ESTRO 2020 Abstract book

S321 ESTRO 2020

chemotherapy dose (3 vs 2 OXA cycle) on cCR&pCR prediction is plotted vs ERI TCP . Conclusion Current results confirmed ERI TCP as a promising index in predicting pathological response after neo-adjuvant RT for rectal cancer and clearly quantify the heavy detrimental effect of avoiding OXA in the last part of RT.

PD-0539 Chemo-modulation of rectal cancer pathological response: prediction of an early regression index S. Broggi 1 , C. Gumina 2 , M. Mori 1 , G.M. Cattaneo 1 , A. Palmisano 3 , A. Di Chiara 3 , M. Ronzoni 4 , N. Slim 5 , F. De Cobelli 3 , R. Calandrino 1 , R. Rosati 6 , N.G. Di Muzio 5 , C. Fiorino 1 , P. Passoni 5 1 IRCCS San Raffaele Scientific Institute, Medical Physics, Milano, Italy ; 2 IRCCS Policlinico San Donato, Radiotherapy, Milano, Italy ; 3 IRCCS San Raffaele Scientific Institute, Radiology, Milano, Italy ; 4 IRCCS San Raffaele Scientific Institute, Oncology, Milano, Italy ; 5 IRCCS San Raffaele Scientific Institute, Radiotherapy, Milano, Italy ; 6 IRCCS San Raffaele Scientific Institute, Gastroenterology Surgery, Milano, Italy Purpose or Objective A radiobiological parameter (early regression index, ERI TCP ) based on early tumor (GTV) regression was previously found to predict pathological complete remission (pCR) after neo-adjuvant radio-chemotherapy (RCT) of locally advanced rectal cancer (Rca) as well as long-term outcome. In current investigation, ERI TCP was used to investigate and model the impact of changes of the delivered chemotherapy regimen on the pathological response. Material and Methods 95 patients were treated following and adaptive (ART) protocol (41.4 Gy/18fr;2.3Gy/fr) delivering a simultaneous integrated boost on the residual GTV in the last 6 fractions (3 Gy/fr) for a total dose of 45.6 Gy. Chemotherapy consisted of oxaliplatin (OXA) 100 mg/m 2 on days -14, 0 (start of RT), and +14, and 5-fluorouracil (5-FU) 200 mg/m 2 /d from day -14 to the end of RT. Most patients (84%) received a 5-FU dose > 90%. The original protocol was seldom modified, based on oncologist’s preference: 59 pts received OXA three times, as planned, while in 36 pts the OXA dose at day +14, was not administered. For 82 patients, T2 weighed MRIs taken at planning and at half- RT were available and GTVs were respectively contoured (V pre and V half ): ERI TCP (equal to ERI TCP = -ln[(1 – (V half / V pre )) Vpre ], was calculated. The discriminative power of ERI TCP (in terms of AUC, sensitivity/specificity, positive/negative predictive value) was separately assessed for the two patients groups with different OXA regimen (2 vs 3 OXA cycles), by considering as end points both the clinical/pathological complete response (cCR&pCR) and the “limited response” (defined by a residual vital cells-RVC >10%). The impact of OXA and of selected clinical parameters on cCR&pCR was also investigated trough multivariate logistic regression. Results Complete data were available for 82 patients (21 pCR and 2 cCR not followed by surgery), 53 pts treated with 3 OXA cycles and 29 pts with 2 cycles: the percentage value of cCR&pCR was 32% and 14% in the two groups, respectively while ERI TCP was not significantly different. The discriminative power of ERI TCP was moderately high, both for cCR&pCR (AUC= 0.74; sensitivity=78%; PPV= 49%; NPV=89%) and for RVC>10% (AUC= 0.70; sensitivity=79%; PPV=55%, NPV=85%). The power increases by considering the patients treated with three OXA cycles (AUC=0.78/0.78; sensitivity=79%/92%, PPV=60/43%, NPV=86/96% for cCR&pCR/RVC>10%). In a logistic multivariate regression (p=0.0001; H&Ltest=0.70), ERI TCP (OR= 0.90, 95%CI=0.88-0.98) and the number of OXA cycles (OR= 4.3, 95%CI=1.22-15.3) were the only two independent variables predictive of cCR&pCR. In Figure 1 the effect of

Poster discussion: PH: Radiobiological and predictive modelling, and radiomics 2

PD-0540 A pooling method for feature selection of quantitative imaging analysis: survival analysis in glioma Z. Shi 1 , C. Zhang 1 , I. Compter 1 , M. Verduin 2 , A. Hoeben 2 , D. Eekers 1 , A. Dekker 1 , L. Wee 1 1 GROW School for Oncology and Developmental Biology- Maastricht University Medical Centre+, Department of Radiation Oncology MAASTRO CLINIC, Maastricht, The Netherlands ; 2 GROW School for Oncology and Developmental Biology- Maastricht University Medical Centre+, Department of Medical Oncology, Maastricht, The Netherlands Purpose or Objective We propose a pooling-based quantitative imaging feature selection method and showed how it would be applied to the clinical question of predicting two-year survival of glioma patients treated by radiotherapy (RT). Material and Methods Data from 130 patients with pathologically confirmed glioma treated at a single RT centre between January 2004 and December 2014 were collected. All patients only received a biopsy prior to high-dose RT with temozolomide or RT only. Follow-up consisted of quarterly clinical consultations including MRI examination, until death from any cause. MRI and CT images were co-registered and a gross tumour volume (GTV) was manually delineated by an experienced radiation oncologist. RT dose and radiomic features were calculated on helical CT (Siemens, Erlangen, Germany) with 0.98 mm by 0.98 mm pixels, 1mm reconstructed slice thickness and 120 kVp tube potential. A total of 1092 radiomic features were extracted from the GTV via an open-source radiomics package O-RAW that is an extension wrapper of PyRadiomics. The feature selection procedures consisting of 5 steps were shown in Figure 1: (1) split samples into in-train and in-test sets with