Auto-contouring may reduce workload, interobserver variation, and time associated with manual contouring of organs at risk. Manual contouring remains the standard due in part to uncertainty around the time and workload savings after accounting for the review and editing of auto-contours. This preliminary study compares a standard manual contouring workflow with 2 auto-contouring workflows (atlas and deep learning) for contouring the bladder and rectum in patients with prostate cancer. Methods and Materials: Three contouring workflows were defined based on the initial contour-generation method including manual (MAN), atlas-based auto-contour (ATLAS), and deep-learning auto-contour (DEEP). For each workflow, initial contour generation was retrospectively performed on 15 patients with prostate cancer. Then, radiation oncologists (ROs) edited each contour while blinded to the manner in which the initial contour was generated. Workflows were compared by time (both in initial contour generation and in RO editing), contour similarity, and dosimetric evaluation. Results: Mean durations for initial contour generation were 10.9 min, 1.4 min, and 1.2 min for MAN, DEEP, and ATLAS, respectively. Initial DEEP contours were more geometrically similar to initial MAN contours. Mean durations of the RO editing steps for MAN, DEEP, and ATLAS contours were 4.1 min, 4.7 min, and 10.2 min, respectively. The geometric extent of RO edits was consistently larger for ATLAS contours compared with MAN and DEEP. No differences in clinically relevant dose-volume metrics were observed between workflows. Conclusion: Auto-contouring software affords time savings for initial contour generation; however, it is important to also quantify workload changes at the RO editing step. Using deep-learning auto-contouring for bladder and rectum contour generation reduced contouring time without negatively affecting RO editing times, contour geometry, or clinically relevant doseevolume metrics.

a b s t r a c tPurpose: The aims of this study are to evaluate the stability of radiomic features from Apparent Diffusion Coefficient (ADC) maps of cervical cancer with respect to: (1) reproducibility in inter-observer delineation, and (2) image pre-processing (normalization/quantization) prior to feature extraction. Materials and methods: Two observers manually delineated the tumor on ADC maps derived from pretreatment diffusion-weighted Magnetic Resonance imaging of 81 patients with FIGO stage IB-IVA cervical cancer. First-order, shape, and texture features were extracted from the original and filtered images considering 5 different normalizations (four taken from the available literature, and one based on urine ADC) and two different quantization techniques (fixed-bin widths from 0.05 to 25, and fixed-bin count). Stability of radiomic features was assessed using intraclass correlation coefficient (ICC): poor (ICC < 0.75); good (0.75 ICC 0.89), and excellent (ICC ! 0.90). Dependencies of the features with tumor volume were assessed using Spearman's correlation coefficient (q). Results: The approach using urine-normalized values together with a smaller bin width (0.05) was the most reproducible (428/552, 78% features with ICC ! 0.75); the fixed-bin count approach was the least (215/552, 39% with ICC ! 0.75). Without normalization, using a fixed bin width of 25, 348/552 (63%) of features had an ICC ! 0.75. Overall, 26% (range 25-30%) of the features were volume-dependent (q ! 0.6). None of the volume-independent shape features were found to be reproducible. Conclusion: Applying normalization prior to features extraction increases the reproducibility of ADCbased radiomics features. When normalization is applied, a fixed-bin width approach with smaller widths is suggested. Ó 2019 The Author(s). Published by Elsevier B.V. Radiotherapy and Oncology 143 (2020) 88-94 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Cervical cancer is the fourth most frequent cancer in women, with an estimated 570,000 new cases in 2018, representing 6.6% of all female cancers worldwide. Cervical cancer still represents a significant burden for middle-and low-income countries [1]. Standard treatment for locally advanced (stage IB2-IVA) cervical cancer is concurrent chemoradiation.Computed Tomography (CT) and Magnetic Resonance (MR) are the standard imaging modalities for cervical cancer staging and evaluation of treatment response. Through appropriate choice of pulse sequences MR imaging provides greater soft tissue contrast than CT and enables assessment of physiological parameters and biochemical function. Diffusion-weighted imaging (DWI) in MR enables measurement of water diffusivity via generation of Apparent Diffusion Coefficient (ADC) maps, and ADC is an established biomarker of tumor cell density and related changes posttherapy [2]. DWI is increasing acquired in addition to T2weighted MRI to detect cervical tumor [3], and pre-treatment tumor ADC has been shown to be p...

Correspondence to Adam Gladwish, adam.gladwish@utoronto.ca SUMMARY Locally advanced lung cancer, if untreated, typically progresses although the rapidity of progression may vary. The authors report the case of an 84-year-old woman who presented with radiologically progressive, biopsy proven stage IIIB (T2N3) squamous cell carcinoma in the left lower lobe of the lung. Her disease was too advanced for curative treatment and in view of the lack of symptoms to palliate, she received no anticancer treatment. In follow-up, her tumour was noted to spontaneously regress in size on serial chest x-rays. Eight months after biopsy, restaging CT showed complete resolution of the enlarged biopsy proven mediastinal and hilar lymph nodes and signifi cant regression of the primary tumour. She remains clinically well.

The volumetric ADC95 may be a useful imaging metric to predict treatment failure in patients with locally advanced cervical cancer treated with chemo- and radiation therapy.

Respiratory gating is emerging as a tool to limit the effect of motion for liver and lung tumors. In order to study the impact of target motion and gated intensity modulated radiation therapy (IMRT) delivery, a computer program was developed to simulate segmental IMRT delivery to a moving phantom. Two distinct plans were delivered to a rigid-motion phantom with a film insert in place under four conditions: static, sinusoidal motion, gated sinusoidal motion with a duty cycle of 25% and gated sinusoidal motion with duty cycle of 50% under motion conditions of a typical patient (A = 1 cm, T = 4 s). The MLC controller log files and gating log files were retained to perform a retrospective Monte Carlo dose calculation of the plans. Comparison of the 2D planar dose distributions between simulation and measurement demonstrated that our technique had at least 94% of the points passing gamma criteria of 3% for dose difference and 3 mm as the distance to agreement. This note demonstrates that the use of dynamic multi-leaf collimator and respiratory monitoring system log files together with a fast Monte Carlo dose calculation algorithm is an accurate and efficient way to study the dosimetric effect of motion for gated or non-gated IMRT delivery on a rigidly-moving body.

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BackgroundEarly and accurate prediction of response to cancer treatment through imaging criteria is particularly important in rapidly progressive malignancies such as Glioblastoma Multiforme (GBM). We sought to assess the predictive value of structural imaging response criteria one month after concurrent chemotherapy and radiotherapy (RT) in patients with GBM.MethodsThirty patients were enrolled from 2005 to 2007 (median follow-up 22 months). Tumor volumes were delineated at the boundary of abnormal contrast enhancement on T1-weighted images prior to and 1 month after RT. Clinical Progression [CP] occurred when clinical and/or radiological events led to a change in chemotherapy management. Early Radiologic Progression [ERP] was defined as the qualitative interpretation of radiological progression one month post-RT. Patients with ERP were determined pseudoprogressors if clinically stable for ≥6 months. Receiver-operator characteristics were calculated for RECIST and MacDonald criteria, along with alternative thresholds against 1 year CP-free survival and 2 year overall survival (OS).Results13 patients (52%) were found to have ERP, of whom 5 (38.5%) were pseudoprogressors. Patients with ERP had a lower median OS (11.2 mo) than those without (not reached) (p < 0.001). True progressors fared worse than pseudoprogressors (median survival 7.2 mo vs. 19.0 mo, p < 0.001). Volume thresholds performed slightly better compared to area and diameter thresholds in ROC analysis. Responses of > 25% in volume or > 15% in area were most predictive of OS.ConclusionsWe show that while a subjective interpretation of early radiological progression from baseline is generally associated with poor outcome, true progressors cannot be distinguished from pseudoprogressors. In contrast, the magnitude of early imaging volumetric response may be a predictive and quantitative metric of favorable outcome.

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