Scientific Exhibit Authors: A. Shimauchi, H. Abe, N. Mori, H. Ota, K. Takase, S.

Transcription

1 MRI- Detected Breast Masses: Are CAD-Measured Kinetic Diversity Analyses Useful for Differential Diagnosis? A New Approach with Whole Lesion Curve Distribution Analysis. Poster No.: C-1901 Congress: ECR 2014 Type: Scientific Exhibit Authors: A. Shimauchi, H. Abe, N. Mori, H. Ota, K. Takase, S Takahashi, G. M. Newstead ; Sendai/JP, Chicago, IL/US, 3 4 Sendai,Miyagi/JP, Winter Harbor, ME/US Keywords: Cancer, CAD, MR, Breast DOI: /ecr2014/C-1901 Any information contained in this pdf file is automatically generated from digital material submitted to EPOS by third parties in the form of scientific presentations. References to any names, marks, products, or services of third parties or hypertext links to thirdparty sites or information are provided solely as a convenience to you and do not in any way constitute or imply ECR's endorsement, sponsorship or recommendation of the third party, information, product or service. ECR is not responsible for the content of these pages and does not make any representations regarding the content or accuracy of material in this file. As per copyright regulations, any unauthorised use of the material or parts thereof as well as commercial reproduction or multiple distribution by any traditional or electronically based reproduction/publication method ist strictly prohibited. You agree to defend, indemnify, and hold ECR harmless from and against any and all claims, damages, costs, and expenses, including attorneys' fees, arising from or related to your use of these pages. Please note: Links to movies, ppt slideshows and any other multimedia files are not available in the pdf version of presentations. Page 1 of 24

2 Aims and objectives Introduction Although several morphologic features have been reported to be specific features of malignancy [1,2], these features are more often found in larger tumors that are already known from mammography and/or sonography, thus histologically proven when patients undergo breast MRI. Breast lesions initially found at MRI, which are clinically more problematic, tend to be smaller compared to index tumors and often exhibit predominantly a homogeneous internal enhancement and indeterminate margins by visual assessment. Hence, it would be more clinically relevant to determine if there are specific MRI features in breast lesions that are initially found at MRI, rather than including known tumors that had been diagnosed by other imaging modalities. In recent years, commercially available computer-aided evaluation (CAE) systems for DCE-MRI have been developed. Automated software provides data including colorcoding kinetic maps and kinetic curves. The most suspicious type of kinetic curve in an analyzed lesion can be identified semi-automatically Fig. 1 on page 3. On colorcoding kinetic maps, different colors representing different kinetic characteristics are displayed within enhancing lesions Fig. 2 on page 3. CAE systems can also display the percentage of different curves in an analyzed volume Fig. 3 on page 4. It has been reported by several studies [3,4] that kinetic data from malignant lesions often exhibit rapid uptake and washout delayed pattern, while benign lesions tend to show slow uptake and persistent signal increase. However, enhancement kinetics of benign and malignant lesions often overlap [3], resulting in relatively low specificity. CAE evaluation generates detailed data from all pixels within the lesion. The entire enhancement pattern of an entire lesion might be a more accurate reflection of tumor biology than solely the most suspicious type kinetic curve of part of a lesion. There are sparse data regarding the effect of the particular commercially available CAEmeasured parameters that best predict malignancy. Our hypothesis was that malignant lesions might have more diverse or heterogeneous kinetic patterns, whereas benign lesions might have more homogeneous kinetic patterns. Purpose Page 2 of 24

3 The purpose of our study was to evaluate diversity of kinetic characteristics of malignant and benign masses detected initially at MRI, and to compare the new method to standard kinetic curve analysis. Images for this section: Fig. 1: The most suspicious type of kinetic curve in an analyzed lesion can be identified semi-automatically by a computer-aided evaluation (CAE) system. Page 3 of 24

4 Fig. 2: On color-coding kinetic maps obtained by a computer-aided evaluation (CAE) system, different colors representing different kinetic characteristics are displayed within an enhancing lesion. Page 4 of 24

5 Fig. 3: Percentages of different curves in an analyzed volume are shown, which are calculated semi-automatically by a computer-aided evaluation (CAE) system. Page 5 of 24

6 Methods and materials Patients and Lesions A retrospective review of pathology logs of sonographic guided and MRI guided biopsies from January 2006 to December 2011 was performed to identify suspicious breast masses that were detected initially at DCE-MRI. Non-mass enhancement (NME) was not included in our dataset, because prior studies [5, 6] suggested that kinetic parameters are not as useful in discriminating benign from malignant NME. Histology of all lesions was confirmed by sonographic guided or MRI guided percutaneous biopsy. MRI technique MR images were acquired using an Achieva 1.5T or an Achieva 3.0T scanner (Philips Healthcare) with use of a dedicated breast coil and patients in the prone position. The imaging protocols for both scanners consisted of unenhanced series, and dynamic pre and five or six post-contrast gradient echo THRIVE images, with the axial plane. Contrast injection was made with IV administration of 0.1 mmol/kg gadopentetate dimeglumine (Omniscan; GE Healthcare, Princeton, NJ) or 0.05 mmol/kg gadobenate dimeglumine (Multihance; Bracco Diagnostics Inc., Princeton, NJ) for patients whose estimated Glomerular filtration rate is less than 60 ml/min. CAE System and Kinetic Data All masses were evaluated with a commercially available CAE system (DynaCad, version , Philips Healthcare) retrospectively. The software incorporates three MR imaging series into its calculations: one pre-contrast gradient echo series, one early post-contrast gradient echo series, and one delayed postcontrast gradient echo series. To classify enhancing lesions, as to whether or not they exhibit "significant" enhancement, pixel values at the pre-contrast and the early postcontrast series are compared initially. If the pixel value on the early post-contrast series increases by a user-specified threshold compared to the pre-contrast series, the pixel will be shown in color. For this study, 50% and 100% thresholds were used for display of medium and rapid uptake. If a pixel value on the delayed post-contrast series decreases by more than 10% compared with the early post-contrast series, it is considered a washout pattern of delayed enhancement, and is color-coded red. If a pixel value increases by more than Page 6 of 24

7 10%, it is considered a persistent pattern of delayed enhancement, and is color-coded blue. If a pixel value does not increase or decrease by more than 10%, it is color-coded green or yellow, indicating a plateau pattern of delayed enhancement. The end result is a color overlay Fig. 2 on page 8 on each MRI slice indicating regions of significant enhancement and providing details about enhancement type and extent. Finally, color-coded lesions are selected manually and the program semi-automatically generates a synopsis of the full volume of that lesion, the initial peak enhancement value calculated as the highest percentage increase in signal intensity on the early postcontrast series, the most suspicious kinetic curve in the lesion Fig. 1 on page 8, and the proportions of medium-persistent, medium-plateau, medium-washout, rapidpersistent, rapid-plateau, and rapid-washout enhancement on the basis of the signal intensities of the multiple pixels comprising the lesion Fig. 3 on page 9. Diversity indices and statistical analyses To measure diversity of kinetic characteristics as a numerical value, we applied diversity measures to our data, the Shannon index Fig. 4: Equation of the Shannon index, where pi is the frequency of species i in the sample. In our study, a species is one of the 6 different kinetic characteristics. References: Tohoku University Hospital - Sendai/JP and the Simpson index Fig. 5: Equation of the Simpson index, where ni is the frequency of species i in the sample. In our study, a species is one of the 6 different kinetic characteristics. We used (1-l) x 100, a number between 0 to 100 that increases with increasing diversity of the sample. References: Tohoku University Hospital - Sendai/JP Page 7 of 24

8 , which are often used in the ecology sciences [7]. These diversity measures estimate the number and distribution of species in a certain geographical area and can be used to summarize the diversity of a population by a single number. In our context, a species is one of the 6 different kinetic characteristics. Hence, for example, a lesion containing areas with 6 different kinetic characteristics is interpreted to contain 6 distinct "species." Initial uptake rate (IUR) as well as signal enhancement ratio (SER) that is a measure of washout, were also calculated from the most suspicious dynamic curve of each lesion and were compared with the diversity indices, using the ROC analysis and the MannWhitney U test. p<0.05 was defined as statistically significant. Images for this section: Fig. 2: On color-coding kinetic maps obtained by a computer-aided evaluation (CAE) system, different colors representing different kinetic characteristics are displayed within an enhancing lesion. Page 8 of 24

9 Fig. 1: The most suspicious type of kinetic curve in an analyzed lesion can be identified semi-automatically by a computer-aided evaluation (CAE) system. Page 9 of 24

10 Fig. 3: Percentages of different curves in an analyzed volume are shown, which are calculated semi-automatically by a computer-aided evaluation (CAE) system. Fig. 4: Equation of the Shannon index, where pi is the frequency of species i in the sample. In our study, a species is one of the 6 different kinetic characteristics. Page 10 of 24

11 Fig. 5: Equation of the Simpson index, where ni is the frequency of species i in the sample. In our study, a species is one of the 6 different kinetic characteristics. We used (1-l) x 100, a number between 0 to 100 that increases with increasing diversity of the sample. Page 11 of 24

12 Results Patients and Lesions During the study period, a total of 159 breast masses detected initially at MRI, were biopsied with sonographic or MRI guidance at our institution. 32 lesions were excluded from the analyses because final pathology results were atypical lesions. 40 lesions were also excluded for technical reasons; for 38 cases (23 malignant and 15 benign) enhancing lesions could not be separated from surrounding parenchymal enhancement by CAE; for 2 cases (1 malignant and 1 benign) lesions could not be processed with CAE because of low initial uptake (less than 50%). The remaining 87 MRI detected masses (44 malignant and 43 benign) were the subjects of this study. Histological types of lesions are listed in Table 1. Fig. 6: Table 1: Histological type of benign and malignant masses. Page 12 of 24

13 References: Tohoku University Hospital - Sendai/JP Overall mean mass size was 10.9 mm. The mean lesion size of benign masses was 9.6 mm (SD, 3.1), and that of malignant masses was 12.2 mm (SD, 3.8). Of the 87 masses, 61 lesions (70.1%) were biopsied under sonographic guidance, and 26 lesions (32.1%) were biopsied under MRI guidance. The clinical indications for breast MRI for the cases included newly diagnosed cancer (n=56), high-risk screening (n=21), problem solving (n=5), short-term follow-up (n=3), and axillary adenopathy with unknown primary (n=2). Case 1 Page 13 of 24

14 Fig. 7: Case 1 (malignant mass): MR images of a 45 year-old female with prior history of right breast carcinoma, who had a screening MRI. (a) An early phase of axial post contrast gradient echo image demonstrates an enhancing round mass measuring 8 mm with smooth margins (arrow) in the left breast, which is mammographically occult. The mass was subsequently found by a targeted sonography and was proven to be infiltrating ductal carcinoma. (b) On a subtraction image generated by CAE system with Page 14 of 24

15 color overlay applied, the enhancing mass (arrow) is shown to have diverse kinetic characteristics. (c) The most suspicious kinetic curve of the mass was rapid uptake (IUR: 143%), and washout pattern (SER: 1.25). (d) Proportions of six kinetic patterns were calculated by CAE system. Shannon and Simpson indices were 5.4 and 80.9, respectively, which are both higher than those of case 2. References: Department of Radiology, The University of Chicago Case 2 Page 15 of 24

16 Fig. 8: Case 2 (benign mass): MR images of a 78 year-old female with a newly diagnosed left breast infiltrating ductal carcinoma, who underwent a staging MRI. (a) An early phase of axial post contrast gradient echo image demonstrates an enhancing mass measuring 8 mm with smooth margins (arrow) in the right breast. The mass was subsequently found by a targeted sonography and was proven to be a benign papilloma. (b) On a subtraction image generated by CAE system with color overlay applied, the enhancing mass (arrow) has homogeneous kinetic characteristics, Page 16 of 24

17 predominantly with washout kinetics. (c) The most suspicious kinetic curve of the mass, obtained semi-automatically by CAE system, demonstrates rapid uptake (IUR: 147%)and washout pattern (SER: 1.60). (d)proportions of six kinetic patterns are generated by CAE system. Shannon and Simpson indices were 3.39 and 64.5, respectively, which are both lower than those of case 1. References: Department of Radiology, The University of Chicago Median, p-values from the Mann-Whitney U test, and areas under the curve (AUC) of Initial uptake rate (IUR), Signal enhancement ratio (SER), Shannon index and Simpson index are shown in Table 2. Fig. 9: Table 2: Median, p-values (Mann-Whitney U test) and AUCs of initial uptake rate (IUR), signal enhancement ratio (SER), Shannon index and Simpson index are shown. References: Tohoku University Hospital - Sendai/JP Of the 4 valuables, only the Shannon index showed a statistically significant difference between malignant and benign masses. AUCs of the Shannon and Simpson indices were higher, compared to those of IUR and SER. Images for this section: Page 17 of 24

18 Fig. 6: Table 1: Histological type of benign and malignant masses. Page 18 of 24

19 Fig. 7: Case 1 (malignant mass): MR images of a 45 year-old female with prior history of right breast carcinoma, who had a screening MRI. (a) An early phase of axial post contrast gradient echo image demonstrates an enhancing round mass measuring 8 mm with smooth margins (arrow) in the left breast, which is mammographically occult. The mass was subsequently found by a targeted sonography and was proven to be infiltrating ductal carcinoma. (b) On a subtraction image generated by CAE system with color overlay Page 19 of 24

20 applied, the enhancing mass (arrow) is shown to have diverse kinetic characteristics. (c) The most suspicious kinetic curve of the mass was rapid uptake (IUR: 143%), and washout pattern (SER: 1.25). (d) Proportions of six kinetic patterns were calculated by CAE system. Shannon and Simpson indices were 5.4 and 80.9, respectively, which are both higher than those of case 2. Page 20 of 24

21 Fig. 8: Case 2 (benign mass): MR images of a 78 year-old female with a newly diagnosed left breast infiltrating ductal carcinoma, who underwent a staging MRI. (a) An early phase of axial post contrast gradient echo image demonstrates an enhancing mass measuring 8 mm with smooth margins (arrow) in the right breast. The mass was subsequently found by a targeted sonography and was proven to be a benign papilloma. (b) On a subtraction image generated by CAE system with color overlay applied, the enhancing mass (arrow) has homogeneous kinetic characteristics, predominantly with washout kinetics. (c) The most suspicious kinetic curve of the mass, obtained semi-automatically by CAE system, demonstrates rapid uptake (IUR: 147%)and washout pattern (SER: 1.60). (d)proportions of six kinetic patterns are generated by CAE system. Shannon and Simpson indices were 3.39 and 64.5, respectively, which are both lower than those of case 1. Fig. 9: Table 2: Median, p-values (Mann-Whitney U test) and AUCs of initial uptake rate (IUR), signal enhancement ratio (SER), Shannon index and Simpson index are shown. Page 21 of 24

22 Conclusion In this study, the Shannon index of kinetic characteristics demonstrated a statistically significant difference between malignant and benign breast masses, although the Simpson index, another parameter that we used to measure diversity of kinetics, did not show a statistical significance. The results from the Shannon index means that malignant masses are more diverse in kinetic patterns, compared to benign masses. In contrast, there were no significant differences in initial uptake rate (IUR) or signal enhancement ratio (SER) between malignant and benign masses, which were obtainded from the most suspicious type of standard kinetic curves of each lesion. In addition, it was shown that AUC of the Shnnon and Simpson indices of kinetic internal enhancement were higher compared to IUR and SER. Thus, assessing diversity of kinetic characteristics from the whole lesion volume has the potential to improve the accuracy when evaluating breast masses that are initially detected at DCE-MRI. In our study, IUR and SER did not demonstrate a significant difference between malignant and benign masses, which is in contrast to several prior studies without using CAE, showing higher IUR and washout delayed pattern to be predictors of malignancy [6,7, 8-11]. Our study included only lesions with IUR of at least 50%, which may explain the difference between the previous investigations and our study, because lesions with slower (less than 50%) uptake were eliminated in our study. As for delayed kinetic pattern, studies (12,13) which did use a CAE system also failed to demonstrate significant differences in delayed enhancement type comparing benign and malignant lesions. It is possible that the results of prior studies without using CAE could be due to sampling error, as small areas within some lesions could have suspicious kinetics but may have been missed due to manual region of interest evaluation. Our inclusion criteria may also account for the disparity in delayed enhancement type results. That is, it could at least partially be due to the fact that only biopsy-proven benign lesions that were suspicious enough to justify a biopsy were selected for our study and most of classically benign lesions with benign type kinetic characteristics, which did not warrant a biopsy, were excluded from our study. It is also important to recognize that two malignant masses were excluded from analyses for this study, because the two lesions could not be processed with CAE because of low initial uptake (less than 50%). Therefore it should be emphasized that kinetic characteristics should not be used as the sole diagnostic discriminator. Although Page 22 of 24

23 morphologic characteristics are not evaluated in this study, if morphological features are also taken into account, the relatively low AUC of all parameters in our study might be increased to a sufficient level. Limitations There are several limitations to our study. This study was a retrospective, single-site investigation. Thus, our findings might not be generalizable to other sites. As a single manufacturer was used for this work, kinetic characteristics obtained with breast MRI CAE by other manufacturers should be evaluated in the future. 38 MRI exams were excluded from analyses for our study, because breast masses could not be separated from surrounding parenchymal enhancement. Therefore, our observation might not be applicable to breast masses in a background of extensive parenchymal enhancement. In addition, this study and prior work [4, 13-15], in which different significant predictors of malignancy have been reported, might all support the conclusion of Jansen et al. [16] that there is variability across systems that combine different magnets, coils and CAE components. Therefore, CAE data should be used with caution. Conclusion In conclusion, assessment of diversity of kinetic characteristics from the whole lesion volume showed a significant difference between malignant and benign masses detected initially at MRI and classified as BI-RADS 4, and was superior to standard kinetic curve analysis. This particular kinetic measure may prove useful in the evaluation of breast masses on MR imaging, particularly as it has the potential to reduce the number of false positive cases, thereby increasing the cost-effectiveness of this breast imaging modality. Personal information References Kuhl CK. MRI of breast tumors. Eur Radiol 2000; 10:46-58 Wedegärtner U, Bick U, Wörtler K, Rummeny E, Bongartz G. Differentiation between benign and malignant findings on MR-mammography: usefulness of morphological criteria. Eur Radiol 2001; 11: Page 23 of 24

24 Kuhl CK, Mielcareck P, Klaschik S, et al. Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions? Radiology 1999; 211: Schnall MD, Blume J, Bluemke DA, et al. Diagnostic architectural and dynamic features at breast MR imaging: multicenter study. Radiology 2006; 238:42-53 Jansen SA, Fan X, Karczmar GS, et al. DCEMRI of breast lesions: is kinetic analysis equally effective for both mass and nonmass-like enhancement? Med Phys 2008; 35: Newell D, Nie K, Chen JH, et al. Selection of diagnostic features on breast MRI to differentiate between malignant and benign lesions using computeraided diagnosis: differences in lesions presenting as mass and non-mass-like enhancement. Eur Radiol 2009 Magurran AE. Measuring Biological Diversity. Malden, MA: Blackwell ; Kaiser WA, Zeitler E. MR imaging of the breast: fast imaging sequences with and without Gd-DTPA. Preliminary observations. Radiology 1989; 170: Kinkel K, Helbich TH, Esserman LJ, et al. Dynamic high-spatial-resolution MR imaging of suspicious breast lesions: diagnostic criteria and interobserver variability. AJR Am J Roentgenol 2000; 175:35-43 Mussurakis S, Gibbs P, Horsman A. Peripheral enhancement and spatial contrast uptake heterogeneity of primary breast tumours: quantitative assessment with dynamic MRI. J Comput Assist Tomogr 1998; 22:35-46 Stomper PC, Herman S, Klippenstein DL, et al. Suspect breast lesions: findings at dynamic gadolinium-enhanced MR imaging correlated with mammographic and pathologic features. Radiology 1995; 197: Williams TC, DeMartini WB, Partridge SC, Peacock S, Lehman CD. Breast MR imaging: computer-aided evaluation program for discriminating benign from malignant lesions. Radiology 2007; 244: Preim U, Glaßer S, Preim B, Fischbach F, Ricke J. Computer-aided diagnosis in breast DCE-MRI--quantification of the heterogeneity of breast lesions. Eur J Radiol 2012; 81: Wang LC, DeMartini WB, Partridge SC, Peacock S, Lehman CD. MRIdetected suspicious breast lesions: predictive values of kinetic features measured by computer-aided evaluation. AJR Am J Roentgenol 2009; 193: Lehman CD, Peacock S, DeMartini WB, Chen X. A new automated software system to evaluate breast MR examinations: improved specificity without decreased sensitivity. AJR Am J Roentgenol 2006; 187:51-56 Jansen SA, Shimauchi A, Zak L, et al. Kinetic curves of malignant lesions are not consistent across MRI systems: need for improved standardization of breast dynamic contrast-enhanced MRI acquisition. AJR Am J Roentgenol 2009; 193: Page 24 of 24