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Optimized tumor volumes by dynamic contrast enhanced MR imaging for assessing response to neoadjuvant chemotherapy in triple negative breast cancer1Imaging Physics, MD Anderson Cancer Center, Houston, TX, United States, 2Diagnostic Radiology, MD Anderson Cancer Center, Houston, TX, United States, 3Breast Medical Oncology, MD Anderson Cancer Center, Houston, TX, United States, 4Cancer Systems Imaging, MD Anderson Cancer Center, Houston, TX, United States
Synopsis
We evaluated several methods of measuring tumor volumes on DCE MRI for assessment of treatment response in triple negative breast cancer (TNBC) undergoing neoadjuvant chemotherapy (NAC), including functional tumor volume (FTV), enhanced tumor volume(ETV), and clinical tumor volume (CTV). We compared different parameters for measurement of functional tumor volume at baseline as well as its changes during therapy, and established optimal parameters for FTV measurements. We found that optimized FTV and ETV have potential to serve as an imaging biomarker for evaluation of NAC treatment response in TNBC patients
Introduction
Tumor perfusion characterization with dynamic contrast enhanced (DCE) MRI has been reported useful in the diagnosis and assessment of therapeutic response in breast cancer1. In particular, changes in tumor volumes on DCE have been shown to predict response to neoadjuvant chemotherapy (NAC) in breast cancer2. However, tumor volumes have been measured using several different methods, including using Enhanced Tumor Volume (ETV)3 and Functional Tumor Volume (FTV)2. In this study, we compared several different methods of measuring tumor volumes and evaluated how they may be useful as potential imaging markers for NAC treatment response in triple-negative breast cancer (TNBC).Methods
Twenty-four patients with biopsy-confirmed TNBC were included in this IRB approved study. After completion of therapy, patients underwent surgical resection and their histopathological findings were used as the standard for treatment response evaluation. MRI exams were conducted at baseline before the start of therapy (MRI1), after four cycles of therapy at mid-treatment (MRI2), and pre-surgery (MRIF). MR exams included T2-w anatomic scans and a DCE MRI scan using the DISCO technique with Dixon water-fat separation4. Typical scan parameters for the DCE MRI scan were as follows: FOV=34x34cm, slice thickness=3.0mm, FA=12°, TR/TE1/TE2=7.4,1.1,2.3ms, matrix=320x320, TA=7.1 mins, # phases =14. Temporal resolution of the DCE scan after acquisition of the mask phase ranged from 25-45 s due to variation in patient size. After obtaining the mask phase, a single bolus of Gadovist contrast agent was injected (~2 mL/s) followed by the DCE scan.
Using the contrast enhancement curve at a major blood vessel, an early-phase was selected for each study. A late-phase was selected as the last phase of the DCE scan. Subtraction images were calculated as the difference between the early phase and mask phase images. The product of the linear tumor dimensions in the sagittal, cranio-caudal, and anterior-posterior directions was calculated as the clinical tumor volume (CTV, Fig. 1a). Contours of the tumors were drawn by an experienced radiologist on early phase subtraction images. ETV was extracted as the entire contoured volume (Fig. 1b). FTV was extracted as a subset of ETV that met pre-defined percentage enhancement (PE) and signal enhancement ratio (SER) thresholds (Fig. 1c)5. Different combinations of PE thresholds (0% to 220%, in increments of 10%) and SER thresholds (0 to 1.4, in increments of 0.05) were investigated for calculating FTV.
Tumor CTV, ETV, and FTV at the different measurement points and their relative changes were compared between responders and non-responders based on final histopathology at surgery using receiver operator curve (ROC) analysis and Mann-Whitney U-test (MW). Heat maps of FTV area under curves (AUC) as a function of PE and SER thresholds were generated to determine the performance and stability. An optimal FTV was selected through visual examination of the heat maps. This was done separately for different FTV measurements or relative change. A p-value below 0.05 was considered significant. MW p-values were not corrected for multiple comparisons.
Results
Of the twenty-four patients, eleven were responders (46%). FTV showed good stability at the following PE/SER thresholds: PE>0%/SER>0.55 for ΔMRIF (Fig. 2a), PE>0%/SER>0.85 for MRIF (Fig. 2b), and PE>0%/SER>0.45 for MRI1 (Fig. 2c). ΔMRIF FTV was best in differentiating responders versus non-responders (Fig. 3a, AUC=0.9, pMW<0.0014**), while ΔMRIF of ETV showed a similar performance (Fig. 3b, AUC=0.878, pMW<0.0066**). MRIF FTV (Fig. 3c) and ETV (Fig. 3d) also provided good discrimination between those two groups (AUC = 0.878, 0.889 and pMW<0.0026**, 0.0020**, respectively). Other tumor volume measurements that provided good discrimination between the two patient groups included MRI1 FTV (Fig. 3e), ETV (Fig. 3f), and CTV (Fig. 3g) (AUC = 0.755, 0.825, 0.832 and pMW<0.038*, 0.0078**,0.0065**, respectively).Discussion
Our study demonstrated that FTV and ETV measured at baseline and their changes during the treatment had good correlation with treatment response in patients with TNBC undergoing NAC. These findings are consistent with those reported by other researchers2. CTV at baseline was useful but was out-performed by both FTV and ETV. Mid-treatment measurements did not perform as strongly as the baseline treatment. Interestingly, none of the FTV measurements were improved from applying a PE threshold, in contrast to an earlier report on the benefit of employing a combined set of SER and PE thresholds5. This was likely because an optimal PE threshold may have been implicitly applied in the radiologist’s contour in our study. Optimized FTV and ETV have potential to serve as an imaging biomarker for evaluation of NAC treatment response in TNBC patients.Acknowledgements
No acknowledgement found.References
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3. Henderson SA, Muhammad Gowdh N, Purdie CA, et al. Breast cancer: influence of tumour volume estimation method at MRI on prediction of pathological response to neoadjuvant chemotherapy. The British journal of radiology. 2018;91(1087):20180123.
4. Saranathan M, Rettmann DW, Hargreaves BA, Clarke SE, Vasanawala SS. DIfferential Subsampling with Cartesian Ordering (DISCO): a high spatio-temporal resolution Dixon imaging sequence for multiphasic contrast enhanced abdominal imaging. Journal of magnetic resonance imaging : JMRI. 2012;35(6):1484-1492.
5. Lo W-C, Li W, Jones EF, et al. Effect of imaging parameter thresholds on MRI prediction of Neoadjuvant chemotherapy response in breast cancer subtypes. PloS one. 2016;11(2):e0142047-e0142047.
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