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Dynamic contrast enhanced MRI in the differential diagnosis of soft tissue tumors
European Journal of Radiology 53 (2005) 500–505
Dynamic contrast enhanced MRI in the differential diagnosis of soft tissue tumors Nermin Tuncbilek a,∗ , Hakki Muammer Karakas b , Ozerk Omur Okten a a
b
Department of Radiology, School of Medicine, Trakya University, 22030 Edirne, Turkey Department of Radiology, Faculty of Medicine, Turgut Ozal Medical Center, Inonu University, Malatya, Turkey Received 12 January 2004; received in revised form 9 April 2004; accepted 14 April 2004
Abstract Purpose: The value of the dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in differentiating benign and malignant soft tissue tumors was investigated. Materials and methods: Turbo FLASH DCE-MRI was performed on 22 subjects (2–74 years) with soft tissue tumors. Enhancement in the first min (Emax/1 ), second min (Emax/2 ) and maximum peak enhancement (Emax ), and steepest slope were calculated. Discriminant analyses were performed to reveal parametric differences of benign and malignant lesions. Results: Diagnosis of benign (N = 10) tumors were hemangioma (n = 3), neurogenic tumor (n = 3) lipoma (n = 2), giant cell tumor (n = 1) and desmoid (n = 1), whereas malignant lesions (N = 12) were classified as liposarcoma (n = 5), malignant fibrous histiocytoma (n = 5) and synovial sarcoma (n = 2). For malignant lesions Emax/1 was 65–198%, Emax/2 was 65–145%, Emax was 78–198%, and steepest slope was 1.45–4.06. For benign lesions these values were 4–98%, 5–105%, 7–125% and 0.67–2.57, respectively. To determine the relation between the variables analysed, Pearson correlation coefficients were calculated. Emax was found to be highly correlated with other variables (rxy > 0.86, P < 0.0001). Consequently, this variable was excluded from the discriminant analysis. In order to determine discrimination of malignant and benign tumors using Emax/1 , Emax/2, and steepest slope of the enhancement curve logistic regression was applied to the above mentioned data. When combined these parameters had a 95.5% of overall accuracy in classifying benign and malignant lesions (P = 0.004). Conclusion: DCE-MRI parameters that thought to be the surrogate markers of tumoral microcirculation and tissue perfusion provides a specific preoperative diagnosis. Dynamic imaging parameters are therefore advocated for monitoring the effect of chemotherapy in soft tissue tumors. © 2004 Elsevier Ireland Ltd. All rights reserved. Keywords: Dynamic contrast enhanced MRI; Semiquantitative enhancement parameters; Soft tissue tumors; Differential diagnosis
1. Introduction Magnetic resonance imaging (MRI), a multiplanar imaging method with superior soft tissue contrast, has a well established use in investigation of soft tissue tumors [1]. It is found to be superior to ultrasonography and computerized tomography in the determination of tumor’s morphological attributes such as its size, spread and vascular relations [1–5]. Although the administration of paramagnetic contrast agents further enriches above mentioned information, it does not permit us to make discrimination between benign and malignant lesions when evaluated qualitatively. This is because of shared enhancement characteristics in ∗ Corresponding author. Present address: Kocasinan Mah. Dr. Sad´ yk Ahmet Cad., Olin Sadik Uzunoglu 2 Apt. Daire 4/13, 22030 Edirne, Turkey. Tel.: +90 542 3165342; fax: + 90 284 2356028. E-mail address: [email protected] (N. Tuncbilek).
many tumoral, infectious, edematous and reactive tissues when considered as a static data at a certain arbitrary point in time. Dynamic contrast enhancement MRI (DCE-MRI), on the other hand, provides a dynamic sampling in many time points, an gives important information about tissue perfusion, tissue vasculature, capillary permeability and interstitial space volume [6]. This type of enhancement is largely affected by angiogenic factors which determine the features of primary tumors and formation of metastasis. There are different methods to analyze these dynamic data and among them semiquantitative parameters may be employed in most routine settings without necessitating specialized software. This parameters are proved to be indirect determinants of tumor microcirculation and tissue perfusion [7–9]. In this study, the value of semiquantitative DCE-MRI parameters in differentiating between benign and malignant soft tissue tumors were evaluated.
0720-048X/$ – see front matter © 2004 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ejrad.2004.04.012
N. Tuncbilek et al. / European Journal of Radiology 53 (2005) 500–505
2. Patients and methods The study groups was consisted of 22 patients with soft tissue tumors. This patients range in age from 2 to 74 years (mean: 45.1, SS: 19.2). As part of their presurgical work-up, all patients were investigated with 1.0 T (±20 mT/m) superconductive scanner (Magnetom Impact Expert, Siemens, Erlangen, Germany). Conventional MRI series (axial, sagittal, coronal spin-echo T1, T2 and fat-suppressed T2-weighted) were
501
used to locate tumoral lesions and to show their morphologic characteristics. After these preliminary series, a precontrast axial turbo fast low-angle shot (FLASH) sequence (TR/TE/NEX/FA:11/4.2/2/25◦ , band thickness: 163 kHz, slice thickness: 8 mm, matrix: 128 × 256) was applied to cover tumoral tissues (Figs. 1A and 2A). After the precontrast turbo FLASH sequence, patients were received 0.1 mmol/kg gadoteric acid (Dotarem, Guerbet, Paris, Aulnay-sous-Bois, France) intravenously through a peripheral line at 5 mL/s. In the postcontrast sequence, eight
Fig. 1. A 56-year-old man with histologically proved liposarcoma. Precontrast turbo FLASH sequences revealed as heterogeneous signal of soft tissue masses in medial and ventral region of gluteus maximus muscularis (A). Subtraction image shows, an intense and heterogeneous enhancement. The region of interest was placed in the peripher of tumor (B). Time intensity curve demonstrates a post Gd-DTPA enhancement of more than 198% in the 105 s followed by a plateau in the next minutes. The steepest slope of the enhancement curve was 4.86 (C).
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N. Tuncbilek et al. / European Journal of Radiology 53 (2005) 500–505
Fig. 2. A 68-year-old man with histologically proved lipoma. Precontrast turbo FLASH sequences revealed lobule contoured soft tissue mass localizated at left lateral side of abdomen wall (A). Postcontrast turbo FLASH sequences shows, low homogeneous enhancement (B). Time intensity curve demonstrates a signal enhancement increase throughout the examination and enhancement of more than 41% in the 5 min. The steepest slope of the enhancement curve was 0.77 (C).
turbo FLASH series, each lasting 30 s, were performed sequentially in 4 min with identical parameters as those used for precontrast sequence (Figs. 1B and 2B). With a temporal resolution of that order up to 110 slices could be acquired for each sampling point. The onset for contrast injection and the data acquisition were triggered synchronously. Precontrast images were substracted from the relevant postcontrast images to demonstrate differential tumoral enhancement.
2.1. Image analysis 2.1.1. Time intensity curves (TICs) TICs were constructed from SI values obtained from freely drawn region of interests (ROIs). For each tumor, one ROI for the most enhancing region was used. The ROIs covered areas of change between 0.2 and 0.4 cm2 (Figs. 1C and 2C). For each 30 s acquisition, the relevant SI data were treated automatically as acquired at the time the center of
N. Tuncbilek et al. / European Journal of Radiology 53 (2005) 500–505
k-space was acquired. Therefore, SIs for 15–225 s with 30 s intervals were obtained. 2.1.2. Enhancement parameters The parameters were obtained using SI values of above-defined ROIs. Maximal relative enhancement within first minute (Emax/1 ) was expressed as the percentage of the nonenhanced SI using the formula: Emax/1 = [(SImax/1 − SIpre/1 ) × 100]/ SIpre/1 . In this formula, SImax/1 represents the highest postcontrast SI reached within first minute, and SIpre/1 represents the relevant precontrast SI. Maximal relative enhancement within second minute (Emax/2 ) and maximal relative enhancement of the entire study (Emax ) was calculated using similar formulas. The steepest slope of the enhancement curve was used as a measure of the tissue perfusion rate and expressed by the following equation as defined by Buadu et al. [7], steepest slope (s, %)= [(SIend − SIprev )100]/[SIpre (Tend − Tprev )], where prev indicates previous, and pre indicates precontrast. SIend and SIprev are the values on the contrast medium uptake curve that differed the most from image to image in the dynamic series. Tend and Tprev represent the time points that corresponding to SIend and SIprev . Time to peak enhancement was defined as the postinjection time necessary to reach to maximum SI. 2.2. Statistical analysis DCE-MRI parameters were determined using descriptive analysis and the variations were defined. The differences revealed in the parameters between benign and malignant lesion groups were analyzed with nonparametric tests. The relation between variables was shown using calculated correlation coefficients. Accurate classifying ability of dynamic parameters was researched with discriminant analysis.
503
250
200
150 Benign Malign
SI 100
50
0 15
45
75
105 135 165 195 225 255
Time (sec)
Scheme 1. Time intensity curves for the malignant and benign groups.
When the Levene test was applied, unequal group variations were found. Thus, for the significance test, non parametric Mann–Whitney U-test was applied, which does not assume equality of variations. With this test, significantly different Emax/1 (P < 0.0001), Emax/2 (P = 0.002), Emax (P = 0.002) and steepest slope of the enhancement curve (P < 0.001) values between the malignant and benign groups were observed (Scheme 2). To determine the relation between the variables analysed, Pearson correlation coefficients were calculated. Emax was found to be highly correlated with other variables (rxy > 0.86, P < 0.0001). Consequently, this variable was excluded from the discriminanant analysis. In order to determine discrimination of malignant and benign tumors using Emax/1 , Emax/2 , and steepest slope of the enhancement curve logistic regression was applied to the above mentioned data.
3. Results Malignant tumors (N = 12) were diagnosed as liposarcoma (n = 5), malignant fibrous histiocytoma (n =5) and synovial sarcoma (n =2). Benign tumors (N = 10) were diagnosed as hemangioma (n =3), neurogenic tumor (n =3), lipoma (n =2), giant cell tumor (n =1) and desmoid tumor (n =1). The ages of the cases were between 2 and 74 (mean: 51.6, SS: 19.8) years in the malignant lesions and 7–60 (mean: 37.2, SS: 15.9) years in the benign lesions. For malignant tumors Emax/1 was 65–198% (mean: 108.3, SS: 44.6), Emax/2 was 65–145% (mean: 109.2, SS: 20.0), Emax was 78–198% (mean: 131.6, SS: 33.5), and steepest slope of the enhancement curve was 1.45–4.06 (mean: 2.93, SS: 0.77). For benign tumors Emax/1 was 4–98% (mean: 48.5, SS: 28.8), Emax/ 2 was 5–105% (mean: 69.9, SS: 35.3), Emax was 7–125% (mean: 79.6, SS: 39.4), and steepest slope of the enhancement curve was 0.67–2.57 (mean: 1.55, SS: 0.69) (Scheme 1).
Scheme 2. Boxplot shows mean Emax/1 of malignant and benign tumors.
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Table 1 Discriminant analysis of malignant and benign groups regarding DCE-MRI parameters (Emax/1 , Emax/2 , and steepest slope of the enhancement curve) Groups
Original group membership (%)
Predicted group membership (%)
Malignant Benign
Malignant
Benign
12 (100%)
0 (0%)
1 (10%)
9 (90%)
When combined these parameters had a 95.5% of overall accuracy in classifying benign and malignant lesions (P = 0.004) (Table 1). The above mentioned regression model has a higher accuracy for malignant lesions (100%) than for benign lesions (90%). When used alone Emax/1 has the best discriminatory power. Using this parameter 83% of the malignant and 80% of the benign lesions were correctly classified (P = 0.001). A ROC curve analysis was identified an Emax/1 value of 71 as a cut-off. This value had a sensitivity of 83% and a specificity of 80% in determining malignant lesions.
4. Discussion There are some differences between benign and malignant soft tissue lesions regarding qualitative enhancement patterns. Contrast enhancement is generally higher in malignant lesions. However, some benign tumors, such as hemangioma, myositis ossificans and aggressive fibromatosis, may show high contrast enhancement, whereas sarcomas with necrotic components are known to have low contrast enhancement [3,10–12]. These overlaps necessitate the use of dynamic methods and quantitative analysis techniques. The use of DCE-MRI in soft tissue tumors has been emphasized in a very few studies [10,13–18]. In this physiological imaging technique, pre-contrast scanning, the rate and the timing of injection and image analysis are of great importance. Moreover the temporal resolution should be increased to the highest possible level and early phase images should be obtained. Techniques which are most widely used have a resolution between 20 and 30 s, although with some novel techniques such as rarallel acquisition this resolution may be slightly improved [19]. Several techniques were descibed to analyse enhancement data and among them the most widely used one is the analysis of time enhancement curves with semiquantitative methods which are obtained from substraction images. Malignant tumors have high vascularity and narrow interstitial space. The majority of these tumors show rapid and high contrast enhancement. On the other hand, benign tumors, owing to their slow perfusion and their wider interstitial space, almost always show late contrast enhancement [7–10]. Recently, Van der Woude et al. [18] prospectively analyzed the value of fast dynamic subtraction MRI in soft
tissue tumors. They assessed the interval between arterial and early tumor enhancement (91% sensivity and 72% specificity), peripheral versus diffuse enhancement pattern (73% sensivity and 97% specificity), and the time intensity curves of enhancement (86% sensitivity and 81% specificity) in differentiation of benign from malignant soft tissue tumors. Most malignant soft tissue tumors exhibited an early and peripheral enhancement with a steep slope, an early maximum followed by a transition to a stable level or a slight decrease of signal intensity [18]. In another study, more than 30% increase in SI per minute were seen in 84% of malignant tumors, and less than 30% increase in SI per minute were seen in 72% of benign tumors. Largely necrotic malignant tumors showed less than 30% increase in SI per minute, whereas aggressive benign lesions, such as myositis ossificans, showed slopes similar to those of malignant tumors [13,14]. These results are in accordance with the results of Verstrate et al. [10]. Conversely, Mirowitz et al. [15], found no significant difference between dynamic gadolinium enhancement of benign and malignant masses. Tacikowska used the maximal contrast enhancement ratio in discrimination of benign and malignant soft tissue tumors [16,17]. With this parameter they observed a 83.3% sensitivity and a 73.3% specificity. The findings of the present study stating a relatively high mean peak contrast enhancement (137%) in malignant, and a low mean peak contrast enhancement (77%) in benign tumors were compatible with most of the past studies. However, the mean peak contrast enhancement for benign lesions was considerably higher than the value Erleman et al. found 72–83% [13,14]. The reason for this difference was the inclusion of cases with dense vascularity, as hemangiomas (Emax of 82%) and desmoid tumors (Emax of 120%). Emax should therefore not be used in differential diagnosis. Determination of qualitative or quantitative contrast enhancement in an unknown period is also not to be used and it is therefore unnecessary to investigate these lesions with more series in long time duration. This conclusion was statistically supported by the exclusion of that parameter by the logistic regression models. The rest of the semiquantitative parameters must be used in combination to reach a high discriminatory power. In a clinical setting Emax/1 may used alone with an acceptable sensitivity (83%) and specificity (80%) to diagnose malignant lesions. Therefore optimal evaluation of soft tissue tumors may be performed using a simple time saving protocol. In this protocol fast precontrast sequence to determine the morphology and precontrast signal intensity should be followed by an additional sequence obtained 1 min after the administration of contrast media to determine Emax/1 . If a third sequence for second minute enhancement is obtained, a very accurate classification of malignant tumors become possible. This protocol may prevent false radiological diagnosis which may lead to a delay in therapeutic resection. In addition to initial diagnosis, DCE-MRI may also assists in the detection of the most viable parts of the tumour and
N. Tuncbilek et al. / European Journal of Radiology 53 (2005) 500–505
serves as an initial standard for follow-up of the metabolic activity of the tumour during and after chemotherapy [20]. Monitoring of this activity may have an impact on modification of neoadjuvant treatment protocols, on patient selection for the performance and timing of surgery and on planning of radiation therapy. Dynamic imaging parameters are therefore advocated for monitoring the effect of chemotherapy in soft tissue tumors.
[11]
[12]
[13]
References [1] De Schepper A, Parizel P, Ramon F, De Beuckeleer L, Vandevenne J. Imaging of soft tissue tumors. New York: Springer, Berlin; 1997. [2] Aisen AM, Martel W, Braunstein EM, McMillin KI, Phillips WA, Kling TF. MRI and CT evaluation of primary bone and soft tissue tumors. AJR 1986;146:749–56. [3] Hough TJ, Tung GA, Terek RM. Staging, characterization, and grading. In: Schepper De, Parizel PA, Ramon F, et al., editors. Imaging of soft tissue tumors. Berlin, Heidelberg: Springer; 1997. p. 113–25. [4] Kransdorf MJ, Murphey MD. Imaging of soft tissue tumors. Philadelphia: WB Saunders; 1997. [5] Petasnick JP, Turner DA, Charters JR, Gitelis S, Zacharias CE. Soft-tissue masses of the locomotor system:comparison of MR imaging with CT. Radiology 1986;160:125–33. [6] Verstraete KL, Lang P. Bone and soft tissue tumors: the role of contrast agents for MR imaging. Eur J Radiol 2000;34:229–46. [7] Buadu LD, Murakami J, Murayama S, Hashiguchi N, Sakai S, Masuda K, et al. Breast lesions:correlation of contrast medium enhancement patterns on MR images with histopathologic findings and tumor angiogenesis. Radiology 1996;2000:639–49. [8] Tuncbilek N, Unlu E, Karakas HM, Cakir B, Ozyilmaz F. Evaluation of tumor angiogenesis with contrast-enhanced MR mammography. Breast J 2003;9:403–8. [9] Tuncbilek N, Karakas HM, Altaner S. Dynamic MRI in indirect estimation of MVD in colorectal adenocarcinomas. Abdominal Imaging. [10] Verstraete KL, De Deene Y, Roels H, Dierick A, Uyttendaele D, Kunnen M. Benign and malignant musculoskeleteal lesions: dynamic
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contrast-enhanced MR imaging-parametric “first pass” images depict tissue vascularization and perfusion. Radiology 1994;192:835– 43. Moulton JS, Blebea JS, Dunco DM, Braley SE, Bisset III GS, Emery KH. MR imaging of soft-tissue masses: diagnostic efficacy and value of distinguishing between benign and malignant lesions. AJR 1995;164:1191–9. Ma LD, Frassica FJ, McCarthy EF, Bluemke DA, Zerhouni EA. Benign and malignant musculoskeletal masses: MR imaging differentiation with rim-to-center differential enhancement ratios. Radiology 1997;202:739–44. Erlemann R, Sciuk J, Wuisman P, Bene D, Edel G, Ritter J, et al. Dynamic MR tomography in the diagnosis of inflammatory and tumorous space-occupying lesions of the musculoskeletal system. Rofo Fortschr Geb Rontgenstr 1992;156:353–9. Erlemann R, Reiser M, Peters PE, Vasallo P, Nommensen B, Kusnierz-Glaz CR, et al. Musculoskeleteal neoplasms:static and dynamic Gd-DTPA enhanced MR imaging. Radiology 1989;171:767– 73. Mirowitz S, Totty W, Lee J. Characterization of musculoskeletal masses using dynamic Gd-DTPA enhanced spin-echo MRI. J Comput Assist Tomogr 1992;16:120–5. Tacikowska M. Dynamic magnetic resonance imaging in soft tissue tumors-assessment of the diagnostic value of tumor enhancement rate indices. Med Sci Monit 2002;8:53–7. Tacikowska M. Dynamic MR imaging of soft tissue tumors with assesment of the rate and character of lesion enhancement. Med Sci Monit 2002;8:31–5. Van der Woude HJ, Verstraete KL, Hogendoorn PC, Taminiau AH, Hermans J, Bloem JL. Musculoskeleteal tumors: does fast dynamic contrast-enhanced subtraction MR imaging contribute to the characterization? Radiology 1998;208:821–8. Dobritz M, Radkow T, Nittka M, Bautz W, Fellner FA. VIBE with parallel acquisition technique—a novel approach to dynamic contrast-enhanced MR imaging of the liver. Rofo Fortschr Geb Rontgenstr Neuen Bildgeb Verfahr 2002;174:738–41. Van der Woude HJ, Bloem JL, Hogendoorn PC. Preoperative evaluation and monitoring chemotherapy in patients with high-grade osteogenic and Ewing’s sarcoma: review of current imaging modalities. Skeletal Radiol 1998;27:57–71.
Dynamic contrast enhanced MRI in the differential diagnosis of soft tissue tumors Nermin Tuncbilek a,∗ , Hakki Muammer Karakas b , Ozerk Omur Okten a a
b
Department of Radiology, School of Medicine, Trakya University, 22030 Edirne, Turkey Department of Radiology, Faculty of Medicine, Turgut Ozal Medical Center, Inonu University, Malatya, Turkey Received 12 January 2004; received in revised form 9 April 2004; accepted 14 April 2004
Abstract Purpose: The value of the dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in differentiating benign and malignant soft tissue tumors was investigated. Materials and methods: Turbo FLASH DCE-MRI was performed on 22 subjects (2–74 years) with soft tissue tumors. Enhancement in the first min (Emax/1 ), second min (Emax/2 ) and maximum peak enhancement (Emax ), and steepest slope were calculated. Discriminant analyses were performed to reveal parametric differences of benign and malignant lesions. Results: Diagnosis of benign (N = 10) tumors were hemangioma (n = 3), neurogenic tumor (n = 3) lipoma (n = 2), giant cell tumor (n = 1) and desmoid (n = 1), whereas malignant lesions (N = 12) were classified as liposarcoma (n = 5), malignant fibrous histiocytoma (n = 5) and synovial sarcoma (n = 2). For malignant lesions Emax/1 was 65–198%, Emax/2 was 65–145%, Emax was 78–198%, and steepest slope was 1.45–4.06. For benign lesions these values were 4–98%, 5–105%, 7–125% and 0.67–2.57, respectively. To determine the relation between the variables analysed, Pearson correlation coefficients were calculated. Emax was found to be highly correlated with other variables (rxy > 0.86, P < 0.0001). Consequently, this variable was excluded from the discriminant analysis. In order to determine discrimination of malignant and benign tumors using Emax/1 , Emax/2, and steepest slope of the enhancement curve logistic regression was applied to the above mentioned data. When combined these parameters had a 95.5% of overall accuracy in classifying benign and malignant lesions (P = 0.004). Conclusion: DCE-MRI parameters that thought to be the surrogate markers of tumoral microcirculation and tissue perfusion provides a specific preoperative diagnosis. Dynamic imaging parameters are therefore advocated for monitoring the effect of chemotherapy in soft tissue tumors. © 2004 Elsevier Ireland Ltd. All rights reserved. Keywords: Dynamic contrast enhanced MRI; Semiquantitative enhancement parameters; Soft tissue tumors; Differential diagnosis
1. Introduction Magnetic resonance imaging (MRI), a multiplanar imaging method with superior soft tissue contrast, has a well established use in investigation of soft tissue tumors [1]. It is found to be superior to ultrasonography and computerized tomography in the determination of tumor’s morphological attributes such as its size, spread and vascular relations [1–5]. Although the administration of paramagnetic contrast agents further enriches above mentioned information, it does not permit us to make discrimination between benign and malignant lesions when evaluated qualitatively. This is because of shared enhancement characteristics in ∗ Corresponding author. Present address: Kocasinan Mah. Dr. Sad´ yk Ahmet Cad., Olin Sadik Uzunoglu 2 Apt. Daire 4/13, 22030 Edirne, Turkey. Tel.: +90 542 3165342; fax: + 90 284 2356028. E-mail address: [email protected] (N. Tuncbilek).
many tumoral, infectious, edematous and reactive tissues when considered as a static data at a certain arbitrary point in time. Dynamic contrast enhancement MRI (DCE-MRI), on the other hand, provides a dynamic sampling in many time points, an gives important information about tissue perfusion, tissue vasculature, capillary permeability and interstitial space volume [6]. This type of enhancement is largely affected by angiogenic factors which determine the features of primary tumors and formation of metastasis. There are different methods to analyze these dynamic data and among them semiquantitative parameters may be employed in most routine settings without necessitating specialized software. This parameters are proved to be indirect determinants of tumor microcirculation and tissue perfusion [7–9]. In this study, the value of semiquantitative DCE-MRI parameters in differentiating between benign and malignant soft tissue tumors were evaluated.
0720-048X/$ – see front matter © 2004 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ejrad.2004.04.012
N. Tuncbilek et al. / European Journal of Radiology 53 (2005) 500–505
2. Patients and methods The study groups was consisted of 22 patients with soft tissue tumors. This patients range in age from 2 to 74 years (mean: 45.1, SS: 19.2). As part of their presurgical work-up, all patients were investigated with 1.0 T (±20 mT/m) superconductive scanner (Magnetom Impact Expert, Siemens, Erlangen, Germany). Conventional MRI series (axial, sagittal, coronal spin-echo T1, T2 and fat-suppressed T2-weighted) were
501
used to locate tumoral lesions and to show their morphologic characteristics. After these preliminary series, a precontrast axial turbo fast low-angle shot (FLASH) sequence (TR/TE/NEX/FA:11/4.2/2/25◦ , band thickness: 163 kHz, slice thickness: 8 mm, matrix: 128 × 256) was applied to cover tumoral tissues (Figs. 1A and 2A). After the precontrast turbo FLASH sequence, patients were received 0.1 mmol/kg gadoteric acid (Dotarem, Guerbet, Paris, Aulnay-sous-Bois, France) intravenously through a peripheral line at 5 mL/s. In the postcontrast sequence, eight
Fig. 1. A 56-year-old man with histologically proved liposarcoma. Precontrast turbo FLASH sequences revealed as heterogeneous signal of soft tissue masses in medial and ventral region of gluteus maximus muscularis (A). Subtraction image shows, an intense and heterogeneous enhancement. The region of interest was placed in the peripher of tumor (B). Time intensity curve demonstrates a post Gd-DTPA enhancement of more than 198% in the 105 s followed by a plateau in the next minutes. The steepest slope of the enhancement curve was 4.86 (C).
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N. Tuncbilek et al. / European Journal of Radiology 53 (2005) 500–505
Fig. 2. A 68-year-old man with histologically proved lipoma. Precontrast turbo FLASH sequences revealed lobule contoured soft tissue mass localizated at left lateral side of abdomen wall (A). Postcontrast turbo FLASH sequences shows, low homogeneous enhancement (B). Time intensity curve demonstrates a signal enhancement increase throughout the examination and enhancement of more than 41% in the 5 min. The steepest slope of the enhancement curve was 0.77 (C).
turbo FLASH series, each lasting 30 s, were performed sequentially in 4 min with identical parameters as those used for precontrast sequence (Figs. 1B and 2B). With a temporal resolution of that order up to 110 slices could be acquired for each sampling point. The onset for contrast injection and the data acquisition were triggered synchronously. Precontrast images were substracted from the relevant postcontrast images to demonstrate differential tumoral enhancement.
2.1. Image analysis 2.1.1. Time intensity curves (TICs) TICs were constructed from SI values obtained from freely drawn region of interests (ROIs). For each tumor, one ROI for the most enhancing region was used. The ROIs covered areas of change between 0.2 and 0.4 cm2 (Figs. 1C and 2C). For each 30 s acquisition, the relevant SI data were treated automatically as acquired at the time the center of
N. Tuncbilek et al. / European Journal of Radiology 53 (2005) 500–505
k-space was acquired. Therefore, SIs for 15–225 s with 30 s intervals were obtained. 2.1.2. Enhancement parameters The parameters were obtained using SI values of above-defined ROIs. Maximal relative enhancement within first minute (Emax/1 ) was expressed as the percentage of the nonenhanced SI using the formula: Emax/1 = [(SImax/1 − SIpre/1 ) × 100]/ SIpre/1 . In this formula, SImax/1 represents the highest postcontrast SI reached within first minute, and SIpre/1 represents the relevant precontrast SI. Maximal relative enhancement within second minute (Emax/2 ) and maximal relative enhancement of the entire study (Emax ) was calculated using similar formulas. The steepest slope of the enhancement curve was used as a measure of the tissue perfusion rate and expressed by the following equation as defined by Buadu et al. [7], steepest slope (s, %)= [(SIend − SIprev )100]/[SIpre (Tend − Tprev )], where prev indicates previous, and pre indicates precontrast. SIend and SIprev are the values on the contrast medium uptake curve that differed the most from image to image in the dynamic series. Tend and Tprev represent the time points that corresponding to SIend and SIprev . Time to peak enhancement was defined as the postinjection time necessary to reach to maximum SI. 2.2. Statistical analysis DCE-MRI parameters were determined using descriptive analysis and the variations were defined. The differences revealed in the parameters between benign and malignant lesion groups were analyzed with nonparametric tests. The relation between variables was shown using calculated correlation coefficients. Accurate classifying ability of dynamic parameters was researched with discriminant analysis.
503
250
200
150 Benign Malign
SI 100
50
0 15
45
75
105 135 165 195 225 255
Time (sec)
Scheme 1. Time intensity curves for the malignant and benign groups.
When the Levene test was applied, unequal group variations were found. Thus, for the significance test, non parametric Mann–Whitney U-test was applied, which does not assume equality of variations. With this test, significantly different Emax/1 (P < 0.0001), Emax/2 (P = 0.002), Emax (P = 0.002) and steepest slope of the enhancement curve (P < 0.001) values between the malignant and benign groups were observed (Scheme 2). To determine the relation between the variables analysed, Pearson correlation coefficients were calculated. Emax was found to be highly correlated with other variables (rxy > 0.86, P < 0.0001). Consequently, this variable was excluded from the discriminanant analysis. In order to determine discrimination of malignant and benign tumors using Emax/1 , Emax/2 , and steepest slope of the enhancement curve logistic regression was applied to the above mentioned data.
3. Results Malignant tumors (N = 12) were diagnosed as liposarcoma (n = 5), malignant fibrous histiocytoma (n =5) and synovial sarcoma (n =2). Benign tumors (N = 10) were diagnosed as hemangioma (n =3), neurogenic tumor (n =3), lipoma (n =2), giant cell tumor (n =1) and desmoid tumor (n =1). The ages of the cases were between 2 and 74 (mean: 51.6, SS: 19.8) years in the malignant lesions and 7–60 (mean: 37.2, SS: 15.9) years in the benign lesions. For malignant tumors Emax/1 was 65–198% (mean: 108.3, SS: 44.6), Emax/2 was 65–145% (mean: 109.2, SS: 20.0), Emax was 78–198% (mean: 131.6, SS: 33.5), and steepest slope of the enhancement curve was 1.45–4.06 (mean: 2.93, SS: 0.77). For benign tumors Emax/1 was 4–98% (mean: 48.5, SS: 28.8), Emax/ 2 was 5–105% (mean: 69.9, SS: 35.3), Emax was 7–125% (mean: 79.6, SS: 39.4), and steepest slope of the enhancement curve was 0.67–2.57 (mean: 1.55, SS: 0.69) (Scheme 1).
Scheme 2. Boxplot shows mean Emax/1 of malignant and benign tumors.
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Table 1 Discriminant analysis of malignant and benign groups regarding DCE-MRI parameters (Emax/1 , Emax/2 , and steepest slope of the enhancement curve) Groups
Original group membership (%)
Predicted group membership (%)
Malignant Benign
Malignant
Benign
12 (100%)
0 (0%)
1 (10%)
9 (90%)
When combined these parameters had a 95.5% of overall accuracy in classifying benign and malignant lesions (P = 0.004) (Table 1). The above mentioned regression model has a higher accuracy for malignant lesions (100%) than for benign lesions (90%). When used alone Emax/1 has the best discriminatory power. Using this parameter 83% of the malignant and 80% of the benign lesions were correctly classified (P = 0.001). A ROC curve analysis was identified an Emax/1 value of 71 as a cut-off. This value had a sensitivity of 83% and a specificity of 80% in determining malignant lesions.
4. Discussion There are some differences between benign and malignant soft tissue lesions regarding qualitative enhancement patterns. Contrast enhancement is generally higher in malignant lesions. However, some benign tumors, such as hemangioma, myositis ossificans and aggressive fibromatosis, may show high contrast enhancement, whereas sarcomas with necrotic components are known to have low contrast enhancement [3,10–12]. These overlaps necessitate the use of dynamic methods and quantitative analysis techniques. The use of DCE-MRI in soft tissue tumors has been emphasized in a very few studies [10,13–18]. In this physiological imaging technique, pre-contrast scanning, the rate and the timing of injection and image analysis are of great importance. Moreover the temporal resolution should be increased to the highest possible level and early phase images should be obtained. Techniques which are most widely used have a resolution between 20 and 30 s, although with some novel techniques such as rarallel acquisition this resolution may be slightly improved [19]. Several techniques were descibed to analyse enhancement data and among them the most widely used one is the analysis of time enhancement curves with semiquantitative methods which are obtained from substraction images. Malignant tumors have high vascularity and narrow interstitial space. The majority of these tumors show rapid and high contrast enhancement. On the other hand, benign tumors, owing to their slow perfusion and their wider interstitial space, almost always show late contrast enhancement [7–10]. Recently, Van der Woude et al. [18] prospectively analyzed the value of fast dynamic subtraction MRI in soft
tissue tumors. They assessed the interval between arterial and early tumor enhancement (91% sensivity and 72% specificity), peripheral versus diffuse enhancement pattern (73% sensivity and 97% specificity), and the time intensity curves of enhancement (86% sensitivity and 81% specificity) in differentiation of benign from malignant soft tissue tumors. Most malignant soft tissue tumors exhibited an early and peripheral enhancement with a steep slope, an early maximum followed by a transition to a stable level or a slight decrease of signal intensity [18]. In another study, more than 30% increase in SI per minute were seen in 84% of malignant tumors, and less than 30% increase in SI per minute were seen in 72% of benign tumors. Largely necrotic malignant tumors showed less than 30% increase in SI per minute, whereas aggressive benign lesions, such as myositis ossificans, showed slopes similar to those of malignant tumors [13,14]. These results are in accordance with the results of Verstrate et al. [10]. Conversely, Mirowitz et al. [15], found no significant difference between dynamic gadolinium enhancement of benign and malignant masses. Tacikowska used the maximal contrast enhancement ratio in discrimination of benign and malignant soft tissue tumors [16,17]. With this parameter they observed a 83.3% sensitivity and a 73.3% specificity. The findings of the present study stating a relatively high mean peak contrast enhancement (137%) in malignant, and a low mean peak contrast enhancement (77%) in benign tumors were compatible with most of the past studies. However, the mean peak contrast enhancement for benign lesions was considerably higher than the value Erleman et al. found 72–83% [13,14]. The reason for this difference was the inclusion of cases with dense vascularity, as hemangiomas (Emax of 82%) and desmoid tumors (Emax of 120%). Emax should therefore not be used in differential diagnosis. Determination of qualitative or quantitative contrast enhancement in an unknown period is also not to be used and it is therefore unnecessary to investigate these lesions with more series in long time duration. This conclusion was statistically supported by the exclusion of that parameter by the logistic regression models. The rest of the semiquantitative parameters must be used in combination to reach a high discriminatory power. In a clinical setting Emax/1 may used alone with an acceptable sensitivity (83%) and specificity (80%) to diagnose malignant lesions. Therefore optimal evaluation of soft tissue tumors may be performed using a simple time saving protocol. In this protocol fast precontrast sequence to determine the morphology and precontrast signal intensity should be followed by an additional sequence obtained 1 min after the administration of contrast media to determine Emax/1 . If a third sequence for second minute enhancement is obtained, a very accurate classification of malignant tumors become possible. This protocol may prevent false radiological diagnosis which may lead to a delay in therapeutic resection. In addition to initial diagnosis, DCE-MRI may also assists in the detection of the most viable parts of the tumour and
N. Tuncbilek et al. / European Journal of Radiology 53 (2005) 500–505
serves as an initial standard for follow-up of the metabolic activity of the tumour during and after chemotherapy [20]. Monitoring of this activity may have an impact on modification of neoadjuvant treatment protocols, on patient selection for the performance and timing of surgery and on planning of radiation therapy. Dynamic imaging parameters are therefore advocated for monitoring the effect of chemotherapy in soft tissue tumors.
[11]
[12]
[13]
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