of quality control purposes, including verification of integrity, measurements and defect detections. Hence there is the potential to improve the overall building processes thus avoiding structure or mechanism defects and ensure the best quality and safety for patients.
Fig. 1. Micro CT instrumentation. X-rays are directed from the-X-ray source toward the sample. A detector placed on the opposite side of the sample measures the intensity of the transmitted X-rays.
done in most studies as a first step [17,18]. Semi-transparent representations can provide a fast three-dimensional overview of the work piece edges, and defects in components.
2.1. Micro CT
2.1.2. Factors influencing X-ray imaging process The resolution of CT measurement and reconstruction is influenced by many factors that have to be taken into account while using micro CT technology. The review paper [19] presents parameters and factors having an impact on CT measurements and those allowing avoiding artifacts which are responsible for images imperfections. Only a quick overview of the latter is given hereafter, as well as the most common encountered artifacts. Finally the purpose of CT scanning may also influence X-ray imaging process.
2.1.1. General principle Micro CT is a 3D imaging technique allowing the virtual reconstruction of objects with pixel size in the micrometer range. Whether a sample is rotated relative to a static X-ray source and a detector or the X-ray source and the detector move around the sample. Only the first case will be considered in this article. Xrays generated by the source are emitted toward the sample. When crossing the sample, X-rays are attenuated according to the length traveled in the absorbing material (thickness), to the material composition and its density (i.e. attenuation coefficient). The detector on the opposite side of the sample measures the intensity of the transmitted X-rays (Fig. 1). The varying levels of signal intensity provide a gray-scale representing the sample and its properties: the X-ray shadow image. This high-resolution X-ray shadow image can be seen live on the monitor of the micro-CT device. X-ray transmission images are collected at multiple discreet angular steps like a map of the relative atomic density of the sample. The 2D gray images projections, called slice plans, are reconstructed using mathematical (e.g. Filtered Back Projection FBP [14]) and iterative algorithms (e.g. Algebraic Reconstruction Technique ART, based on successive estimations of solutions [15]). In case of a cone beam source, which induces modification of the projection plane during sample’s rotation, the reconstruction is based on Feldkamp algorithm [16]. Finally, the reconstructed 2D radiographs are gathered and stacked together. As a result, the complete 3D map of the sample is computed and available for further processing (Fig. 2). Image analysis software is designed to simultaneously observe the 3D object view, and the three 2D cross sections. 3D visualization is
• Parameters and factors Not only the parts of the equipment (source, detector) but also the analyzed sample, the measurement setup parameters and the user play an important role in the whole X-ray imaging process. They are all connected together. - Source: The type and material of the target of the X-ray source have an influence of the radiation properties i.e. shape, intensity and quality. The power of the X-ray beam, affected by the source current and source voltage, has to be adjusted for each sample analyzed, according to their density, geometry, etc. High absorbing materials will need high energy exposure to be visible, but low absorbing materials will not be visible. On the contrary, low absorbing material will only need low energy exposure, but artifacts or total extinction could appear due to the presence of high absorbing neighboring materials. - Sample and environment: The sample orientation and thickness influence the amount of measuring noise and scatter (see artifacts hereafter). Optimal sample orientation should avoid part surfaces that are parallel to the X-ray beam, as beam scattering is then favored and leads to instabilities in 3D reconstruction. Also temperature control is important to avoid measurements errors. Vendors advise to have the CT equipment in an airconditioned room. - Detector: Detector sensitivity will also impact the resulting 3D image and in particular the number of angular poses at which images are taken. The more the angular poses, the more the improvement of reconstruction accuracy, but the larger the measurement time.
2. Material and method
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F. Hindelang et al. / Journal of Pharmaceutical and Biomedical Analysis 108 (2015) 38–48
Fig. 2. Principle of Micro CT from measurement to reconstruction.
- User: The CT strategy via user influence is also at stake since user defines the best parameters for each CT scan: current (impact on image contrast), voltage (impact on image brightness), integration time (impact on scanning time and image quality). Possibility is given to measure the whole object at once or in parts by selecting a Region of Interest ROI, for instance. ROI scanning allows measuring specific regions (volume portions) without reconstructing the whole object, often time consuming. The focus on a portion allows concentrating effects of quality adjustments. Other parameters such as choice and use of filters (impact on image quality and artifacts), voxel resolution, etc. are also part of this strategy.
• Artifacts Among common artifacts, beam hardening, scattering, metal artifacts can be mentioned. - Beam hardening is due to different photons energy in the beam, resulting in difficult edge detection as the borders of the sample constitutive elements are not clearly defined. Indeed, the gray values of edge pixels are altered. The use of Cu or Al plates between the source and the sample allow avoiding the problem but it reduces the beam intensity. - Scattering: Other artifacts like scattering, causing halos around materials, are due to deflection of X-ray inside the sample or the detector.
Table 1 Micro CT parameters used for presented examples. Sample description/identification
Voltage (kV)
Current (mA)
Integration time (s)
Filtera
Reconstruction mode 1 = single 2 = multiple
Projections number
Qualityb (low/standard/ high) + resolutionc (premium/quick)
DAI activated/not activated/Fig. 3 Vial: thickness of glass/Fig. 5 Vial: Alu cap and flip-off cap/Fig. 6 RNS syringes: integrity check/Fig. 7 DAI broken/Fig. 9 SID defect: needle not in vial/Fig. 10 SID defect: needle bent in septum/Fig. 11 Part SID: glass missing in vial/Figs. 12 and 13 Glass distortion in vial/Fig. 14
150
5
0.74
1.5
2
360
Standard + premium
225 200
3.55 3.1
1 1.7
2 2
2 1
960 620
Standard + premium Standard + premium
50
2.2
2
None
N.A.
N.A.
N.A.
95 220
2.5 3.6
1.5 2
1 3
2 2
430 830
Standard + premium Standard + premium
100
8
0.56
1
1
900
High + premium
95
2.5
1.85
1
1
850
High + premium
180
1.6
1.7
1.5
1
480
Standard + premium
a b c
Filter = filter 1: 4 mm, filter 1.5: 1 mm, filter 2: 2 mm, filter 3: 4 mm. Quality = related to number of projections. Resolution = voxel resolution (low 168 m, standard 84 m, high 42 m).
F. Hindelang et al. / Journal of Pharmaceutical and Biomedical Analysis 108 (2015) 38–48
- Metal artifacts: these artifacts are due to the presence of metal with high absorption properties compared to other parts. It results in high brilliancy distortions, or ghost images in the reconstructed CT images. • Purpose of CT scanning The scanning parameters are chosen according to the final purpose of CT scan: shadow live imaging, defect analysis, 3D inspections, etc. - For X-ray live imaging, importance will be given to optimized contrast and brightness between constitutive elements, i.e. voltage and current settings will be highlighted, as well as the use of filters. The purpose of this is to get a picture, were the constitutive materials are distinguishable and possible defects are detectable thanks to gray shading. - For defect analysis, integrity checks, requesting a CT scan, all parameters mentioned above will be taken into account but quality may be medium (related to number of projections and voxel resolution), as long as constitutive materials are distinguishable and possible defects are detectable once object is reconstructed. - For 3D inspections, metrology and deep investigations inside scanned objects, the efforts will be focused on all parameters since the goal is to find a good compromise between them all to obtain the best reconstructed images with minimized imperfections. Afterwards, image processing (separation of the constitutive materials, measurements, etc.) will be eased and all the more representative of the original object.
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GmbH, Germany and is made of silicon. Its pixel geometry is rectangular. The geometric magnification is 1.2. The equipment is controlled via a computer by “exaCT Control” software, version 2.0.0. from WENZEL Volumetrik GmbH. The reconstruction algorithm is based on Feldkamp classical algorithm [16]. The Wenzel “exaCT Control” software has two reconstruction modes, depending on the size of the sample analyzed. If the object size is smaller than the out coming X-ray beam and/or the detector’s height, then the direct 3D reconstruction can be computed in a single step; the reconstruction mode is then “single”. However if the object size is taller than the beam and/or the detector’s height, the slices of the object are reconstructed separately and concatenated afterwards; the reconstruction mode is then “multiple”. 3D inspections and defect analysis of the object have been performed thanks to “VG Studio Max” Software, version 2.2 from Volume Graphics Gmbh.
Optimization of all parameters according to the final CT scan purposes is a hard task as they have an effect on the information content of the resulting image. 2.2. Material 2.2.1. Instrumentation The measurements have been performed on a Micro Computer Tomography system, the CT workstation exaCT from WENZEL Volumetrik GmbH, Germany. It uses a Perkin Elmer X-ray source with large conic analyzing beam, enveloping objects up to 150 mm of diameter and 300 mm of height. It possesses a maximum acceleration voltage of 225 kV and a corresponding power of 800 W. The detector is a flat panel detector developed by WENZEL Volumetrik
Table 2 Image processing actions for presented examples. Sample description/Identification
Image processing actions
DAI activated/not activated/Fig. 3 Vial: thickness of glass/Fig. 5 Vial: Aluminum cap and flip-off cap/Fig. 6
Segmentation
RNS syringes: integrity check/Fig. 7 DAI broken/Fig. 9 SID defect: needle not in vial/Fig. 10 SID defect: needle bent in septum/Fig. 11 Part SID: glass missing in via l/Figs. 12 and 13 Glass distortion in vial/Fig. 14
Wall thickness analysis Segmentation alignment with reference object Reference object for roundness N.A. Segmentation Segmentation Comparison/superposition Segmentation Alignment with reference object Size measurement Segmentation Alignment with reference object Segmentation Alignment with reference object Reference object for cylindricity
Fig. 3. Verification DAIs activated, not activated. Before activation (DAI A), the metal springs are compressed. After activation (DAI B), the metal springs are relaxed.
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F. Hindelang et al. / Journal of Pharmaceutical and Biomedical Analysis 108 (2015) 38–48
Fig. 4. Principle of segmentation histogram with gray values. Each constitutive material is represented by a peak. The choice of a gray value serves as a threshold that determines the material boundary: brighter areas are considered as material, darker areas are considered as background. (A) Standing for an example of mono-material (glass vial), the segmentation process defines the interface between glass (material) and the surrounding air (background). (B) Standing for an example of multi-material, an iteration of the segmentation process should be performed in order to split the whole dataset in a list of sub-volumes so as to define the interface between different materials. For each iteration, unwanted structures are removed from the image to keep the material of interest.
2.2.2. Analyzed samples Experiments have been conducted on 2 types of samples: - medical devices; - pharmaceutical packaging. Medical devices investigated are disposable auto-injectors DAI (named A), single injection devices SID (named B), part of SID (named C) and Rigid Needle Shield syringes (named D). The DAI A is a single-use infusion device that works mechanically. It is made of a cap, an indicator window, an activation button and a needle guard. When the patient presses the activation button, a spring is relaxed to inject the drug. Afterwards, an indicator window confirms that the dose has been administered.
On the contrary, the SID B is an electronic single-use infusion device that works with a motor. It consists of about 80 individual components and allows the administration of oncology drug. The cartridge containing the drug is housed in a fluidic path container and set in motion by the motor. The patient activates the mechanism by pushing the start button. The needle penetrates in the patient’s body. The battery driven motor depresses the piston down and the drug is injected subcutaneously. After the drug administration, the needle is removed from the patient’s body and kept secured in the device, to avoid further injuries during manipulation [20]. Rigid Needle Shield syringes D are used to reduce needle tip damage, for better grip of needle shield and to reduce risk of needle injuries.
F. Hindelang et al. / Journal of Pharmaceutical and Biomedical Analysis 108 (2015) 38–48
Pharmaceutical packaging investigated are glass bottles, glass vials, aluminum caps of vial and rubber stoppers. 2.3. Method 2.3.1. Acquisition For each sample, a base of low density foam (polystyrene) has been created to fix the object. This foam has the advantage of being transparent to X-rays. The object has been centered as much as possible on the foam, to reduce the region to scan and limit mechanical collisions inside the device. For non-cylindrical or nonspherical objects a slight recommended tilt (3–5◦ ) has been applied to enhance the acquisition process and avoid artifacts [19]. Before starting acquisition, proper parameters have been selected and optimized based on the X-ray live shadow imaging to acquire the best object projections:
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- resolution; - quality mode. Table 1 details all parameters used for the different examples.
2.3.2. Reconstruction and image analysis After reconstruction in 3D pixels (so-called voxels) of the object, analysis and processing of the object volume data have been started. Segmentation of different materials within scanned objects has been performed based on the histogram of the frequency of occurrence of the different gray values within the scanned volume. Other handlings like Superposition/Alignment of objects, Comparison with reference objects and Measurements tools have been employed to investigate samples. Table 2 highlights the processing steps used for each example.
-
voltage; current; integration time; filter (filter material is aluminum alloy for low filters and copper alloy for high ones. Exact composition is confidential data, not communicated by the supplier); - reconstruction mode (single or multiple);
Fig. 5. Measurement of vials wall thickness. The chart displays the distribution of the different thicknesses (x-axis in mm) among glass vials.
Fig. 6. Verification of integrity for aluminum cap. (A) Shows the 3D view where the aluminum cap has been colored in gray and the flip-off cap in purple. (B) Shows the 2D front view in the middle section of the cap: a reference circle (radius 10 mm) has been created for assessing aluminum cap integrity. (For interpretation of the references to color in figure legend, the reader is referred to the web version of the article.)
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Fig. 7. X-ray live shadow imaging for verification of RNS syringes integrity. The syringe A is a reference syringe and no de-capping/re-capping has been performed. The needle is straight in the RNS. The syringe B is a defective syringe. After de-capping/re-capping, the needle is bent and has penetrated the RNS.
3. Results and discussion 3.1. Verification and measurement 3.1.1. Material/assembly checks In the first example (Fig. 3), two Disposable Auto Injectors (DAIs) type A have been scanned separately. Segmentation has been performed so as to distinguish the constitutive materials and compare the overall built structure of an activated and non-activated DAI sample. Segmentation is a procedure that allows separating constitutive materials of a scanned object (named volume). Indeed, the distribution of the materials densities is given in a histogram of the frequency of occurrence of the different gray values in the volume (Fig. 4): each peak represents a constitutive material. A surface determination can be defined by choosing a gray value applied globally to the object and corresponding to a material of interest. This gray value serves as a threshold that determines the material boundary: brighter areas are considered as material, darker areas are considered as background. In Fig. 4A, standing for an example of mono-material (glass vial), the segmentation process defines the
Fig. 8. Example of needle bent in a disposable injection device. The segmentation allows a view of the components inside the device. Here, the needle is bent.
interface between glass (material) and the surrounding air (background). In Fig. 4B, standing for an example of multi-material, an iteration of the segmentation process should be performed in order to split the whole dataset in a list of sub-volumes so as to define the interface between different materials. For each iteration, unwanted structures are removed from the image to keep the material of interest. The result is that each component is distinguished from another and can be differentiated by a color rendering. The selection of the threshold is a critical parameter during the segmentation
Fig. 9. Broken DAI. The metal parts have been colored in yellow and the glass parts in red. Here, the glass syringe has broken into pieces and the metal spring guide rod is not in the axis. The device is broken. (For interpretation of the references to color in figure legend, the reader is referred to the web version of the article.)
F. Hindelang et al. / Journal of Pharmaceutical and Biomedical Analysis 108 (2015) 38–48
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Fig. 10. Comparison of a defective SID with a reference SID. The SID gray A is in its initial state: the springs are compressed. The SID green B is a reference sample: it has been activated thus the springs are relaxed. (C) Shows the superposition of A and B: the differences between springs are easily visible. (For interpretation of the references to color in figure legend, the reader is referred to the web version of the article.)
of the micro CT data and can influence the measurement results (e.g. length, diameter, resolution, etc.) [19]. The constitutive materials have been separately processed and colored to be easily distinguishable. The metal parts (springs and needle) have been colored in yellow. The glass syringe has been colored in red. Light plastics have been colored in light blue and heavy ones in purple. The materials are visible all at once and cuts allow an overall view of the internal side of the device. The DAI on the left (picture A) is in its initial state and has not been activated. The metal springs, colored in yellow, are compressed. The DAI on the right (picture B) has been activated; the springs are relaxed.
3.1.4. Shadow live imaging for quick internal integrity checks In the next case, the aim of the study was to check the integrity of RNS syringes D, in other words assess whether the needle had penetrated the rubber after a de-capping/re-capping experience. Fig. 7A shows a reference RNS syringe, as it is initially. Fig. 7B shows the result after a de-capping/re-capping test: the needle is not straight and it has penetrated the RNS. In this case, the CT-scan was not necessary as the consequence of the test appeared obvious. Shadow live imaging is of great interest for big batches such as this one made of 80 syringes for fast verification. One could imagine setting a micro CT directly on the manufacturing chain for quick live checks. 3.2. Detection of defects
3.1.2. Quality control (testing technique) In the following example, the wall thickness of glass vials has been checked. To do so, a series of vial samples has been scanned and investigated with the wall thickness tool. Fig. 5 shows the obtained results. The chart displays the distribution of the different thicknesses. Most values are included in the range 0.976–1.061. This tool could be interesting to use in case of lyophilization problems for instance, since the glass thickness homogeneity could be checked. 3.1.3. Integrity checks A vial cap (Fig. 6A) has been segmented thanks to surface determination to easily distinguish the two constitutive elements: the flip-off cap made of plastic has been color rendered in purple whereas the aluminum cap made of aluminum has been color rendered in gray. In Fig. 6B, showing a 2D view, a reference circle has been created and adapted on the glass to check the morphology of the cap and conclude about a possible damage during manipulation. The cap is intact and no damage is visible.
3.2.1. Defects detection inside mechanical devices In the following example, a defective DAI A has been investigated. After segmentation of the constitutive materials, it appeared that the metal needle, kept inside the device, was bent (Fig. 8). The exact position of the curvature could be assessed without opening or breaking the device. Another example of DAI is presented in Fig. 9. It is a complaint sample returned for investigations: during last phase of infusion, needle remained in patients’ body and the auto injector broke into pieces in hands of the doctor. After 3D scan, the device has been segmented in its constitutive materials. The result is that the device is completely damaged. The glass syringe has broken into pieces and the spatial and functional relationships between components are compromised. 3.2.2. Defects detection inside electronic devices and metrology The first example, a SID type B, is a complaint sample coming from a patient. When the latter pressed the start button of the device, nothing happened and the device automatically stopped. No
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Fig. 12. X-ray preview of a vial with glass part missing.
Fig. 11. Defect detection, needle in septum. The metal needle is not straight in the vial and partially in the rubber, preventing the drug from being correctly delivered. (B) Shows different measurements performed with the software caliper tool.
drug was delivered to the patient. A CT scan has been performed on this defective sample. The metallic parts, namely springs and needles have been segmented and colored in gray (Fig. 10A). In the meantime, a CT scan has been performed on a reference sample, with successful delivery so as to compare both. The metallic parts, namely springs and needles have been segmented and colored in green (Fig. 10B). The sample and the reference have been superposed to easily detect differences. Fig. 10C shows the superposition of the defective and reference samples. The metal springs of the reference are relaxed. On the contrary, those of the defective sample are still in their initial state: compressed.
In the second case of SID type B, which is also a complaint sample, the device started delivering the drug after activation. But it quickly stopped, before the delivery was completed. A CT scan has been performed. Fig. 11A shows that the cartridge needle is not straight in the vial and the needle aperture is partially in the stopper. As a result, the liquid cannot flow through the hole of the needle toward the external needle which penetrates the patient body and the drug cannot be entirely delivered. In Fig. 11B, some sizes have been checked thanks to measurement tools available on the software. Theses sizes have been compared to the supplier specifications to assess the defect. An overpressure in the device has made the delivery system prematurely stop. In this case, as the liquid inside the vial and the stopper have similar densities, the contrast has been improved by finding a good compromise between gray values and opacity, thus allowing the visualization of the stopper border. 3.2.3. Defects detection of pharmaceutical packagings In the next example, a vial closed with a rubber stopper and an aluminum cap and fixed in a SID plastic container (type C) has been investigated. The liquid contained in the vial has leaked although the assembly seems integer and impervious after visible observation. The X-ray live shadow imaging of the glass vial (Fig. 12), prior to scanning, helps drawing a quick diagnosis of the defect: a glass part is missing. A surface determination has been applied on the object to define glass boundaries. A reference cylinder has been created and adjusted on the vial. Afterwards the vial and the reference cylinder have been aligned. Fig. 13 shows a 2D top view of the assembly and a front view placed in the middle section of the vial. The defect is clearly identified: a glass part is missing and the aluminum cap is bent, thus leading to a leak defect.
Fig. 13. 2D views of the vial showing glass part missing. (A) Shows a view of the vial top: the glass part missing is clearly visible (top view). (B) Shows a middle section of the vial after alignment with a reference cylinder (front view).
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Fig. 14. Sealing defect in glass vial. (A) Shows a 2D top view of the glass vial. 2 glass defects highlighted with green circles are visible. 2 red cylinders have been created to assess these glass distortions. There is no contact between glass and plastic at these glass distortions locations, thus the vial is not impervious. (B) Shows a middle section of the vial and the location of the top view (A). (C, D) are respectively zooms of (A, B). (For interpretation of the references to color in figure legend, the reader is referred to the web version of the article.)
Leaks may also be caused by a glass distortion. Fig. 14 shows a glass vial with a plastic cap after CT scan. A segmentation on glass has been performed. Two reference cylinders have been created and aligned to the vial to highlight the glass distortion. The glass surface is not cylindrical that is why leak problems are likely to occur. 4. Conclusion The examination of the samples regarding 3D reconstructions via virtual 3D cuttings, rotations and 2D views as well as shadow live imaging showed that micro CT was well suited for: -
material and assembly checks; verification of integrity; metrology; detection of defects.
The micro CT provides non-destructive internal analyses, thus being an important advantage over other traditional methods like those using tactile or optical coordinate measurement machines. It allows quality control of samples having non accessible internal features or multi-material components. The examination of the internal parts within the sample allows seeing their shape in their built position in 3D whereas when opened, the spatial relationships cannot be assessed anymore, which could be problematic to understand functional mechanisms. That is why micro CT is particularly convenient for medical device and pharmaceutical packaging that sometimes have complex assembly and functional mechanisms as well. This technology is innovative for biomedical and pharmaceutical industry since it can be used to improve the manufacturing processes while reducing defects. X-ray shadow live imaging could be installed on-line to perform quick checks during assembly. For
deeper investigations such as measurements and off-line checks, 3D image processing can be performed.
References [1] J. Ambrose, Radiologists who co-developed computer tomography and performed the first scan, Br. Med. J. 332 (2006) 977. [2] C. Richmond, Jamie Ambrose modest radiologist who helped to pioneer the CT scanner, Guardian (2006). [3] S.R. Stock, Trends in the micro- and nanoComputed Tomography 2010–2012, in: Proc. SPIE 8506, Developments in X-ray Tomography VIII, 850602 (17 October 2012), 2012. [4] J. Alba-Tercedor, I. Sanchez Almazo, The use of micro-CT for the study of eggs and development of two microtomographs, Microsc. Anal. 11 (2014) 7–10. [5] S.J. Schambach, S. Bag, L. Schilling, C. Groden, M.A. Brockmann, Application of micro-CT in small animal imaging, Methods 50 (1) (2010) 2–13. [6] S. Faulwetter, T. Dailianis, K. Vasileiadou, M. Kouratoras, C. Arvanitidis, Can micro-CT become an essential tool for the 21st century taxonomist? An evaluation using marine polychaetes, Microsc. Anal. 11 (2014) S9–S12 (tomography and 3D reconstruction supplement). [7] Á. Görög, B. Szinger, E. Tóth, J. Viszkok, Methodology of the micro-computer tomography on foraminifera, Palaeontol. Electron. 15 (1) (2012) 3T. [8] F. Dzar Eljabbar Latief, U. Fauzi, S. Feranie, Digital isolation technique for reconstruction and visualization of cracks in micro-CT images of geothermal reservoir rock, Microsc. Anal. 11 (2014) 13–17. [9] D.R. Baker, L. Mancini, M. Polacci, M.D. Higgins, G.A.R. Gualda, R.J. Hill, M.L. Rivers, An introduction to the application of X-ray microtomography to the three-dimensional study of igneous rocks, Lithos 148 (2012) 262–276. [10] N.N. Naik, A.C. Jupe, S.R. Stock, A.P. Wilkinson, P.L. Lee, K.E. Kurtis, Sulfate attack monitored by microCT and EDXRD: influence of cement type, water-to-cement ratio, and aggregate, Cem. Concr. Res. 36 (2006) 144–159. [11] L. Salvo, P. Cloetens, E. Maire, S. Zabler, J.J. Blandin, J.Y. Buffiere, W. Ludwig, E. Boller, D. Bellet, C. Josserond, X-ray micro-tomography an attractive characterization technique in materials science, Nucl. Instrum. Methods Phys. Res. B 200 (2003) 273–286. [12] L. De Chiffre, S. Carmignato, J.-P. Kruth, R. Schmitt, A. Weckenmann, Industrial applications of computed tomography, CIRP Ann. – Manuf. Technol. 63 (2) (2014) 655–677. [13] B.C. Hancock, M.P. Mullarney, X-ray microtomography of solid dosage forms, Pharm. Technol. (2005) 92–100. [14] F. Dubois, Reconstruction des images tomographiques par retro-projection filtrée, Revue de l’ACOMEN 4 (2) (1998) 8.
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[15] R. Gordon, R. Bender, G.T. Herman, Algebraic Reconstruction Techniques (ART) for three-dimensional electron microscopy and X-ray photography, J. Theor. Biol. 29 (3) (1970) 471–476. [16] L.A. Feldkamp, L.C. Davis, J.W. Kress, Practical cone-beam algorithm, J. Opt. Soc. Am. 1 (6) (1984) 612–619. [17] X. Thibault, J.F. Bloch, E. Boller, Felt structure characterized by synchrotron micro-tomography, Appita J. 55 (2) (2002) 145–148.
[18] J.F. Bloch, La revue de Metallurgie, 29–31, Octobre 2001, SF2M Paris, 2001, p. 87. [19] J.-P. Kruth, M. Bartscher, S. Carmignato, R. Schmitt, L. De Chiffre, A. Weckenmann, Computed tomography for dimensional metrology, CIRP Ann. – Manuf. Technol. 60 (2) (2011) 821–842. [20] F. Hoffmann-La Roche Ltd., Innovative process ensures innovative drug delivery to patients, Suppl. Pharm. Eng. 31 (3) (2011) 38–43.
Contents lists available at ScienceDirect
Journal of Pharmaceutical and Biomedical Analysis journal homepage: www.elsevier.com/locate/jpba
Review
Micro Computer Tomography for medical device and pharmaceutical packaging analysis Florine Hindelang, Raphael Zurbach, Yves Roggo ∗ Complaint and Counterfeit Department, Quality Control for Commercial Bulk Products, F. Hoffmann-La Roche Ltd, Wurmisweg, CH-4303 Kaiseraugst, Switzerland
a r t i c l e
i n f o
Article history: Received 9 December 2014 Received in revised form 21 January 2015 Accepted 22 January 2015 Available online 9 February 2015 Keywords: X-ray microtomography Medical device Defect detection Quality control 3D imaging
a b s t r a c t Biomedical device and medicine product manufacturing are long processes facing global competition. As technology evolves with time, the level of quality, safety and reliability increases simultaneously. Micro Computer Tomography (Micro CT) is a tool allowing a deep investigation of products: it can contribute to quality improvement. This article presents the numerous applications of Micro CT for medical device and pharmaceutical packaging analysis. The samples investigated confirmed CT suitability for verification of integrity, measurements and defect detections in a non-destructive manner. © 2015 Elsevier B.V. All rights reserved.
Contents 1. 2.
3.
4.
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Material and method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Micro CT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1. General principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2. Factors influencing X-ray imaging process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1. Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2. Analyzed samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1. Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2. Reconstruction and image analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Verification and measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1. Material/assembly checks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2. Quality control (testing technique) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.3. Integrity checks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.4. Shadow live imaging for quick internal integrity checks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Detection of defects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1. Defects detection inside mechanical devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2. Defects detection inside electronic devices and metrology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3. Defects detection of pharmaceutical packagings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
∗ Corresponding author at: F. Hoffmann-La Roche Ltd, Wurmisweg, Building 250, CH-4303 Kaiseraugst, Switzerland. Tel.: +41 061 68 81 336. E-mail addresses: fl[email protected] (F. Hindelang), [email protected] (R. Zurbach), [email protected] (Y. Roggo). http://dx.doi.org/10.1016/j.jpba.2015.01.045 0731-7085/© 2015 Elsevier B.V. All rights reserved.
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1. Introduction Over the last 25 years and since the invention of the first CT-scanner prototype by Hounsfield in 1969 [1,2], computer technology has greatly improved, allowing details in the reconstructed images with pixel sizes in the nanometer range [3]. Micro Computer Tomography nowadays applies to many domains such as biology [4,5], taxonomy [6], paleontology [7], geology [8–10], material science [11], medicine or automotive industry [12]. It has been involved in the pharmaceutical industry to help understand and improve the development and manufacturing processes of medicine during Quality by Design studies [13]. Indeed Micro CT allows a direct observation on the impact of physical parameters set during the drug elaboration (cracks, surface defects, or internal failures). Currently drugs are directly designed within medical devices and delivered by mean of physical, mechanical, or thermal means. Those mechanisms could also encounter defects or technical problems. The CT systems are convenient for testing both internal and external structures of objects without contact, by carrying out nondestructive 3D measurements. That is why this technique can also be applied to medical device and pharmaceutical packaging that until now have been otherwise impossible to visualize without opening them, thus leading to a possible damage and loss of structure information. This article presents the suitability of Micro CT system for the analysis of medical devices and pharmaceutical packaging. Objects can be virtually handled for a variety of quality control purposes, including verification of integrity, measurements and defect detections. Hence there is the potential to improve the overall building processes thus avoiding structure or mechanism defects and ensure the best quality and safety for patients.
Fig. 1. Micro CT instrumentation. X-rays are directed from the-X-ray source toward the sample. A detector placed on the opposite side of the sample measures the intensity of the transmitted X-rays.
done in most studies as a first step [17,18]. Semi-transparent representations can provide a fast three-dimensional overview of the work piece edges, and defects in components.
2.1. Micro CT
2.1.2. Factors influencing X-ray imaging process The resolution of CT measurement and reconstruction is influenced by many factors that have to be taken into account while using micro CT technology. The review paper [19] presents parameters and factors having an impact on CT measurements and those allowing avoiding artifacts which are responsible for images imperfections. Only a quick overview of the latter is given hereafter, as well as the most common encountered artifacts. Finally the purpose of CT scanning may also influence X-ray imaging process.
2.1.1. General principle Micro CT is a 3D imaging technique allowing the virtual reconstruction of objects with pixel size in the micrometer range. Whether a sample is rotated relative to a static X-ray source and a detector or the X-ray source and the detector move around the sample. Only the first case will be considered in this article. Xrays generated by the source are emitted toward the sample. When crossing the sample, X-rays are attenuated according to the length traveled in the absorbing material (thickness), to the material composition and its density (i.e. attenuation coefficient). The detector on the opposite side of the sample measures the intensity of the transmitted X-rays (Fig. 1). The varying levels of signal intensity provide a gray-scale representing the sample and its properties: the X-ray shadow image. This high-resolution X-ray shadow image can be seen live on the monitor of the micro-CT device. X-ray transmission images are collected at multiple discreet angular steps like a map of the relative atomic density of the sample. The 2D gray images projections, called slice plans, are reconstructed using mathematical (e.g. Filtered Back Projection FBP [14]) and iterative algorithms (e.g. Algebraic Reconstruction Technique ART, based on successive estimations of solutions [15]). In case of a cone beam source, which induces modification of the projection plane during sample’s rotation, the reconstruction is based on Feldkamp algorithm [16]. Finally, the reconstructed 2D radiographs are gathered and stacked together. As a result, the complete 3D map of the sample is computed and available for further processing (Fig. 2). Image analysis software is designed to simultaneously observe the 3D object view, and the three 2D cross sections. 3D visualization is
• Parameters and factors Not only the parts of the equipment (source, detector) but also the analyzed sample, the measurement setup parameters and the user play an important role in the whole X-ray imaging process. They are all connected together. - Source: The type and material of the target of the X-ray source have an influence of the radiation properties i.e. shape, intensity and quality. The power of the X-ray beam, affected by the source current and source voltage, has to be adjusted for each sample analyzed, according to their density, geometry, etc. High absorbing materials will need high energy exposure to be visible, but low absorbing materials will not be visible. On the contrary, low absorbing material will only need low energy exposure, but artifacts or total extinction could appear due to the presence of high absorbing neighboring materials. - Sample and environment: The sample orientation and thickness influence the amount of measuring noise and scatter (see artifacts hereafter). Optimal sample orientation should avoid part surfaces that are parallel to the X-ray beam, as beam scattering is then favored and leads to instabilities in 3D reconstruction. Also temperature control is important to avoid measurements errors. Vendors advise to have the CT equipment in an airconditioned room. - Detector: Detector sensitivity will also impact the resulting 3D image and in particular the number of angular poses at which images are taken. The more the angular poses, the more the improvement of reconstruction accuracy, but the larger the measurement time.
2. Material and method
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F. Hindelang et al. / Journal of Pharmaceutical and Biomedical Analysis 108 (2015) 38–48
Fig. 2. Principle of Micro CT from measurement to reconstruction.
- User: The CT strategy via user influence is also at stake since user defines the best parameters for each CT scan: current (impact on image contrast), voltage (impact on image brightness), integration time (impact on scanning time and image quality). Possibility is given to measure the whole object at once or in parts by selecting a Region of Interest ROI, for instance. ROI scanning allows measuring specific regions (volume portions) without reconstructing the whole object, often time consuming. The focus on a portion allows concentrating effects of quality adjustments. Other parameters such as choice and use of filters (impact on image quality and artifacts), voxel resolution, etc. are also part of this strategy.
• Artifacts Among common artifacts, beam hardening, scattering, metal artifacts can be mentioned. - Beam hardening is due to different photons energy in the beam, resulting in difficult edge detection as the borders of the sample constitutive elements are not clearly defined. Indeed, the gray values of edge pixels are altered. The use of Cu or Al plates between the source and the sample allow avoiding the problem but it reduces the beam intensity. - Scattering: Other artifacts like scattering, causing halos around materials, are due to deflection of X-ray inside the sample or the detector.
Table 1 Micro CT parameters used for presented examples. Sample description/identification
Voltage (kV)
Current (mA)
Integration time (s)
Filtera
Reconstruction mode 1 = single 2 = multiple
Projections number
Qualityb (low/standard/ high) + resolutionc (premium/quick)
DAI activated/not activated/Fig. 3 Vial: thickness of glass/Fig. 5 Vial: Alu cap and flip-off cap/Fig. 6 RNS syringes: integrity check/Fig. 7 DAI broken/Fig. 9 SID defect: needle not in vial/Fig. 10 SID defect: needle bent in septum/Fig. 11 Part SID: glass missing in vial/Figs. 12 and 13 Glass distortion in vial/Fig. 14
150
5
0.74
1.5
2
360
Standard + premium
225 200
3.55 3.1
1 1.7
2 2
2 1
960 620
Standard + premium Standard + premium
50
2.2
2
None
N.A.
N.A.
N.A.
95 220
2.5 3.6
1.5 2
1 3
2 2
430 830
Standard + premium Standard + premium
100
8
0.56
1
1
900
High + premium
95
2.5
1.85
1
1
850
High + premium
180
1.6
1.7
1.5
1
480
Standard + premium
a b c
Filter = filter 1: 4 mm, filter 1.5: 1 mm, filter 2: 2 mm, filter 3: 4 mm. Quality = related to number of projections. Resolution = voxel resolution (low 168 m, standard 84 m, high 42 m).
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- Metal artifacts: these artifacts are due to the presence of metal with high absorption properties compared to other parts. It results in high brilliancy distortions, or ghost images in the reconstructed CT images. • Purpose of CT scanning The scanning parameters are chosen according to the final purpose of CT scan: shadow live imaging, defect analysis, 3D inspections, etc. - For X-ray live imaging, importance will be given to optimized contrast and brightness between constitutive elements, i.e. voltage and current settings will be highlighted, as well as the use of filters. The purpose of this is to get a picture, were the constitutive materials are distinguishable and possible defects are detectable thanks to gray shading. - For defect analysis, integrity checks, requesting a CT scan, all parameters mentioned above will be taken into account but quality may be medium (related to number of projections and voxel resolution), as long as constitutive materials are distinguishable and possible defects are detectable once object is reconstructed. - For 3D inspections, metrology and deep investigations inside scanned objects, the efforts will be focused on all parameters since the goal is to find a good compromise between them all to obtain the best reconstructed images with minimized imperfections. Afterwards, image processing (separation of the constitutive materials, measurements, etc.) will be eased and all the more representative of the original object.
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GmbH, Germany and is made of silicon. Its pixel geometry is rectangular. The geometric magnification is 1.2. The equipment is controlled via a computer by “exaCT Control” software, version 2.0.0. from WENZEL Volumetrik GmbH. The reconstruction algorithm is based on Feldkamp classical algorithm [16]. The Wenzel “exaCT Control” software has two reconstruction modes, depending on the size of the sample analyzed. If the object size is smaller than the out coming X-ray beam and/or the detector’s height, then the direct 3D reconstruction can be computed in a single step; the reconstruction mode is then “single”. However if the object size is taller than the beam and/or the detector’s height, the slices of the object are reconstructed separately and concatenated afterwards; the reconstruction mode is then “multiple”. 3D inspections and defect analysis of the object have been performed thanks to “VG Studio Max” Software, version 2.2 from Volume Graphics Gmbh.
Optimization of all parameters according to the final CT scan purposes is a hard task as they have an effect on the information content of the resulting image. 2.2. Material 2.2.1. Instrumentation The measurements have been performed on a Micro Computer Tomography system, the CT workstation exaCT from WENZEL Volumetrik GmbH, Germany. It uses a Perkin Elmer X-ray source with large conic analyzing beam, enveloping objects up to 150 mm of diameter and 300 mm of height. It possesses a maximum acceleration voltage of 225 kV and a corresponding power of 800 W. The detector is a flat panel detector developed by WENZEL Volumetrik
Table 2 Image processing actions for presented examples. Sample description/Identification
Image processing actions
DAI activated/not activated/Fig. 3 Vial: thickness of glass/Fig. 5 Vial: Aluminum cap and flip-off cap/Fig. 6
Segmentation
RNS syringes: integrity check/Fig. 7 DAI broken/Fig. 9 SID defect: needle not in vial/Fig. 10 SID defect: needle bent in septum/Fig. 11 Part SID: glass missing in via l/Figs. 12 and 13 Glass distortion in vial/Fig. 14
Wall thickness analysis Segmentation alignment with reference object Reference object for roundness N.A. Segmentation Segmentation Comparison/superposition Segmentation Alignment with reference object Size measurement Segmentation Alignment with reference object Segmentation Alignment with reference object Reference object for cylindricity
Fig. 3. Verification DAIs activated, not activated. Before activation (DAI A), the metal springs are compressed. After activation (DAI B), the metal springs are relaxed.
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Fig. 4. Principle of segmentation histogram with gray values. Each constitutive material is represented by a peak. The choice of a gray value serves as a threshold that determines the material boundary: brighter areas are considered as material, darker areas are considered as background. (A) Standing for an example of mono-material (glass vial), the segmentation process defines the interface between glass (material) and the surrounding air (background). (B) Standing for an example of multi-material, an iteration of the segmentation process should be performed in order to split the whole dataset in a list of sub-volumes so as to define the interface between different materials. For each iteration, unwanted structures are removed from the image to keep the material of interest.
2.2.2. Analyzed samples Experiments have been conducted on 2 types of samples: - medical devices; - pharmaceutical packaging. Medical devices investigated are disposable auto-injectors DAI (named A), single injection devices SID (named B), part of SID (named C) and Rigid Needle Shield syringes (named D). The DAI A is a single-use infusion device that works mechanically. It is made of a cap, an indicator window, an activation button and a needle guard. When the patient presses the activation button, a spring is relaxed to inject the drug. Afterwards, an indicator window confirms that the dose has been administered.
On the contrary, the SID B is an electronic single-use infusion device that works with a motor. It consists of about 80 individual components and allows the administration of oncology drug. The cartridge containing the drug is housed in a fluidic path container and set in motion by the motor. The patient activates the mechanism by pushing the start button. The needle penetrates in the patient’s body. The battery driven motor depresses the piston down and the drug is injected subcutaneously. After the drug administration, the needle is removed from the patient’s body and kept secured in the device, to avoid further injuries during manipulation [20]. Rigid Needle Shield syringes D are used to reduce needle tip damage, for better grip of needle shield and to reduce risk of needle injuries.
F. Hindelang et al. / Journal of Pharmaceutical and Biomedical Analysis 108 (2015) 38–48
Pharmaceutical packaging investigated are glass bottles, glass vials, aluminum caps of vial and rubber stoppers. 2.3. Method 2.3.1. Acquisition For each sample, a base of low density foam (polystyrene) has been created to fix the object. This foam has the advantage of being transparent to X-rays. The object has been centered as much as possible on the foam, to reduce the region to scan and limit mechanical collisions inside the device. For non-cylindrical or nonspherical objects a slight recommended tilt (3–5◦ ) has been applied to enhance the acquisition process and avoid artifacts [19]. Before starting acquisition, proper parameters have been selected and optimized based on the X-ray live shadow imaging to acquire the best object projections:
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- resolution; - quality mode. Table 1 details all parameters used for the different examples.
2.3.2. Reconstruction and image analysis After reconstruction in 3D pixels (so-called voxels) of the object, analysis and processing of the object volume data have been started. Segmentation of different materials within scanned objects has been performed based on the histogram of the frequency of occurrence of the different gray values within the scanned volume. Other handlings like Superposition/Alignment of objects, Comparison with reference objects and Measurements tools have been employed to investigate samples. Table 2 highlights the processing steps used for each example.
-
voltage; current; integration time; filter (filter material is aluminum alloy for low filters and copper alloy for high ones. Exact composition is confidential data, not communicated by the supplier); - reconstruction mode (single or multiple);
Fig. 5. Measurement of vials wall thickness. The chart displays the distribution of the different thicknesses (x-axis in mm) among glass vials.
Fig. 6. Verification of integrity for aluminum cap. (A) Shows the 3D view where the aluminum cap has been colored in gray and the flip-off cap in purple. (B) Shows the 2D front view in the middle section of the cap: a reference circle (radius 10 mm) has been created for assessing aluminum cap integrity. (For interpretation of the references to color in figure legend, the reader is referred to the web version of the article.)
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Fig. 7. X-ray live shadow imaging for verification of RNS syringes integrity. The syringe A is a reference syringe and no de-capping/re-capping has been performed. The needle is straight in the RNS. The syringe B is a defective syringe. After de-capping/re-capping, the needle is bent and has penetrated the RNS.
3. Results and discussion 3.1. Verification and measurement 3.1.1. Material/assembly checks In the first example (Fig. 3), two Disposable Auto Injectors (DAIs) type A have been scanned separately. Segmentation has been performed so as to distinguish the constitutive materials and compare the overall built structure of an activated and non-activated DAI sample. Segmentation is a procedure that allows separating constitutive materials of a scanned object (named volume). Indeed, the distribution of the materials densities is given in a histogram of the frequency of occurrence of the different gray values in the volume (Fig. 4): each peak represents a constitutive material. A surface determination can be defined by choosing a gray value applied globally to the object and corresponding to a material of interest. This gray value serves as a threshold that determines the material boundary: brighter areas are considered as material, darker areas are considered as background. In Fig. 4A, standing for an example of mono-material (glass vial), the segmentation process defines the
Fig. 8. Example of needle bent in a disposable injection device. The segmentation allows a view of the components inside the device. Here, the needle is bent.
interface between glass (material) and the surrounding air (background). In Fig. 4B, standing for an example of multi-material, an iteration of the segmentation process should be performed in order to split the whole dataset in a list of sub-volumes so as to define the interface between different materials. For each iteration, unwanted structures are removed from the image to keep the material of interest. The result is that each component is distinguished from another and can be differentiated by a color rendering. The selection of the threshold is a critical parameter during the segmentation
Fig. 9. Broken DAI. The metal parts have been colored in yellow and the glass parts in red. Here, the glass syringe has broken into pieces and the metal spring guide rod is not in the axis. The device is broken. (For interpretation of the references to color in figure legend, the reader is referred to the web version of the article.)
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Fig. 10. Comparison of a defective SID with a reference SID. The SID gray A is in its initial state: the springs are compressed. The SID green B is a reference sample: it has been activated thus the springs are relaxed. (C) Shows the superposition of A and B: the differences between springs are easily visible. (For interpretation of the references to color in figure legend, the reader is referred to the web version of the article.)
of the micro CT data and can influence the measurement results (e.g. length, diameter, resolution, etc.) [19]. The constitutive materials have been separately processed and colored to be easily distinguishable. The metal parts (springs and needle) have been colored in yellow. The glass syringe has been colored in red. Light plastics have been colored in light blue and heavy ones in purple. The materials are visible all at once and cuts allow an overall view of the internal side of the device. The DAI on the left (picture A) is in its initial state and has not been activated. The metal springs, colored in yellow, are compressed. The DAI on the right (picture B) has been activated; the springs are relaxed.
3.1.4. Shadow live imaging for quick internal integrity checks In the next case, the aim of the study was to check the integrity of RNS syringes D, in other words assess whether the needle had penetrated the rubber after a de-capping/re-capping experience. Fig. 7A shows a reference RNS syringe, as it is initially. Fig. 7B shows the result after a de-capping/re-capping test: the needle is not straight and it has penetrated the RNS. In this case, the CT-scan was not necessary as the consequence of the test appeared obvious. Shadow live imaging is of great interest for big batches such as this one made of 80 syringes for fast verification. One could imagine setting a micro CT directly on the manufacturing chain for quick live checks. 3.2. Detection of defects
3.1.2. Quality control (testing technique) In the following example, the wall thickness of glass vials has been checked. To do so, a series of vial samples has been scanned and investigated with the wall thickness tool. Fig. 5 shows the obtained results. The chart displays the distribution of the different thicknesses. Most values are included in the range 0.976–1.061. This tool could be interesting to use in case of lyophilization problems for instance, since the glass thickness homogeneity could be checked. 3.1.3. Integrity checks A vial cap (Fig. 6A) has been segmented thanks to surface determination to easily distinguish the two constitutive elements: the flip-off cap made of plastic has been color rendered in purple whereas the aluminum cap made of aluminum has been color rendered in gray. In Fig. 6B, showing a 2D view, a reference circle has been created and adapted on the glass to check the morphology of the cap and conclude about a possible damage during manipulation. The cap is intact and no damage is visible.
3.2.1. Defects detection inside mechanical devices In the following example, a defective DAI A has been investigated. After segmentation of the constitutive materials, it appeared that the metal needle, kept inside the device, was bent (Fig. 8). The exact position of the curvature could be assessed without opening or breaking the device. Another example of DAI is presented in Fig. 9. It is a complaint sample returned for investigations: during last phase of infusion, needle remained in patients’ body and the auto injector broke into pieces in hands of the doctor. After 3D scan, the device has been segmented in its constitutive materials. The result is that the device is completely damaged. The glass syringe has broken into pieces and the spatial and functional relationships between components are compromised. 3.2.2. Defects detection inside electronic devices and metrology The first example, a SID type B, is a complaint sample coming from a patient. When the latter pressed the start button of the device, nothing happened and the device automatically stopped. No
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Fig. 12. X-ray preview of a vial with glass part missing.
Fig. 11. Defect detection, needle in septum. The metal needle is not straight in the vial and partially in the rubber, preventing the drug from being correctly delivered. (B) Shows different measurements performed with the software caliper tool.
drug was delivered to the patient. A CT scan has been performed on this defective sample. The metallic parts, namely springs and needles have been segmented and colored in gray (Fig. 10A). In the meantime, a CT scan has been performed on a reference sample, with successful delivery so as to compare both. The metallic parts, namely springs and needles have been segmented and colored in green (Fig. 10B). The sample and the reference have been superposed to easily detect differences. Fig. 10C shows the superposition of the defective and reference samples. The metal springs of the reference are relaxed. On the contrary, those of the defective sample are still in their initial state: compressed.
In the second case of SID type B, which is also a complaint sample, the device started delivering the drug after activation. But it quickly stopped, before the delivery was completed. A CT scan has been performed. Fig. 11A shows that the cartridge needle is not straight in the vial and the needle aperture is partially in the stopper. As a result, the liquid cannot flow through the hole of the needle toward the external needle which penetrates the patient body and the drug cannot be entirely delivered. In Fig. 11B, some sizes have been checked thanks to measurement tools available on the software. Theses sizes have been compared to the supplier specifications to assess the defect. An overpressure in the device has made the delivery system prematurely stop. In this case, as the liquid inside the vial and the stopper have similar densities, the contrast has been improved by finding a good compromise between gray values and opacity, thus allowing the visualization of the stopper border. 3.2.3. Defects detection of pharmaceutical packagings In the next example, a vial closed with a rubber stopper and an aluminum cap and fixed in a SID plastic container (type C) has been investigated. The liquid contained in the vial has leaked although the assembly seems integer and impervious after visible observation. The X-ray live shadow imaging of the glass vial (Fig. 12), prior to scanning, helps drawing a quick diagnosis of the defect: a glass part is missing. A surface determination has been applied on the object to define glass boundaries. A reference cylinder has been created and adjusted on the vial. Afterwards the vial and the reference cylinder have been aligned. Fig. 13 shows a 2D top view of the assembly and a front view placed in the middle section of the vial. The defect is clearly identified: a glass part is missing and the aluminum cap is bent, thus leading to a leak defect.
Fig. 13. 2D views of the vial showing glass part missing. (A) Shows a view of the vial top: the glass part missing is clearly visible (top view). (B) Shows a middle section of the vial after alignment with a reference cylinder (front view).
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Fig. 14. Sealing defect in glass vial. (A) Shows a 2D top view of the glass vial. 2 glass defects highlighted with green circles are visible. 2 red cylinders have been created to assess these glass distortions. There is no contact between glass and plastic at these glass distortions locations, thus the vial is not impervious. (B) Shows a middle section of the vial and the location of the top view (A). (C, D) are respectively zooms of (A, B). (For interpretation of the references to color in figure legend, the reader is referred to the web version of the article.)
Leaks may also be caused by a glass distortion. Fig. 14 shows a glass vial with a plastic cap after CT scan. A segmentation on glass has been performed. Two reference cylinders have been created and aligned to the vial to highlight the glass distortion. The glass surface is not cylindrical that is why leak problems are likely to occur. 4. Conclusion The examination of the samples regarding 3D reconstructions via virtual 3D cuttings, rotations and 2D views as well as shadow live imaging showed that micro CT was well suited for: -
material and assembly checks; verification of integrity; metrology; detection of defects.
The micro CT provides non-destructive internal analyses, thus being an important advantage over other traditional methods like those using tactile or optical coordinate measurement machines. It allows quality control of samples having non accessible internal features or multi-material components. The examination of the internal parts within the sample allows seeing their shape in their built position in 3D whereas when opened, the spatial relationships cannot be assessed anymore, which could be problematic to understand functional mechanisms. That is why micro CT is particularly convenient for medical device and pharmaceutical packaging that sometimes have complex assembly and functional mechanisms as well. This technology is innovative for biomedical and pharmaceutical industry since it can be used to improve the manufacturing processes while reducing defects. X-ray shadow live imaging could be installed on-line to perform quick checks during assembly. For
deeper investigations such as measurements and off-line checks, 3D image processing can be performed.
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