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Detection of lung cancer tissue by attenuated total reflection–Fourier transform infrared spectroscopy—a pilot study of 60 samples
j o u r n a l o f s u r g i c a l r e s e a r c h 1 7 9 ( 2 0 1 3 ) 3 3 e3 8
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journal homepage: www.JournalofSurgicalResearch.com
Detection of lung cancer tissue by attenuated total reflectioneFourier transform infrared spectroscopyda pilot study of 60 samples Xiaoliang Sun, MD,a Yizhuang Xu, PhD,b Jinguang Wu, PhD,b Yuanfu Zhang, PhD,b and Kelin Sun, MDa,* a
Department of Thoracic Surgery, Cancer Institute and Hospital, Chinese Academy of Medical Science, Peking Union Medical College, Beijing, China b State Key Laboratory of Rare Earth Material Chemistry and Application, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
article info
abstract
Article history:
Background: Attenuated total reflectioneFourier transform infrared (ATReFTIR) spectros-
Received 22 May 2012
copy could serve as a diagnostic tool for detecting and discriminating different diseases.
Received in revised form
The aim of this preliminary study was to distinguish malignant and nonmalignant lung
21 August 2012
tissues with ATReFTIR spectroscopy.
Accepted 30 August 2012
Methods: Sixty lung tissue samples were obtained from 30 patients who underwent
Available online 21 September 2012
pulmonary lobectomy. Samples were examined with ATReFTIR spectroscopy before histologic diagnosis. Peak positions, intensities, and full width at half maximum of each
Keywords:
absorbent band were measured, and the relative intensity ratios were calculated. Canon-
ATReFTIR
ical discriminant analysis was performed to discriminate malignant and nonmalignant
Mid-infrared radiation
groups.
Spectrum
Results: Twenty-two parameters were significantly different between malignant and
Lung tumor
nonmalignant groups. Peak intensity at 1546/cm, intensity ratio at 1120/cm, and full width
Canonical discriminant analysis
at half maximum at 1303 and 1240/cm were selected as independent factors to form
Frozen section diagnosis
discriminant functions. The sensitivity and specificity of the discriminants were all 96.7%.
Histologic examination
Conclusions: ATReFTIR spectroscopy is a promising method for the detection of malignant
Low-dose computerized
lung tissue and could be proved useful in lung tumor surgery.
tomography
ª 2013 Elsevier Inc. All rights reserved.
Sensitivity Specificity
1.
Introduction
Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer death globally. It accounts for 13% (1.6 million) of the total cancer cases and 18% (1.4 million) of
the deaths in 2008. Lung cancer rates are increasing in countries such as China and several other countries in Asia and Africa [1]. Overall, the 5-y survival rate is approximately 15%, whereas the 5-y survival rate for patients with surgically resected early-stage disease is 60%e80% [2]. The present
* Corresponding author. Department of Thoracic Surgery, Cancer Institute and Hospital, Chinese Academy of Medical Science, Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China. Tel.: þ86 108778 7160; fax: þ86 108778 8909. E-mail address: [email protected] (K. Sun). 0022-4804/$ e see front matter ª 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jss.2012.08.057
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j o u r n a l o f s u r g i c a l r e s e a r c h 1 7 9 ( 2 0 1 3 ) 3 3 e3 8
paradigm is that most of the untreated lung cancers are rapidly fatal, and consequently, early surgical intervention is mandatory [3]. The introduction of low-dose computerized tomography (LDCT) allows the detection of much smaller nodules (3e5 mm) and small peripheral lung cancer [4]. A large number of review studies have been published on lung cancer LDCT screening in recent years and conclude that its sensitivity ranges between 86.5% and 98.0%, whereas the false-positive rate remains as high as 6%e38% [5]. Preoperative diagnosis of small intrapulmonary nodules with transbronchial or transthoracic biopsies is hard to make as it is difficult to get enough materials or biopsy from deep location [6,7]. A successful limited resection is based on accurate intraoperative frozen section diagnosis (FSD). However, as inflammatory and fibrotic lesions can be confused for malignancy, intraoperative diagnosis becomes a dilemma for the pathologists and thoracic surgeons [8]. The Fourier transform infrared (FTIR) spectroscopy, with the absorption of electromagnetic radiation from 400 to 4000/cm, is sensitive to changes in molecular compositions and structures. It permits rapid collection of spectra obtained from millimeter-sized samples and could detect biochemical signatures of tissues that associated with generation and progression of disease [9,10]. FTIR spectroscopy has been applied to some types of organs and suggested as an objective method [11,12]. The attenuated total reflection (ATR) detection, installed to the FTIR spectroscopy equipment, is independent of sample thickness. Thus, ATReFTIR spectroscopic technique is reagent free and requires minimal or no sample pretreatment before spectral measurements [13e15]. In this pilot study, ATReFTIR spectra of malignant and nonmalignant lung tissues were acquired and compared. Canonical discriminant analysis (CDA) was performed to classify the two groups.
2.
Materials and methods
2.1.
Tissue collection
ATReFTIR spectroscopic analysis, all lung samples were fixed in formalin and then processed for histologic examination at the Pathology department of Chinese Academy of Medical Science.
2.2.
FTIR spectra acquisition
A WQF-600 FTIR spectrometer (Beijing Rayleigh Analytical Instrument Corporation, Beijing, China) was used in this study. After thawing in room temperature, lung tissues were mounted on an ATR plate attached to FTIR spectroscopic equipment. Mid-infrared (IR) radiation (wave number range, 1000e4000/cm) was passed to and from the ATR accessory. Spectra were measured at a resolution of 4/cm, and 32 scans were coadded to achieve a good signal-to-noise ratio. Background spectrum was recorded before every sample scanning and was subtracted automatically to eliminate atmospheric effects. The procedure took approximately 1e2 min for every sample. After scanning, distilled water and alcohol were used to clean the ATR plate. After air-drying of the ATR plate, another sample tissue was mounted on the plate and scanned for spectrum. The technicians there were well trained and blinded to whether the sample is malignant or benign.
2.3.
Statistical analysis
OMNIC software developed by Thermo Electron Corporation (Thermo Nicolet, Boston) was used in harvesting spectra. The peak intensity, peak position, and full width at half maximum (FWHM) of each band were measured using SpaPro version 2.2 software (College of Chemistry and Molecular Engineering, Peking University, Beijing, China). The peak intensity at 1460/cm is the most stable band in the intensity parameters; therefore, the relative intensity ratios were calculated as peak intensity/intensity at 1460/cm. FTIR parameters of malignant and nonmalignant samples of the two groups were compared.
Table 1 e Clinical characteristics of 30 patients with lung tumor. Characteristics
This study was approved by the Cancer Institute and Hospital, Chinese Academy of Medical Science board. Patients were enrolled after being given information about the study and providing written informed consents. For the study, 60 lung tissues were collected from 30 patients with pulmonary lobectomy surgery from January 2009 to February 2010. The average age of the patients was 58.5 y (range, 33e75 y). For every patient, interested samples were removed from the center of the tumor lesion and the distal margin of the dissected lung lobe during operation. Once the tissues were harvested, they were collected immediately by one member of our research team, who is in charge of tissue collection and made the corresponding record of every sample. Samples were immediately prepared to <0.5 cm in diameter and preserved in liquid nitrogen without other pretreatment. All samples were examined at the College of Chemistry and Molecular Engineering, State Key Laboratory of Rare Earth Material Chemistry and Application, Peking University. After
Median age, y (range) Sex ratio (male:female) Tumor location Superior lobe of left lung Inferior lobe of left lung Superior lobe of right lung Middle lobe of right lung Inferior lobe of right lung Pathologic type Squamous cell carcinoma Adenocarcinoma Small cell carcinoma Pathological TNM classification stage IA IB IIA IIB IIIA IIIB
Number of patients 58.5 (33e75) 16:14 10 3 10 2 5 11 18 1 2 11 2 2 11 2
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Normally, distributed data were analyzed with the t-test; otherwise, the ManneWhitney U test was used. P < 0.050 was considered statistically significant. CDA was used to distinguish malignant and nonmalignant lung samples (SPSS release 11.0.0; Chicago, IL). Wilk lambda stepwise discriminant program was applied to help select variables that contribute most to the discriminant function. Two discriminant equations ðLmalignant and Lnonmalignant Þ were established. Retrospective validation and leave-one-out cross-validation were also used to evaluate the discriminant power of the CDA. Sensitivity (true positives/[true positives þ false negative]) and specificity (true negatives/[true negatives þ false positives]) were calculated. Pathologic results as gold standard were compared with the CDA classification later.
3.
Results
Thirty patients’ clinical characteristics are listed in Table 1. The preliminary peak positions assigned as protein, lipids, carbohydrate, or nucleic acid were shown in Table 2. Of the 60 lung tissue samples, 30 were diagnosed as malignant, whereas the remaining 30 were nonmalignant. Characteristic spectra of malignant and nonmalignant tissues from the same patient were shown in Figure. The differences between the two groups (malignant and nonmalignant lung samples) were shown in Table 3. Of the two groups, peak positions of 1640, 1303, 1120, and 1085/cm were significantly different; peak intensities of 1546, 1460, 1400, 1165, and 1120/cm and relative intensity ratios of 1743, 1640, 1546, 1240, and 1120/cm of the two groups were distinctly different from each other. The differences of FWHM at 1640, 1460, 1400, 1303, 1240, 1165, 1120, and 1085/cm
Table 2 e FTIR assignments of lung tissue samples. Peak position (cm1) 3280 2925 2855 1743 1640 1546 1460 1400 1303 1240 1165 1120 1085
Vibrations
Assignments of substance
nOH, nNH nas, CH3 ns, CH2 nC¼O Amide I Amide II dCH dCH, dCOH dCH, dCOH, Amide III nas, Po 2 nCO, dCOH, nCO-c nCO, dCOH, nCO-c nPo2
Water, protein Lipid related Lipid related Lipid Protein Protein Lipid related Lipid related Undetermined Nucleic acid related Carbohydrate related Carbohydrate related Nucleic acid related
n ¼ stretching vibration; ns ¼ symmetry stretching vibration; nas ¼ asymmetry stretching vibration; d ¼ bending vibration.
between the malignant and nonmalignant sample groups were statistically significant. Functions of CDA were established as follows: Lmalignant ¼ 3:241X1 þ 3:687X2 þ 106:193X3 þ 116:557X4 137:103; Lnonmalignant ¼ 3:613X1 þ 3:200X2 þ 79:639X3 þ 151:923X4 131:738; where X1 represents FWHM at 1303/cm; X2 signifies FWHM at 1240/cm; X3 indicates peak intensity ratio at 1120/cm; and X4 presents as peak intensity at 1546/cm. A comparison of the result between ATReFTIR spectroscopy and histologic examination (gold standard) was shown in Table 4. The sensitivity and specificity of the CDA were all 96.7%.
Fig. e ATR-FTIR spectra of nonmaglinant and malignant lung tumors. (A) Nonmalignant lung tissue and (B) malignant lung tissue. (Color version of figure is available online.)
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Table 3 e ATReFTIR alterations of malignant lung tissues compared with nonmalignant lung samples. Band (/cm)
Peak position MLT
3280 2925 2855 1743 1640 1546 1460 1400 1303 1240 1165 1120 1085
3250.76 2920.87 2849.39 1774.20 1640.47 1542.92 1456.39 1399.97 1313.66 1237.33 1166.11 1122.14 1083.41
(85.34) (8.06) (5.33) (0.5 104) (7.06) (1.23) (2.38) (0.71) (3.13) (2.56) (5.22) (1.41) (1.19)
Peak intensity y
NMLT
P
3234.43 (82.62) 2921.51 (3.18) 2849.91 (4.46) 1774.20 (0.5 104) 1648.74 (4.51) 1542.67 (0.71) 1455.87 (1.93) 1399.45 (1.48) 1310.84 (5.79) 1238.10 (0.40 104) 1167.14 (2.63) 1123.41 (4.15) 1083.93 (0.71)
0.359 0.552 0.435 1.000 <0.001 0.321 0.460 0.088 0.041 0.165 0.978 0.025 0.045
MLT 1.07 7.13 103 5.24 103 6.53 105 0.31 0.05 0.01 0.02 3.78 103 1.16 102 3.06 103 1.78 103 1.30 102
(0.97) (6.90 103) (3.74 103) (2.48 105) (0.10) (0.03) (3.93 103) (6.73 103) (1.39 103) (4.78 103) (2.11 103) (8.41 104) (6.44 103)
MLT ¼ malignant lung tissue (n ¼ 30); NMLN ¼ nonmalignant lung tissue (n ¼ 30). Values are mean (standard deviation). P < 0.050 was considered as statistically significant; P value is two tailed. * Relative intensity ratio ¼ peak intensity/intensity at 1460/cm (1460/cm is the most stable band in the intensity parameters). y t-test for data with a normal distribution and ManneWhitney U test for other data.
4.
Discussion
The advancement of LDCT allows the detection of small lung nodules and small peripheral lung cancer. However, this increases the difficulty of transbronchial or transthoracic biopsies because of the sampling technique limitations [6,7]. Therefore, intraopretive FSDs are frequently performed in these patients [16,17], and it is a very important pathologic examination that can determine the extent of the subsequent surgical procedure. However, FSD has its limitations. First, the peripheral lung lesions as small as 5 mm in diameter are very difficult to diagnose with preoperative biopsies. Many of these patients undergo wedge biopsy and intraoperative FSD and might yield histologic slides difficult to interpret. As a result, some investigators even point that both thoracic surgeons and pathologists need to approach the intraoperative diagnosis of small pulmonary nodules with caution, particularly those <1 cm in diameter [8]. Besides, reactive proliferative epithelial changes in inflamed lung tissue and histologic artifacts can closely simulate malignancy. In this scenario, a dilemma is encountered: either a malignant intraoperative diagnosis based on atypical changes that might be enhanced by the technical artifacts or defer the diagnosis to permanent histologic examinations [18,19]. An equivocal diagnosis such as “atypia defer to permanent sections” in a lung nodule with FSD could delay the correct diagnosis and subjects the patient to increased morbidity associated with a second anesthesia and reoperation after permanent pathologic examination [20]. Furthermore, FSD is especially difficult in small pulmonary nodules because of severely distorted architecture, ice crystal formation, and complete collapse of the alveolar spaces during cryosection [20]. Gupta et al. [21] reported that after examining a total of 2405 frozen sections, 143 cases were
misdiagnosed or deferred. Another study also showed a small number of false-negative errors and “deferrals,” with sensitivities of 86.9%e94.1% for pulmonary nodules <1.0 and 1.5 cm in diameter, respectively [22]. Permanent histologic examination is widely used and considered as the gold standard. However, the complex sample pretreatment procedures are time consuming and manual demanding. It takes >1 wk to obtain the final diagnosis. As it is a subjective process and requires systemic trainings and years of experience, only senior pathologists are qualified to diagnose. In addition, peripheral lung lesions as small as 5 mm in diameter are sometimes only undergone FSD while leaving no tissues for permanent histologic examination. FTIR spectroscopy identifies different chemical “signatures” as a result of changes in the chemical compositions or structures of biofluids or entities at the molecular level [23]. The components of biological tissues are mainly DNA or RNA, proteins, carbohydrates, lipids, and water. These components are featured by distinct vibrational absorption characteristics in spectral analysis. Therefore, FTIR spectroscopy could serve as a diagnostic tool for detecting and discriminating different diseases or disease progression [24]. FTIR spectroscopy has a wide range of application, including cell lines, serum, freshly dissected tissues, and permanent paraffin slides. Serum IR spectroscopy now has been readily used in analyzing and differentiating clinical diseases, such as examining bovine spongiform encephalopathy serum [25], distinguishing Alzheimer disease [26], assessing myocardial infarction [27], and is also used as a prognostic tool for examining the severity of acute pancreatitis [28]. FTIR spectroscopic technique has a promising classification efficacy on freshly dissected tissues of thyroid nodules and metastatic lymph nodes [13,14]. FTIR spectroscopic imaging could well differentiate benign prostatic epithelium from malignant ones [29,30]. These investigations indicate that FTIR spectroscopy is a promising and powerful tool for future clinical applications.
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Table 3. continued Peak intensity
Relative intensity ratio* y
FWHM y
NMLT
P
MLT
NMLT
P
1.57 (1.71) 1.10 102 (1.42 102) 7.50 103 (6.81 103) 7.1 104 (2.4 104) 0.37 (0.10) 0.10 (0.04) 0.02 (4.58 103) 0.02 (6.59 103) 5.17 103 (2.69 103) 1.31 102 (3.69 103) 4.52 103 (1.75 103) 1.15 103 (9.19 104) 1.20 102 (3.56 103)
0.294 0.751 0.225 0.246 0.019 <0.001 <0.001 0.009 0.065 0.093 0.005 0.007 0.491
102.92 (122.27) 0.60 (0.54) 0.43 (0.27) 5.90 103 (2.80 103) 27.29 (8.78) 4.51 (0.89) d 1.43 (0.31) 0.33 (0.07) 0.98 (0.17) 0.26 (0.14) 0.16 (0.07) 21.98 (2.19)
101.88 (116.91) 0.66 (0.84) 0.46 (0.41) 4.43 103 (1.53 103) 22.75 (5.79) 5.82 (1.20) d 1.29 (0.22) 0.31 (0.13) 0.80 (0.13) 0.27 (0.09) 0.07 (0.04) 0.73 (0.12)
0.139 0.679 0.695 0.015 0.021 <0.001 d 0.052 0.237 <0.001 0.165 <0.001 <0.001
A unique advantage of IR spectroscopy is that it allows simultaneous study of the structure of lipids and proteins in intact biological membranes without the introduction of foreign perturbing probes. ATReFTIR is one of the most powerful methods for recording IR spectra of biological materials in general. It could yield a strong signal with only a few micrograms of sample and provide information about the secondary structure, the orientation, and the tertiary structure changes of a protein in an oriented system [31]. ATReFTIR spectroscopy requires minimal or no sample preparation before spectral measurements. This is because of the fact that the penetration depth of IR light in the sample for ATR measurements is independent of sample thickness. Consequently, this approach is particularly suitable to measure substances with strong IR absorption such as water. Furthermore, investigations have shown that a good contact with the ATR crystal can be obtained by simply placing the tissue directly on the diamond ATR crystal [32,33]. The advantages of ATReFTIR spectroscopy application in lung cancer differentiation include that the advancement of
Table 4 e Lung tissues from 60 casesda comparison of the result between ATReFTIR spectroscopy and histologic examination (gold standard*). ATReFTIR spectroscopy
Nonmalignant lung tissue Malignant lung tissue Total
Histologic diagnosis
Sum
Malignant lung tissue
Nonmalignant lung tissue
1
29
30
29 30
1 30
30 60
* Compared with histologic diagnosis, 96.7% of original grouped cases were correctly classified by ATReFTIR spectroscopy with CDA.
MLT 306.75 14.44 10.01 30.90 61.57 30.20 28.67 30.07 29.55 41.78 19.71 13.11 21.98
(100.85) (13.48) (8.09) (0.00) (2.09) (4.22) (3.66) (2.20) (4.48) (3.57) (5.27) (2.67) (2.19)
NMLT 275.84 12.73 9.59 30.90 59.06 31.42 30.32 27.56 39.06 31.46 22.75 11.01 27.17
(137.38) (11.15) (6.14) (0.00) (2.70) (2.07) (2.35) (1.08) (3.41) (4.54) (2.63) (4.07) (8.58)
Py 0.478 0.796 0.271 1.000 <0.001 0.506 0.043 <0.001 <0.001 <0.001 0.013 0.022 0.003
this technique simplify sample preparation procedures and minimize sample modifications; its noninvasive nature could allow precious samples to be examined many times without damaging the tissue. This is especially useful for peripheral lung lesions 5 mm in diameter; as it is reagent free, it can save the sample for further permanent histologic examination. Furthermore, both spectroscopic scanning and spectra analysis are objective processes, and the inexpensive procedure could also extend the application of this technique to future clinical diagnosis.
5.
Conclusions
To our knowledge, this pilot study for the first time classified malignant and nonmalignant lung tissue with ATReFTIR spectroscopy. The sensitivity and specificity are all 96.7%. The aim of future investigation was, when integrated with flexible optic fiber, this technique could achieve the intraoperative in vivo detection and differentiation, which could help guiding surgeons in fast diagnosis, deciding the extent of dissection, and avoiding unnecessary surgical trauma. There were only 60 samples studied in this pilot experiment, including 30 malignant tissues from different types of lung cancer. More samples as testing team that are blinded to specimen origin are to be collected and examined to validate and improve the established CDA equation in the future study. Comparisons with benign pulmonary nodules and lung tissue from healthy controls would also be included in the following study.
6.
Synopsis
In this pilot study, ATReFTIR spectroscopy technique in combination with CDA method can achieve satisfying discrimination between malignant and nonmalignant lung
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tumors in 60 tissue samples. The sensitivity and specificity are all 96.7%.
Acknowledgment The authors thank the National Science Foundation of China 50973005 for supporting this work. They also thank Dr Xiaoqing Zhang from Peking University Third Hospital for revising the manuscript. The authors declare no conflict of interest.
references
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[15] Ke Y, Li Y, Wang ZY. The changes of Fourier transform infrared spectrum in rat brain. J Forensic Sci; 2012. http:// dx.doi.org/10.1111/j.1556-4029.2011.02036.x. [16] Gharagozloo F, Tempesta B, Margolis M. Video-assisted thoracic surgery lobectomy for stage I lung cancer. Ann Thorac Surg 2003;76:1009. [17] Warner EE, Mulshine JL. Surgical considerations with lung cancer screening. J Surg Oncol 2003;84:1. [18] Nashef SA, Kakadellis JG, Hasleton PS, et al. Histological examination of peroperative frozen sections in suspected lung cancer. Thorax 1993;48:388. [19] Novis DA, Zarbo RJ. Interinstitutional comparison of frozen section turnaround time. A College of American Pathologists Q-Probes study of 32868 frozen sections in 700 hospitals. Arch Pathol Lab Med 1997;121:559. [20] Xu X, Chung JH, Jheon S, et al. The accuracy of frozen section diagnosis of pulmonary nodules: evaluation of inflation method during intraoperative pathology consultation with cryosection. J Thorac Onco 2010;5:39. [21] Gupta R, McKenna R Jr, Marchevsky AM. Lessons learned from mistakes and deferrals in the frozen section diagnosis of bronchioloalveolar carcinoma and welldifferentiated pulmonary adenocarcinoma: an evidencebased pathology approach. Am J Clin Pathol 2008; 130:11. [22] Lechago J. The frozen section: pathology in the trenches. Arch Pathol Lab Med 2005;129:1529. [23] Mantsch HH, Chapman D. Infrared spectroscopy of biomolecules. New York: Wiley-Liss; 1996. [24] Maziak DE, Do MT, Shamji FM, et al. Fourier-transform infrared spectroscopic study of characteristic molecular structure in cancer cells of esophagus: an exploratory study. Cancer Detect Prev 2007;31:244. [25] Menze BH, Petrich W, Hamprecht FA. Multivariate feature selection and hierarchical classification for infrared spectroscopy: serum-based detection of bovine spongiform encephalopathy. Anal Bioanal Chem 2007;387:1801. [26] Griebe M, Daffertshofer M, Stroick M, et al. Infrared spectroscopy: a new diagnostic tool in Alzheimer disease. Neurosci Lett 2007;420:29. [27] Haas SL, Mu¨ller R, Fernandes A, et al. Spectroscopic diagnosis of myocardial infarction and heart failure by Fourier transform infrared spectroscopy in serum samples. Appl Spectrosc 2010;64:262. [28] Petrov MS, Gordetzov AS, Kukosh MV. Early prediction of severity in acute pancreatitis using infrared spectroscopy of serum. Pancreatology 2007;7:451. [29] Fernandez DC, Bhargava R, Hewitt SM. Infrared spectroscopic imaging for histopathologic recognition. Nat Biotechnol 2005;23:469. [30] Bhargava R, Fernandez DC, Hewitt SM. High throughput assessment of cells and tissues: Bayesian classification of spectral metrics from infrared vibrational spectroscopic imaging data. Biochim Biophys Acta 2006;1758:1830. [31] Martin I, Goormaghtigh E, Ruysschaert JM. Attenuated total reflection IR spectroscopy as a tool to investigate the orientation and tertiary structure changes in fusion proteins. Biochim Biophys Acta 2003;1614:97. [32] Chan KL, Kazarian SG. New opportunities in micro- and macro-attenuated total reflection infrared spectroscopic imaging: spatial resolution and sampling versatility. Appl Spectrosc 2003;57:381. [33] Kazarian SG, Chan KL. Applications of ATR-FTIR spectroscopic imaging to biomedical samples. Biochim Biophys Acta 2006;1758:858.
Available online at www.sciencedirect.com
journal homepage: www.JournalofSurgicalResearch.com
Detection of lung cancer tissue by attenuated total reflectioneFourier transform infrared spectroscopyda pilot study of 60 samples Xiaoliang Sun, MD,a Yizhuang Xu, PhD,b Jinguang Wu, PhD,b Yuanfu Zhang, PhD,b and Kelin Sun, MDa,* a
Department of Thoracic Surgery, Cancer Institute and Hospital, Chinese Academy of Medical Science, Peking Union Medical College, Beijing, China b State Key Laboratory of Rare Earth Material Chemistry and Application, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
article info
abstract
Article history:
Background: Attenuated total reflectioneFourier transform infrared (ATReFTIR) spectros-
Received 22 May 2012
copy could serve as a diagnostic tool for detecting and discriminating different diseases.
Received in revised form
The aim of this preliminary study was to distinguish malignant and nonmalignant lung
21 August 2012
tissues with ATReFTIR spectroscopy.
Accepted 30 August 2012
Methods: Sixty lung tissue samples were obtained from 30 patients who underwent
Available online 21 September 2012
pulmonary lobectomy. Samples were examined with ATReFTIR spectroscopy before histologic diagnosis. Peak positions, intensities, and full width at half maximum of each
Keywords:
absorbent band were measured, and the relative intensity ratios were calculated. Canon-
ATReFTIR
ical discriminant analysis was performed to discriminate malignant and nonmalignant
Mid-infrared radiation
groups.
Spectrum
Results: Twenty-two parameters were significantly different between malignant and
Lung tumor
nonmalignant groups. Peak intensity at 1546/cm, intensity ratio at 1120/cm, and full width
Canonical discriminant analysis
at half maximum at 1303 and 1240/cm were selected as independent factors to form
Frozen section diagnosis
discriminant functions. The sensitivity and specificity of the discriminants were all 96.7%.
Histologic examination
Conclusions: ATReFTIR spectroscopy is a promising method for the detection of malignant
Low-dose computerized
lung tissue and could be proved useful in lung tumor surgery.
tomography
ª 2013 Elsevier Inc. All rights reserved.
Sensitivity Specificity
1.
Introduction
Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer death globally. It accounts for 13% (1.6 million) of the total cancer cases and 18% (1.4 million) of
the deaths in 2008. Lung cancer rates are increasing in countries such as China and several other countries in Asia and Africa [1]. Overall, the 5-y survival rate is approximately 15%, whereas the 5-y survival rate for patients with surgically resected early-stage disease is 60%e80% [2]. The present
* Corresponding author. Department of Thoracic Surgery, Cancer Institute and Hospital, Chinese Academy of Medical Science, Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China. Tel.: þ86 108778 7160; fax: þ86 108778 8909. E-mail address: [email protected] (K. Sun). 0022-4804/$ e see front matter ª 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jss.2012.08.057
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paradigm is that most of the untreated lung cancers are rapidly fatal, and consequently, early surgical intervention is mandatory [3]. The introduction of low-dose computerized tomography (LDCT) allows the detection of much smaller nodules (3e5 mm) and small peripheral lung cancer [4]. A large number of review studies have been published on lung cancer LDCT screening in recent years and conclude that its sensitivity ranges between 86.5% and 98.0%, whereas the false-positive rate remains as high as 6%e38% [5]. Preoperative diagnosis of small intrapulmonary nodules with transbronchial or transthoracic biopsies is hard to make as it is difficult to get enough materials or biopsy from deep location [6,7]. A successful limited resection is based on accurate intraoperative frozen section diagnosis (FSD). However, as inflammatory and fibrotic lesions can be confused for malignancy, intraoperative diagnosis becomes a dilemma for the pathologists and thoracic surgeons [8]. The Fourier transform infrared (FTIR) spectroscopy, with the absorption of electromagnetic radiation from 400 to 4000/cm, is sensitive to changes in molecular compositions and structures. It permits rapid collection of spectra obtained from millimeter-sized samples and could detect biochemical signatures of tissues that associated with generation and progression of disease [9,10]. FTIR spectroscopy has been applied to some types of organs and suggested as an objective method [11,12]. The attenuated total reflection (ATR) detection, installed to the FTIR spectroscopy equipment, is independent of sample thickness. Thus, ATReFTIR spectroscopic technique is reagent free and requires minimal or no sample pretreatment before spectral measurements [13e15]. In this pilot study, ATReFTIR spectra of malignant and nonmalignant lung tissues were acquired and compared. Canonical discriminant analysis (CDA) was performed to classify the two groups.
2.
Materials and methods
2.1.
Tissue collection
ATReFTIR spectroscopic analysis, all lung samples were fixed in formalin and then processed for histologic examination at the Pathology department of Chinese Academy of Medical Science.
2.2.
FTIR spectra acquisition
A WQF-600 FTIR spectrometer (Beijing Rayleigh Analytical Instrument Corporation, Beijing, China) was used in this study. After thawing in room temperature, lung tissues were mounted on an ATR plate attached to FTIR spectroscopic equipment. Mid-infrared (IR) radiation (wave number range, 1000e4000/cm) was passed to and from the ATR accessory. Spectra were measured at a resolution of 4/cm, and 32 scans were coadded to achieve a good signal-to-noise ratio. Background spectrum was recorded before every sample scanning and was subtracted automatically to eliminate atmospheric effects. The procedure took approximately 1e2 min for every sample. After scanning, distilled water and alcohol were used to clean the ATR plate. After air-drying of the ATR plate, another sample tissue was mounted on the plate and scanned for spectrum. The technicians there were well trained and blinded to whether the sample is malignant or benign.
2.3.
Statistical analysis
OMNIC software developed by Thermo Electron Corporation (Thermo Nicolet, Boston) was used in harvesting spectra. The peak intensity, peak position, and full width at half maximum (FWHM) of each band were measured using SpaPro version 2.2 software (College of Chemistry and Molecular Engineering, Peking University, Beijing, China). The peak intensity at 1460/cm is the most stable band in the intensity parameters; therefore, the relative intensity ratios were calculated as peak intensity/intensity at 1460/cm. FTIR parameters of malignant and nonmalignant samples of the two groups were compared.
Table 1 e Clinical characteristics of 30 patients with lung tumor. Characteristics
This study was approved by the Cancer Institute and Hospital, Chinese Academy of Medical Science board. Patients were enrolled after being given information about the study and providing written informed consents. For the study, 60 lung tissues were collected from 30 patients with pulmonary lobectomy surgery from January 2009 to February 2010. The average age of the patients was 58.5 y (range, 33e75 y). For every patient, interested samples were removed from the center of the tumor lesion and the distal margin of the dissected lung lobe during operation. Once the tissues were harvested, they were collected immediately by one member of our research team, who is in charge of tissue collection and made the corresponding record of every sample. Samples were immediately prepared to <0.5 cm in diameter and preserved in liquid nitrogen without other pretreatment. All samples were examined at the College of Chemistry and Molecular Engineering, State Key Laboratory of Rare Earth Material Chemistry and Application, Peking University. After
Median age, y (range) Sex ratio (male:female) Tumor location Superior lobe of left lung Inferior lobe of left lung Superior lobe of right lung Middle lobe of right lung Inferior lobe of right lung Pathologic type Squamous cell carcinoma Adenocarcinoma Small cell carcinoma Pathological TNM classification stage IA IB IIA IIB IIIA IIIB
Number of patients 58.5 (33e75) 16:14 10 3 10 2 5 11 18 1 2 11 2 2 11 2
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Normally, distributed data were analyzed with the t-test; otherwise, the ManneWhitney U test was used. P < 0.050 was considered statistically significant. CDA was used to distinguish malignant and nonmalignant lung samples (SPSS release 11.0.0; Chicago, IL). Wilk lambda stepwise discriminant program was applied to help select variables that contribute most to the discriminant function. Two discriminant equations ðLmalignant and Lnonmalignant Þ were established. Retrospective validation and leave-one-out cross-validation were also used to evaluate the discriminant power of the CDA. Sensitivity (true positives/[true positives þ false negative]) and specificity (true negatives/[true negatives þ false positives]) were calculated. Pathologic results as gold standard were compared with the CDA classification later.
3.
Results
Thirty patients’ clinical characteristics are listed in Table 1. The preliminary peak positions assigned as protein, lipids, carbohydrate, or nucleic acid were shown in Table 2. Of the 60 lung tissue samples, 30 were diagnosed as malignant, whereas the remaining 30 were nonmalignant. Characteristic spectra of malignant and nonmalignant tissues from the same patient were shown in Figure. The differences between the two groups (malignant and nonmalignant lung samples) were shown in Table 3. Of the two groups, peak positions of 1640, 1303, 1120, and 1085/cm were significantly different; peak intensities of 1546, 1460, 1400, 1165, and 1120/cm and relative intensity ratios of 1743, 1640, 1546, 1240, and 1120/cm of the two groups were distinctly different from each other. The differences of FWHM at 1640, 1460, 1400, 1303, 1240, 1165, 1120, and 1085/cm
Table 2 e FTIR assignments of lung tissue samples. Peak position (cm1) 3280 2925 2855 1743 1640 1546 1460 1400 1303 1240 1165 1120 1085
Vibrations
Assignments of substance
nOH, nNH nas, CH3 ns, CH2 nC¼O Amide I Amide II dCH dCH, dCOH dCH, dCOH, Amide III nas, Po 2 nCO, dCOH, nCO-c nCO, dCOH, nCO-c nPo2
Water, protein Lipid related Lipid related Lipid Protein Protein Lipid related Lipid related Undetermined Nucleic acid related Carbohydrate related Carbohydrate related Nucleic acid related
n ¼ stretching vibration; ns ¼ symmetry stretching vibration; nas ¼ asymmetry stretching vibration; d ¼ bending vibration.
between the malignant and nonmalignant sample groups were statistically significant. Functions of CDA were established as follows: Lmalignant ¼ 3:241X1 þ 3:687X2 þ 106:193X3 þ 116:557X4 137:103; Lnonmalignant ¼ 3:613X1 þ 3:200X2 þ 79:639X3 þ 151:923X4 131:738; where X1 represents FWHM at 1303/cm; X2 signifies FWHM at 1240/cm; X3 indicates peak intensity ratio at 1120/cm; and X4 presents as peak intensity at 1546/cm. A comparison of the result between ATReFTIR spectroscopy and histologic examination (gold standard) was shown in Table 4. The sensitivity and specificity of the CDA were all 96.7%.
Fig. e ATR-FTIR spectra of nonmaglinant and malignant lung tumors. (A) Nonmalignant lung tissue and (B) malignant lung tissue. (Color version of figure is available online.)
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Table 3 e ATReFTIR alterations of malignant lung tissues compared with nonmalignant lung samples. Band (/cm)
Peak position MLT
3280 2925 2855 1743 1640 1546 1460 1400 1303 1240 1165 1120 1085
3250.76 2920.87 2849.39 1774.20 1640.47 1542.92 1456.39 1399.97 1313.66 1237.33 1166.11 1122.14 1083.41
(85.34) (8.06) (5.33) (0.5 104) (7.06) (1.23) (2.38) (0.71) (3.13) (2.56) (5.22) (1.41) (1.19)
Peak intensity y
NMLT
P
3234.43 (82.62) 2921.51 (3.18) 2849.91 (4.46) 1774.20 (0.5 104) 1648.74 (4.51) 1542.67 (0.71) 1455.87 (1.93) 1399.45 (1.48) 1310.84 (5.79) 1238.10 (0.40 104) 1167.14 (2.63) 1123.41 (4.15) 1083.93 (0.71)
0.359 0.552 0.435 1.000 <0.001 0.321 0.460 0.088 0.041 0.165 0.978 0.025 0.045
MLT 1.07 7.13 103 5.24 103 6.53 105 0.31 0.05 0.01 0.02 3.78 103 1.16 102 3.06 103 1.78 103 1.30 102
(0.97) (6.90 103) (3.74 103) (2.48 105) (0.10) (0.03) (3.93 103) (6.73 103) (1.39 103) (4.78 103) (2.11 103) (8.41 104) (6.44 103)
MLT ¼ malignant lung tissue (n ¼ 30); NMLN ¼ nonmalignant lung tissue (n ¼ 30). Values are mean (standard deviation). P < 0.050 was considered as statistically significant; P value is two tailed. * Relative intensity ratio ¼ peak intensity/intensity at 1460/cm (1460/cm is the most stable band in the intensity parameters). y t-test for data with a normal distribution and ManneWhitney U test for other data.
4.
Discussion
The advancement of LDCT allows the detection of small lung nodules and small peripheral lung cancer. However, this increases the difficulty of transbronchial or transthoracic biopsies because of the sampling technique limitations [6,7]. Therefore, intraopretive FSDs are frequently performed in these patients [16,17], and it is a very important pathologic examination that can determine the extent of the subsequent surgical procedure. However, FSD has its limitations. First, the peripheral lung lesions as small as 5 mm in diameter are very difficult to diagnose with preoperative biopsies. Many of these patients undergo wedge biopsy and intraoperative FSD and might yield histologic slides difficult to interpret. As a result, some investigators even point that both thoracic surgeons and pathologists need to approach the intraoperative diagnosis of small pulmonary nodules with caution, particularly those <1 cm in diameter [8]. Besides, reactive proliferative epithelial changes in inflamed lung tissue and histologic artifacts can closely simulate malignancy. In this scenario, a dilemma is encountered: either a malignant intraoperative diagnosis based on atypical changes that might be enhanced by the technical artifacts or defer the diagnosis to permanent histologic examinations [18,19]. An equivocal diagnosis such as “atypia defer to permanent sections” in a lung nodule with FSD could delay the correct diagnosis and subjects the patient to increased morbidity associated with a second anesthesia and reoperation after permanent pathologic examination [20]. Furthermore, FSD is especially difficult in small pulmonary nodules because of severely distorted architecture, ice crystal formation, and complete collapse of the alveolar spaces during cryosection [20]. Gupta et al. [21] reported that after examining a total of 2405 frozen sections, 143 cases were
misdiagnosed or deferred. Another study also showed a small number of false-negative errors and “deferrals,” with sensitivities of 86.9%e94.1% for pulmonary nodules <1.0 and 1.5 cm in diameter, respectively [22]. Permanent histologic examination is widely used and considered as the gold standard. However, the complex sample pretreatment procedures are time consuming and manual demanding. It takes >1 wk to obtain the final diagnosis. As it is a subjective process and requires systemic trainings and years of experience, only senior pathologists are qualified to diagnose. In addition, peripheral lung lesions as small as 5 mm in diameter are sometimes only undergone FSD while leaving no tissues for permanent histologic examination. FTIR spectroscopy identifies different chemical “signatures” as a result of changes in the chemical compositions or structures of biofluids or entities at the molecular level [23]. The components of biological tissues are mainly DNA or RNA, proteins, carbohydrates, lipids, and water. These components are featured by distinct vibrational absorption characteristics in spectral analysis. Therefore, FTIR spectroscopy could serve as a diagnostic tool for detecting and discriminating different diseases or disease progression [24]. FTIR spectroscopy has a wide range of application, including cell lines, serum, freshly dissected tissues, and permanent paraffin slides. Serum IR spectroscopy now has been readily used in analyzing and differentiating clinical diseases, such as examining bovine spongiform encephalopathy serum [25], distinguishing Alzheimer disease [26], assessing myocardial infarction [27], and is also used as a prognostic tool for examining the severity of acute pancreatitis [28]. FTIR spectroscopic technique has a promising classification efficacy on freshly dissected tissues of thyroid nodules and metastatic lymph nodes [13,14]. FTIR spectroscopic imaging could well differentiate benign prostatic epithelium from malignant ones [29,30]. These investigations indicate that FTIR spectroscopy is a promising and powerful tool for future clinical applications.
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Table 3. continued Peak intensity
Relative intensity ratio* y
FWHM y
NMLT
P
MLT
NMLT
P
1.57 (1.71) 1.10 102 (1.42 102) 7.50 103 (6.81 103) 7.1 104 (2.4 104) 0.37 (0.10) 0.10 (0.04) 0.02 (4.58 103) 0.02 (6.59 103) 5.17 103 (2.69 103) 1.31 102 (3.69 103) 4.52 103 (1.75 103) 1.15 103 (9.19 104) 1.20 102 (3.56 103)
0.294 0.751 0.225 0.246 0.019 <0.001 <0.001 0.009 0.065 0.093 0.005 0.007 0.491
102.92 (122.27) 0.60 (0.54) 0.43 (0.27) 5.90 103 (2.80 103) 27.29 (8.78) 4.51 (0.89) d 1.43 (0.31) 0.33 (0.07) 0.98 (0.17) 0.26 (0.14) 0.16 (0.07) 21.98 (2.19)
101.88 (116.91) 0.66 (0.84) 0.46 (0.41) 4.43 103 (1.53 103) 22.75 (5.79) 5.82 (1.20) d 1.29 (0.22) 0.31 (0.13) 0.80 (0.13) 0.27 (0.09) 0.07 (0.04) 0.73 (0.12)
0.139 0.679 0.695 0.015 0.021 <0.001 d 0.052 0.237 <0.001 0.165 <0.001 <0.001
A unique advantage of IR spectroscopy is that it allows simultaneous study of the structure of lipids and proteins in intact biological membranes without the introduction of foreign perturbing probes. ATReFTIR is one of the most powerful methods for recording IR spectra of biological materials in general. It could yield a strong signal with only a few micrograms of sample and provide information about the secondary structure, the orientation, and the tertiary structure changes of a protein in an oriented system [31]. ATReFTIR spectroscopy requires minimal or no sample preparation before spectral measurements. This is because of the fact that the penetration depth of IR light in the sample for ATR measurements is independent of sample thickness. Consequently, this approach is particularly suitable to measure substances with strong IR absorption such as water. Furthermore, investigations have shown that a good contact with the ATR crystal can be obtained by simply placing the tissue directly on the diamond ATR crystal [32,33]. The advantages of ATReFTIR spectroscopy application in lung cancer differentiation include that the advancement of
Table 4 e Lung tissues from 60 casesda comparison of the result between ATReFTIR spectroscopy and histologic examination (gold standard*). ATReFTIR spectroscopy
Nonmalignant lung tissue Malignant lung tissue Total
Histologic diagnosis
Sum
Malignant lung tissue
Nonmalignant lung tissue
1
29
30
29 30
1 30
30 60
* Compared with histologic diagnosis, 96.7% of original grouped cases were correctly classified by ATReFTIR spectroscopy with CDA.
MLT 306.75 14.44 10.01 30.90 61.57 30.20 28.67 30.07 29.55 41.78 19.71 13.11 21.98
(100.85) (13.48) (8.09) (0.00) (2.09) (4.22) (3.66) (2.20) (4.48) (3.57) (5.27) (2.67) (2.19)
NMLT 275.84 12.73 9.59 30.90 59.06 31.42 30.32 27.56 39.06 31.46 22.75 11.01 27.17
(137.38) (11.15) (6.14) (0.00) (2.70) (2.07) (2.35) (1.08) (3.41) (4.54) (2.63) (4.07) (8.58)
Py 0.478 0.796 0.271 1.000 <0.001 0.506 0.043 <0.001 <0.001 <0.001 0.013 0.022 0.003
this technique simplify sample preparation procedures and minimize sample modifications; its noninvasive nature could allow precious samples to be examined many times without damaging the tissue. This is especially useful for peripheral lung lesions 5 mm in diameter; as it is reagent free, it can save the sample for further permanent histologic examination. Furthermore, both spectroscopic scanning and spectra analysis are objective processes, and the inexpensive procedure could also extend the application of this technique to future clinical diagnosis.
5.
Conclusions
To our knowledge, this pilot study for the first time classified malignant and nonmalignant lung tissue with ATReFTIR spectroscopy. The sensitivity and specificity are all 96.7%. The aim of future investigation was, when integrated with flexible optic fiber, this technique could achieve the intraoperative in vivo detection and differentiation, which could help guiding surgeons in fast diagnosis, deciding the extent of dissection, and avoiding unnecessary surgical trauma. There were only 60 samples studied in this pilot experiment, including 30 malignant tissues from different types of lung cancer. More samples as testing team that are blinded to specimen origin are to be collected and examined to validate and improve the established CDA equation in the future study. Comparisons with benign pulmonary nodules and lung tissue from healthy controls would also be included in the following study.
6.
Synopsis
In this pilot study, ATReFTIR spectroscopy technique in combination with CDA method can achieve satisfying discrimination between malignant and nonmalignant lung
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tumors in 60 tissue samples. The sensitivity and specificity are all 96.7%.
Acknowledgment The authors thank the National Science Foundation of China 50973005 for supporting this work. They also thank Dr Xiaoqing Zhang from Peking University Third Hospital for revising the manuscript. The authors declare no conflict of interest.
references
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