ESTRO 2020 Abstract book

S448 ESTRO 2020

2 Rajiv Gandhi Cancer Institute & Research Centre, Senior Resident Radiologist, Rohini- Delhi, India ; 3 Rajiv Gandhi Cancer Institute & Research Centre, Senior Resident Medical Oncologist, Rohini- Delhi, India ; 4 Rajiv Gandhi Cancer Institute & Research Centre, Consultant Radiologist, Rohini- Delhi, India ; 5 Rajiv Gandhi Cancer Institute & Research Centre, Consultant Radiation Oncologist, Rohini- Delhi, India ; 6 Rajiv Gandhi Cancer Institute & Research Centre, Attending Consultant Radiation Oncologist, Rohini- Delhi, India ; 7 Rajiv Gandhi Cancer Institute & Research Centre, Senior Resident Radiation Oncologist, Rohini- Delhi, India ; 8 Rajiv Gandhi Cancer Institute & Research Centre, Resident Radiation Oncologist, Rohini- Delhi, India ; 9 Rajiv Gandhi Cancer Institute & Research Centre, Research Assistant, Rohini- Delhi, India ; 10 Rajiv Gandhi Cancer Institute & Research Centre, Director Radiology, Rohini- Delhi, India ; 11 Rajiv Gandhi Cancer Institute & Research Centre, Chair Radiology, Rohini- Delhi, India Purpose or Objective Apparent Diffusion Coefficient (ADC) is proposed as a potential marker in response evaluation in many malignancies.The purpose of our study was to compare quantitative MRI (ADC values) and clinically correlate with outcomes in patients with cervical cancer. Material and Methods MR studies of histopathologically confirmed cervical Squamous Cell Carcinoma patients (n= 133) presenting to our institute, were retrospectively analyzed. Patients included for the study had locally advanced disease, stages IIB to IVA. ADC values were retrospectively measured from pretreatment MR images. The mean ADC value was measured in a region of interest (ROI by drawing an arbitrary circle of area 0.35 cm 2 ) chosen after imaging analysis and corresponding to the best area of diffusion restriction. Further treatment with brachytherapy(BT) was done as per the residual disease after EBRT. Brachytherapy (BT) was either intracavitatory (ICRT) or interstitial using the MUPIT template. Change of ADC values was correlated with the outcomes and disease related parameters. Median ADC was charted for all patients and subdivided into a low ADC change group <0.48 vs high ADC change group >0.48. Results 100 patients underwent ICRT and 33 underwent MUPIT. Baseline ADC mean value (range ±SD) was 0.93(0.55- 1.53±0.159)in ICRT vs 0.94( 0.53-1.55 ± 0.265) in MUPIT. Post EBRT mean ADC in ICRT was 1.50(0.68-1.94 ± 0.237) vs 1.42 (0.66-1.86 ± 0.329) in MUPIT. ADC change in ICRT was 0.66(0.51-2.35± 0.413) vs -0.46(-0.78 to -0.07 ± 0.173) in MUPIT. 4% (4/100) had nodal positivity in ICRT compared to 24%(8/33) in MUPIT. In ICRT 13% (13/100) had metastatic disease on follow up vs 10 % (3/30) in MUPIT arm. Stage distribution in ICRT arm (stage II, III, IV) is 49%, 45%, 6% vs 27%, 61%, 12% in MUPIT arm. In ICRT arm 4%(4/100) had recurrence compared to 8/33(24%) in MUPIT arm. Change in ADC was significant between 2 groups(p value <0.001). Median recurrence free survival for ICRT was 25 vs 9 months in MUPIT arm. Correlation of change in ADC with recurrence in the ICRT vs MUPIT group was statistically insignificant. High ADC change had better survival in both groups when compared to low ADC Group and more significant in the MUPIT group as shown in Figure. Change of ADC is significantly correlated with the stage(p value = 0.025) and correlation is more strong when stage III and IV were clubbed together compared to stage 2 (p value=0.012). Lymph node status was not significantly correlated with ADC change probably because of the low

Results Two-hundred and five RF were extracted by using a previously validated semi-automatic SUV gradient-based method and 133 out of them were excluded due to poor repeatability/reproducibility, mostly due to delineation uncertainty. Among 72 selected robust RF only 7 were conserved after redundancy filtering; the resulting COX multivariable models for OS, LRFS and DRFS are reported in Table 1 with/without including clinical variables; Kaplan Mayer curves including only RF are shown in Figure 1. Models based on few (i.e.: one-two) independent RF were able to clearly stratify pts in risk classes for all end-points. In particular, a surprisingly high ability in stratifying pts according to the risk to develop distant metastasis (HR= 0.24) or local relapse (HR=0.38) was found, as reported in Figures 1B-C: two first order RF (COM_shift and percentile10) and one texture RF (small-zone-emphasis) were the best RF predictors for DRFS and LRFS respectively. As shown by p values and hazard ratios in Table 1, the addition of clinical factors (pre-RT GICA/stage for OS/LRFS) did not significantly improve the models performances. Bootstrap based validation showed that the results were sufficiently robust. Conclusion Few robust PET-RF carefully predicted the outcome of LAPC pts after chemo-RT. External validations of the models are in progress on an independent group of patients treated in the same Institute and in another large group treated in additional three Institutes. If confirmed, current results could have dramatically positive impact on LAPC personalized treatment. PH-0718 Quantitative MRI in prognosticating clinical outcomes in carcinoma cervix treated with Radiotherapy S. Mitra 1 , A. Jajodia 2 , V.P.B. Koyyala 3 , V. Mahawar 4 , A. Dewan 5 , S. Aggarwal 6 , I. Singh Wahi 6 , S. Barik 7 , K. Dobriyal 8 , J. Mukhee 8 , H. Khurana 9 , R. Tripathy 9 , A. Rao 10 , A. Chaturvedi 11 1 Rajiv Gandhi Cancer Institute & Research Centre, Senior Consultant Radiation Oncologist, Rohini- Delhi, India ;