Serious game for radiotherapy training.

BACKGROUND: Cancer patients are often treated with radiation, therefore increasing their exposure to high energy emissions. In such cases, medical errors may be threatening or fatal, inducing the need to innovate new methods for maximum reduction of irreversible events. Training is an efficient and methodical tool to subject professionals to the real world and heavily educate them on how to perform with minimal errors. An evolving technique for this is Serious Gaming that can fulfill this purpose, especially with the rise of COVID-19 and the shift to the online world, by realistic and visual simulations built to present engaging scenarios. This paper presents the first Serious Game for Lung Cancer Radiotherapy training that embodies Biomedical Engineering principles and clinical experience to create a realistic and precise platform for coherent training. METHODS: To develop the game, thorough 3D modeling, animation, and gaming fundamentals were utilized to represent the whole clinical process of treatment, along with the scores and progress of every player. The model's goal is to output coherency and organization for students' ease of use and progress tracking, and to provide a beneficial educational experience supplementary to the users' training. It aims to also expand their knowledge and use of skills in critical cases where they must perform crucial decision-making and procedures on patients of different cases. RESULTS: At the end of this research, one of the accomplished goals consists of building a realistic model of the different equipment and tools accompanied with the radiotherapy process received by the patient on Maya 2018, including the true beam table, gantry, X-ray tube, CT Scanner, and so on. The serious game itself was then implemented on Unity Scenes with the built models to create a gamified authentic environment that incorporates the 5 main series of steps; Screening, Contouring, External Beam Planning, Plan Evaluation, Treatment, to simulate the practical workflow of an actual Oncology treatment delivery for lung cancer patients. CONCLUSION: This serious game provides an educational and empirical space for training and practice that can be used by students, trainees, and professionals to expand their knowledge and skills in the aim of reducing potential errors.

An Explainable MRI-Radiomic Quantum Neural Network to Differentiate Between Large Brain Metastases and High-Grade Glioma Using Quantum Annealing for Feature Selection.

Solitary large brain metastases (LBM) and high-grade gliomas (HGG) are sometimes hard to differentiate on MRI. The management differs significantly between these two entities, and non-invasive methods that help differentiate between them are eagerly needed to avoid potentially morbid biopsies and surgical procedures. We explore herein the performance and interpretability of an MRI-radiomics variational quantum neural network (QNN) using a quantum-annealing mutual-information (MI) feature selection approach. We retrospectively included 423 patients with HGG and LBM (> 2 cm) who had a contrast-enhanced T1-weighted (CE-T1) MRI between 2012 and 2019. After exclusion, 72 HGG and 129 LBM were kept. Tumors were manually segmented, and a 5-mm peri-tumoral ring was created. MRI images were pre-processed, and 1813 radiomic features were extracted. A set of best features based on MI was selected. MI and conditional-MI were embedded into a quadratic unconstrained binary optimization (QUBO) formulation that was mapped to an Ising-model and submitted to D'Wave's quantum annealer to solve for the best combination of 10 features. The 10 selected features were embedded into a 2-qubits QNN using PennyLane library. The model was evaluated for balanced-accuracy (bACC) and area under the receiver operating characteristic curve (ROC-AUC) on the test set. The model performance was benchmarked against two classical models: dense neural networks (DNN) and extreme gradient boosting (XGB). Shapley values were calculated to interpret sample-wise predictions on the test set. The best 10-feature combination included 6 tumor and 4 ring features. For QNN, DNN, and XGB, respectively, training ROC-AUC was 0.86, 0.95, and 0.94; test ROC-AUC was 0.76, 0.75, and 0.79; and test bACC was 0.74, 0.73, and 0.72. The two most influential features were tumor Laplacian-of-Gaussian-GLRLM-Entropy and sphericity. We developed an accurate interpretable QNN model with quantum-informed feature selection to differentiate between LBM and HGG on CE-T1 brain MRI. The model performance is comparable to state-of-the-art classical models.

Urothelial carcinoma in the era of immune checkpoint inhibitors.

Bladder cancer is the seventh most frequent cancer worldwide. The majority of patients present with nonmuscle invasive disease, while 20% of the patients are diagnosed with muscle-invasive bladder cancer. The treatment of nonmuscle invasive disease is endoscopic resection followed by intravesical adjuvant treatment for high risk patients. The standard treatment of localized muscle-invasive disease is neoadjuvant chemotherapy followed by radical cystectomy. Platinum-based chemotherapy is the first-line treatment in locally advanced or metastatic urothelial carcinoma. Immune checkpoint inhibitors have been approved for the treatment of metastatic urothelial carcinoma as second-line treatment or first-line in platinum-ineligible patients. Recently, pembrolizumab have been approved in bacillus Calmette-Guérin (BCG)-refractory nonmuscle invasive bladder cancer. This review summarizes the current evidence concerning immunotherapy in the treatment of urothelial carcinoma.

Lay abstract Bladder cancer is one of the most frequent cancers worldwide with multiple known risk factors such as cigarette smoking and occupational exposures. The majority of patients present with a superficial disease treated with endoscopic resection and intravesical treatment if needed. The localized form of bladder cancer is treated with chemotherapy followed by radical cystectomy. Metastatic bladder cancer is an incurable disease and historic treatment remains on chemotherapy. Recently, immunotherapy has been approved for the treatment of bladder cancer after progression on chemotherapy. In this article we reviewed the most recent available data concerning immunotherapy for the treatment of early-stage and advanced disease.

Colorectal cancer and brain metastases: An aggressive disease with a different response to treatment.

INTRODUCTION: Brain metastases (BM) are rare in colorectal cancer (CRC) and are associated with a dismal prognosis. This work aims to report the rate of BM in CRC patients treated in a single institution, along with survival and prognostic factors. METHODS: Medical charts for patients with histologically proven CRC were retrospectively reviewed. RESULTS: A total of 538 patients were identified, of whom 33% developed any metastatic disease and 4.4% presented BM. Lung was the most frequently associated metastatic site (in 68% of the cases). The only factor independently associated with BM development was the presence of metastatic disease at the time of initial presentation. The median duration from initial diagnosis to BM development was 38.6 months (SD 29.1 months). Median survival after BM development was 62 days (95% confidence interval [CI] 56-68). Patients diagnosed with BM within 1 year of cancer diagnosis responded significantly better to treatment than those who acquired BM later, with a median survival after BM diagnosis of 261 days versus 61 days, respectively (p = .002). Patients with BM who received antiangiogenic therapy had an improved median survival compared to those who did not (151 days vs 59 days, p = 0.02; hazard ratio for death 0.29 [95% CI 0.09-0.94]). CONCLUSION: CRC with BM is an aggressive disease resistant to standard treatment and is associated with poor outcomes. Adding antiangiogenic therapy might be of value for those patients. Patients with BM developing early in the disease course might respond better to treatment.

Image-guided adaptive brachytherapy in primary vaginal cancers: A monocentric experience.

PURPOSE: Primary vaginal cancer is a rare disease for which treatment has been modeled based on cervical cancer. We report our experience in the use of image-guided adaptive brachytherapy (IGABT) in this indication. METHODS AND MATERIALS: Patients treated for vaginal cancer with a combination of external beam radiation therapy and IGABT were identified through electronic search. The Groupe Européen de Curiethérapie-European Society for Radiotherapy and Oncology recommendations for cervical cancer have been extrapolated with the definition of two clinical target volumes (CTVs) corresponding to the residual disease after external beam radiation therapy (CTVBT), assessed from clinical and imaging findings, and the so-called CTVi, comprising the CTVBT with directional margins and at least the initial disease at diagnosis. RESULTS: Twenty-seven patients were identified. MRI was used for brachytherapy guidance in 82% of the cases. An interstitial component was used in 59% of the cases. The D90 CTVBT and D90 CTVi were 73.1 ± 12.8 Gy and 66.6 ± 6.7 Gy, respectively. After a median followup of 40.1 months, nine recurrences in 8 patients were observed of which four were local. Local relapses occurred within the CTVBT. Three-year local control and disease-free rates were 82% and 65%, respectively. At 2 years, the Grade 2-4 gastrointestinal or urinary morbidity accrual rate was 9%. Twelve patients experienced late sexual morbidity, including three patients with Grade 3 stenosis. CONCLUSION: IGABT is feasible in vaginal cancer with promising outcomes. Harmonizing the definition of CTVs is required to allow comparisons between experiences and to perform multicenter studies.

Contribution of image-guided adaptive brachytherapy to pelvic nodes treatment in locally advanced cervical cancer.

PURPOSE: With the increasing use of simultaneous integrated boost in the treatment of cervical cancer, there is a need to anticipate the brachytherapy (BT) contribution at the level of the pathologic pelvic lymph nodes. This study aimed to report the dose delivered at their level during BT. METHODS AND MATERIALS: Patients with pelvic nodal involvement and treated with a combination of chemoradiation followed by image-guided adaptive pulsed-dose-rate BT were selected. On per BT three-dimensional images, pelvic lymphadenopathies were delineated, without planning aim. For the purposes of the study, D100, D98, D90, and D50 were reviewed and converted in 2-Gy equivalent doses, using the linear quadratic model with an α/ß of 10 Gy. RESULTS: Ninety-one patients were identified, allowing evaluation at the level of 226 lymphadenopathies. The majority of them were external iliac (48%), followed by common iliac (25%), and internal iliac (16%) regions. The 2-Gy equivalent doses D98 were 4.4 ± 1.9 Gy, 5.4 ± 3.1 Gy, and 4.3 ± 2.1 Gy for the obturator, internal iliac, and external iliac, respectively, and 2.8 ± 2.5 Gy for the common iliac. The contribution to the common iliac nodes was significantly lower than the one of external and internal iliac (p < 0.001). CONCLUSIONS: BT significantly contributes to the treatment of pelvic nodes at the level of approximately 5 Gy in the internal, external, and obturator areas and 2.5 Gy in the common iliac, allowing the anticipation of nodal boost with the simultaneous integrated boost technique. However, important individual variations have been observed, and evaluation of the genuine BT contribution should be recommended.