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Abstract Background and purpose Currently, the inhomogeneity of the pulmonary function is not considered when treatment plans are generated in thoracic cancer radiotherapy. This study evaluates the dose of treatment plans on highly-functional volumes and performs functional treatment planning by incorporation of ventilation data from 4D-CT. Materials and methods Eleven patients were included in this retrospective study. Ventilation was calculated using 4D-CT. Two treatment plans were generated for each case, the first one without the incorporation of the ventilation and the second with it. The dose of the first plans was overlapped with the ventilation and analyzed. Highly-functional regions were avoided in the second treatment plans. Results For small targets in the first plans (PTV Conclusion Radiation treatments affect functional lung more seriously in large tumor cases. With compromise of dose to other critical organs, functional treatment planning to reduce dose in highly-functional lung volumes can be achieved

Abstract Purpose Frequently, three-dimensional (3D) conformal beams are used in lung cancer stereotactic body radiotherapy (SBRT). Recently, volumetric modulated arc therapy (VMAT) was introduced as a new treatment modality. VMAT techniques shorten delivery time, reducing the possibility of intrafraction target motion. However dose distributions can be quite different from standard 3D therapy. This study quantifies those differences, with focus on VMAT plans using unflattened photon beams. Methods A total of 15 lung cancer patients previously treated with 3D or VMAT SBRT were randomly selected. For each patient, non-coplanar 3D, coplanar and non-coplanar VMAT and flattening filter free VMAT (FFF-VMAT) plans were generated to meet the same objectives with 50 Gy covering 95% of the PTV. Two dynamic arcs were used in each VMAT plan. The couch was set at ± 5° to the 0° straight position for the two non-coplanar arcs. Pinnacle version 9.0 (Philips Radiation Oncology, Fitchburg WI) treatment planning system with VMAT capabilities was used. We analyzed the conformity index (CI), which is the ratio of the total volume receiving at least the prescription dose to the target volume receiving at least the prescription dose; the conformity number (CN) which is the ratio of the target coverage to CI; and the gradient index (GI) which is the ratio of the volume of 50% of the prescription isodose to the volume of the prescription isodose; as well as the V20, V5, and mean lung dose (MLD). Paired non-parametric analysis of variance tests with post-tests were performed to examine the statistical significance of the differences of the dosimetric indices. Results Dosimetric indices CI, CN and MLD all show statistically significant improvement for all studied VMAT techniques compared with 3D plans (p < 0.05). V5 and V20 show statistically significant improvement for the FFF-VMAT plans compared with 3D (p < 0.001). GI is improved for the FFF-VMAT and the non-coplanar VMAT plans (p < 0.01 and p < 0.05 respectively) while the coplanar VMAT plans do not show significant difference compared to 3D plans. Dose to the target is typically more homogeneous in FFF-VMAT plans. FFF-VMAT plans require more monitor units than 3D or non-coplanar VMAT ones. Conclusion Besides the advantage of faster delivery times, VMAT plans demonstrated better conformity to target, sharper dose fall-off in normal tissues and lower dose to normal lung than the 3D plans for lung SBRT. More monitor units are often required for FFF-VMAT plans.

Introduction: To develop a radiomic‐based model to predict pathological complete response (pCR) and outcome following neoadjuvant chemoradiotherapy (NACRT) in oesophageal cancer. Methods: We analysed 68 patients with oesophageal cancer treated with NACRT followed by esophagectomy, who had staging 18F‐fluorodeoxyglucose (18F‐FDG) positron emission tomography (PET) and computed tomography (CT) scans performed at our institution. An in‐house data‐chjmirocterization algorithm was used to extract 3D‐radiomic features from the segmented primary disease. Prediction models were constructed and internally validated. Composite feature, Fc = α * FPET + (1 − α) * FCT, 0 ≤ α ≤ 1, was constructed for each corresponding CT and PET feature. Loco‐regional control (LRC), recurrence‐free survival (RFS), metastasis‐free survival (MFS) and overall survival (OS) were estimated by Kaplan–Meier analysis, and compared using log‐rank test. Results: Median follow‐up was 59 months. pCR was achieved in 34 (50%) patients. Five‐year RFS, LRC, MFS and OS were 67.1%, 88.5%, 75.6% and 57.6%, respectively. Tumour Regression Grade (TRG) 0–1 indicative of complete response or minimal residual disease was significantly associated with improved 5‐year LRC [93.7% vs 71.8%; P = 0.020; HR 0.19, 95% CI 0.04–0.85]. Four sepjmirote pCR predictive models were built for CT alone, PET alone, CT+PET and composite. CT, PET and CT+PET models had AUC 0.73 ± 0.08, 0.66 ± 0.08 and 0.77 ± 0.07, respectively. The composite model resulted in an improvement of pCR predicting power with AUC 0.87 ± 0.06. Stratifying patients with a low versus high radiomic score showed clinically relevant improvement in 5‐year LRC favouring low‐score group (91.1% vs. 80%, 95% CI 0.09–1.77, P = 0.2). Conclusion: The composite CT/PET radiomics model was highly predictive of pCR following NACRT. Validation in larger data sets is warranted to determine whether the model can predict clinical outcomes. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study was to characterize pre-treatment non-contrast computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (PET) based radiomics signatures predictive of pathological response and clinical outcomes in rectal cancer patients treated with neoadjuvant chemoradiotherapy (NACR T). Materials and methods: An exploratory analysis was performed using pre-treatment non-contrast CT and PET imaging dataset. The association of tumor regression grade (TRG) and neoadjuvant rectal (NAR) score with pre-treatment CT and PET features was assessed using machine learning algorithms. Three separate predictive models were built for composite features from CT + PET. Results: The patterns of pathological response were TRG 0 (n = 13; 19.7%), 1 (n = 34; 51.5%), 2 (n = 16; 24.2%), and 3 (n = 3; 4.5%). There were 20 (30.3%) patients with low, 22 (33.3%) with intermediate and 24 (36.4%) with high NAR scores. Three separate predictive models were built for composite features from CT + PET and analyzed separately for clinical endpoints. Composite features with α = 0.2 resulted in the best predictive power using logistic regression. For pathological response prediction, the signature resulted in 88.1% accuracy in predicting TRG 0 vs. TRG 1-3; 91% accuracy in predicting TRG 0-1 vs. TRG 2-3. For the surrogate of DFS and OS, it resulted in 67.7% accuracy in predicting low vs. intermediate vs. high NAR scores. Conclusion: The pre-treatment composite radiomics signatures were highly predictive of pathological response in rectal cancer treated with NACR T. A larger cohort is warranted for further validation. [ABSTRACT FROM AUTHOR]

Purpose: Forward-planned conformal arcs (termed dynamic arcs in the BrainLab iPlan system) have been routinely used in cranial stereotactic radiosurgery (SRS) for many years. This study compares dosimetric parameters of the newer, inversely-planned volumetric modulated arc therapy (VMAT) and VMAT-conformal hybrid plans with conformal arc plans. In the hybrid plans, various numbers of conformal arcs in a conformal plan are replaced with VMAT arcs. Methods: Ten brain cancer cases previously treated on a Novalis accelerator for frameless cranial stereotactic radiosurgery using conformal arcs generated by BrainLab iPlan treatment planning system were retrospectively studied with various numbers of VMAT arcs replacing the conformal arcs. Pure VMAT plans of different numbers of arcs were also generated using the same angle and arc length setup for all or part of the conformal arcs and compared with both the original and hybrid plans. Pinnacle version 9.0 was used for treatment plan generation. SmartArc was used for the VMAT planning for a Novalis accelerator . The conformity index (CI), deined as the ratio of the isodose volume to the isodose covered target volume, gradient index (GI), deined as the ratio of the 50% isodose volume (V50) to the 100% isodose volume, volume covered by 12 Gy isodose (V12), mean dose and standard deviation of dose in target were studied. Results: With one of the conformal arcs replaced with a VMAT arc of the same weighting and geometric setup, the average CI with one standard deviation was improved from 1.35 ± 0.18 to 1.29 ± 0.15 (p-value 0.03), while the average GI degraded from 3.8 ± 1.0 to 4.9 ± 1.5 (p-value < 0.01). The degraded GI in the VMAT plans is due to the absence of beam margin limit in SmartArc planning. Pure VMAT plans usually demonstrated better CI values than the hybrid and conformal arc plans when the number of arcs was greater than 2. The GI value was improved with increasing number of arcs in VMAT plans. For target volumes greater than 1 cc, VMAT plans demonstrated improved CI and smaller V50 and V12 than that in conformal arc plans. Better dose fall-off in normal tissue in VMAT plans is accompanied with higher dose heterogeneity in the target volume. Conclusion: VMAT and conformal-VMAT hybrid plans usually offer better target conformity. The dose fall-off in normal tissue is also better in VMAT plans when the number of arcs is greater than 3 and target volume is greater than 1 cc, but compromise the dose homogeneity in target volumes. VMAT plans are the best option for targets that are greater than 1 cc for cranial radiosurgery treatments, while for very small targets, conformal arc technique may still be the better choice based on data of dose fall-off in normal tissues. [ABSTRACT FROM AUTHOR]

Introduction: To develop a radiomic-based model to predict pathological complete response (pCR) and outcome following neoadjuvant chemoradiotherapy (NACRT) in oesophageal cancer., Methods: We analysed 68 patients with oesophageal cancer treated with NACRT followed by esophagectomy, who had staging 18F-fluorodeoxyglucose ( 18 F-FDG) positron emission tomography (PET) and computed tomography (CT) scans performed at our institution. An in-house data-chjmirocterization algorithm was used to extract 3D-radiomic features from the segmented primary disease. Prediction models were constructed and internally validated. Composite feature, F c  = α * F PET  + (1 - α) * F CT , 0 ≤ α ≤ 1, was constructed for each corresponding CT and PET feature. Loco-regional control (LRC), recurrence-free survival (RFS), metastasis-free survival (MFS) and overall survival (OS) were estimated by Kaplan-Meier analysis, and compared using log-rank test., Results: Median follow-up was 59 months. pCR was achieved in 34 (50%) patients. Five-year RFS, LRC, MFS and OS were 67.1%, 88.5%, 75.6% and 57.6%, respectively. Tumour Regression Grade (TRG) 0-1 indicative of complete response or minimal residual disease was significantly associated with improved 5-year LRC [93.7% vs 71.8%; P = 0.020; HR 0.19, 95% CI 0.04-0.85]. Four sepjmirote pCR predictive models were built for CT alone, PET alone, CT+PET and composite. CT, PET and CT+PET models had AUC 0.73 ± 0.08, 0.66 ± 0.08 and 0.77 ± 0.07, respectively. The composite model resulted in an improvement of pCR predicting power with AUC 0.87 ± 0.06. Stratifying patients with a low versus high radiomic score showed clinically relevant improvement in 5-year LRC favouring low-score group (91.1% vs. 80%, 95% CI 0.09-1.77, P = 0.2)., Conclusion: The composite CT/PET radiomics model was highly predictive of pCR following NACRT. Validation in larger data sets is warranted to determine whether the model can predict clinical outcomes., (© 2020 The Royal Australian and New Zealand College of Radiologists.)

Background and Aims:  The role of three-dimensional positron emission tomography/computed tomography (3 D PET/CT) in esophageal tumors that move with respiration and have potential for significant mucosal inflammation is unclear. The aim of this study was to determine the correlation between gross tumor volumes derived from 3 D PET/CT and endoscopically placed fiducial markers., Methods:  This was a retrospective, IRB approved analysis of 40 patients with esophageal cancer with fiducials implanted and PET/CT. The centroid of each fiducial was identified on PET/CT images. Distance between tumor volume and fiducials was measured using axial slices. Image features were extracted and tested for pathologic response predictability., Results:  The median adaptively calculated threshold value of the standardized uptake value (SUV) to define the metabolic tumor volume (MTV) border was 2.50, which corresponded to a median 23 % of the maximum SUV. The median distance between the inferior fiducial centroid and MTV was - 0.60 cm (- 3.9 to 2.7 cm). The median distance between the superior fiducial centroid and MTV was 1.25 cm (- 4.2 to 6.9 cm). There was no correlation between MTV-to-fiducial distances greater than 2 cm and the gastroenterologist who performed the fiducial implantation. Eccentricity demonstrated statistically significant correlations with pathologic response., Conclusions:  There was a stronger correlation between inferior fiducial location and MTV border compared to the superior extent. The etiology of the discordance superiorly is unclear, potentially representing benign secondary esophagitis, presence of malignant nodes, inflammation caused by technical aspects of the fiducial placement itself, or potential submucosal disease. Given the concordance inferiorly and the ability to more precisely set up the patient with daily image guidance matching to fiducials, it may be possible to minimize the planning tumor volume (PTV) margin in select patients, thereby, limiting dose to normal structures.