A gradient mapping guided explainable deep neural network for extracapsular extension identification in 3D head and neck cancer computed tomography images.

BACKGROUND: Diagnosis and treatment management for head and neck squamous cell carcinoma (HNSCC) is guided by routine diagnostic head and neck computed tomography (CT) scans to identify tumor and lymph node features. The extracapsular extension (ECE) is a strong predictor of patients' survival outcomes with HNSCC. It is essential to detect the occurrence of ECE as it changes staging and treatment planning for patients. Current clinical ECE detection relies on visual identification and pathologic confirmation conducted by clinicians. However, manual annotation of the lymph node region is a required data preprocessing step in most of the current machine learning-based ECE diagnosis studies. PURPOSE: In this paper, we propose a Gradient Mapping Guided Explainable Network (GMGENet) framework to perform ECE identification automatically without requiring annotated lymph node region information. METHODS: The gradient-weighted class activation mapping (Grad-CAM) technique is applied to guide the deep learning algorithm to focus on the regions that are highly related to ECE. The proposed framework includes an extractor and a classifier. In a joint training process, informative volumes of interest (VOIs) are extracted by the extractor without labeled lymph node region information, and the classifier learns the pattern to classify the extracted VOIs into ECE positive and negative. RESULTS: In evaluation, the proposed methods are well-trained and tested using cross-validation. GMGENet achieved test accuracy and area under the curve (AUC) of 92.2% and 89.3%, respectively. GMGENetV2 achieved 90.3% accuracy and 91.7% AUC in the test. The results were compared with different existing models and further confirmed and explained by generating ECE probability heatmaps via a Grad-CAM technique. The presence or absence of ECE has been analyzed and correlated with ground truth histopathological findings. CONCLUSIONS: The proposed deep network can learn meaningful patterns to identify ECE without providing lymph node contours. The introduced ECE heatmaps will contribute to the clinical implementations of the proposed model and reveal unknown features to radiologists. The outcome of this study is expected to promote the implementation of explainable artificial intelligence-assiste ECE detection.

Building Better Patient Care in Mississippi Radiation Oncology: Why Mississippi Needs a Collaborative Quality Initiative.

OBJECTIVES: Cancer is an insidious and devastating disease that affects many people. Progress in mortality rate has not been realized universally across the United States, and challenges remain in how to best make up the ground that has been lost in these areas, one of which is Mississippi. Radiation therapy is a significant contributor to cancer control rates and certain challenges exist specifically regarding this treatment modality. METHODS: The challenges of radiation oncology in Mississippi have been reviewed and discussed, with the proposal of a potential collaboration between clinical practitioners and payors to provide optimal and cost-effective radiation therapy to patients in Mississippi. RESULTS: A similar model to that proposed has been reviewed and evaluated. This model is discussed based on its potential validity and usefulness in Mississippi. CONCLUSIONS: Significant barriers exist in the state of Mississippi to patients receiving a consistent standard of care, regardless of their location and socioeconomic status. A collaborative quality initiative has been shown to be a boon to this endeavor elsewhere and stands to have a similar impact in Mississippi.

Strategic Reduction of Package Time in Head and Neck Cancer.

Purpose: Total package time, or the time from diagnosis to completion of definitive treatment, has been associated with outcomes for a variety of tumor sites, but especially to head and neck (HN) cancer. Patients with HN cancer often undergo a complex diagnosis and treatment process involving multiple disciplines both within and outside of oncology. This complexity can lead to longer package times, and each involved discipline has the responsibility to maintain an efficient and effective process. Strategic intervention to improve package time must involve not only new technology or tools, but also "soft" components such as accountability, motivation, and leadership. This combination is necessary to truly optimize radiation therapy for HN cancer, leading to shorter total package times for these patients. Methods and Materials: Two interventions were strategically executed to improve radiation therapy workflow: upgrade of the treatment planning system and implementation of an automated patient management and accountability system. The radiation therapy-related timelines of 112 patients with HN cancer treated over 2 years were reviewed, and the average time differences were compared between the patient populations before and after the strategic interventions. Results: Purely upgrading the treatment planning system did not show significant improvements, but when combined with the patient management system, significant improvement in radiation-related package time can be noted for every time point. The overall reduction of radiation-related package time was statistically significant at 22.85 days (P = .002). Conclusions: On face value, the patient management system could be credited as responsible for the improvement, but on qualitative analysis, it is noted that the new system is only a tool that can be ignored or underused. Owing to the addition of important "soft" components such as accountability, motivation, and leadership, the patient management system was optimized and implemented in such a manner as to have the desired effect.

Local Treatment of the Primary Tumor for Patients With Metastatic Cancer (PRIME-TX): A Meta-Analysis.

PURPOSE: Local treatment of the primary tumor for patients with metastases is controversial, and prospective data across many disease sites have conflicting conclusions regarding benefits. METHODS AND MATERIALS: A comprehensive search was conducted in PubMed/MEDLINE including randomized controlled trials (RCTs) published in the past 50 years. Inclusion criteria were multi-institutional RCTs of patients with metastatic disease receiving systemic therapy randomized to addition of local treatment to the primary tumor. Two primary outcome measures, overall survival (OS) and progression-free survival (PFS), were quantitatively assessed using random effects, and meta-analyses were conducted using the inverse variance method for pooling. Secondary endpoints were qualitatively assessed and included toxicity and patient-reported quality of life. Exploratory analyses were performed by treatment type and volume of disease. RESULTS: Eleven studies comprising 4952 patients were included (1558 patients received radiation therapy and 913 patients received surgery as primary tumor treatment). OS and PFS were not significantly improved from treatment of the primary (OS: hazard ratio [HR], 0.91; 95% confidence interval [CI], 0.80-1.05; PFS: HR, 0.88; 95% CI, 0.72-1.07). Assessment of primary local treatment modality demonstrated a significant difference in summary effect size on PFS between trials using surgery (HR, 1.15; 95% CI, 0.99-1.33) compared with radiation therapy (HR, 0.73; 95% CI, 0.56-0.96) as the local treatment modality (P = .005). In low metastatic burden patients, radiation therapy was associated with significantly improved OS (HR, 0.67; 95% CI, 0.52-0.85), but surgery was not associated with improved OS compared with no local treatment (HR, 1.12; 95% CI, 0.94-1.34). CONCLUSIONS: In RCTs conducted to date enrolling a variety of cancer types with variable metastatic burden, there is no consistent improvement in PFS or OS from the addition of local therapy to the primary tumor in unselected patients with metastatic disease. Carefully selected patients may derive oncologic benefit and should be discussed in tumor boards. Future prospective studies should aim to further optimize patient selection and the optimal systemic and local therapy treatment types.

Radiation Fractionation Schedules Published During the COVID-19 Pandemic: A Systematic Review of the Quality of Evidence and Recommendations for Future Development.

PURPOSE: Numerous publications during the COVID-19 pandemic recommended the use of hypofractionated radiation therapy. This project assessed aggregate changes in the quality of the evidence supporting these schedules to establish a comprehensive evidence base for future reference and highlight aspects for future study. METHODS AND MATERIALS: Based on a systematic review of published recommendations related to dose fractionation during the COVID-19 pandemic, 20 expert panelists assigned to 14 disease groups named and graded the highest quality of evidence schedule(s) used routinely for each condition and also graded all COVID-era recommended schedules. The American Society for Radiation Oncology quality of evidence criteria were used to rank the schedules. Process-related statistics and changes in distributions of quality ratings of the highest-rated versus recommended COVID-19 era schedules were described by disease groups and for specific clinical scenarios. RESULTS: From January to May 2020 there were 54 relevant publications, including 233 recommended COVID-19-adapted dose fractionations. For site-specific curative and site-specific palliative schedules, there was a significant shift from established higher-quality evidence to lower-quality evidence and expert opinions for the recommended schedules (P = .022 and P < .001, respectively). For curative-intent schedules, the distribution of quality scores was essentially reversed (highest levels of evidence "pre-COVID" vs "in-COVID": high quality, 51.4% vs 4.8%; expert opinion, 5.6% vs 49.3%), although there was variation in the magnitude of shifts between disease sites and among specific indications. CONCLUSIONS: A large number of publications recommended hypofractionated radiation therapy schedules across numerous major disease sites during the COVID-19 pandemic, which were supported by a lower quality of evidence than the highest-quality routinely used dose fractionation schedules. This work provides an evidence-based assessment of these potentially practice-changing recommendations and informs individualized decision-making and counseling of patients. These data could also be used to support radiation therapy practices in the event of second waves or surges of the pandemic in new regions of the world.

Use of Amifostine for Cytoprotection during Radiation Therapy: A Review.

BACKGROUND: Radiation therapy is a cornerstone of the therapeutic modalities used in modern oncology. However, it is sometimes limited in its ability to achieve optimal tumor control by radiation-induced normal tissue toxicity. In delivering radiation therapy, a balance must be achieved between maximizing the dose to the tumor and minimizing any injury to the normal tissues. Amifostine was the first Food and Drug Administration (FDA)-approved clinical radiation protector intended to reduce the impact of radiation on normal tissue, lessening its toxicity and potentially allowing for increased tumor dose/control. Despite being FDA-approved almost 20 years ago, Amifostine has yet to achieve widespread clinical use. SUMMARY: A thorough review of Amifostine's development, mechanism of action, and current clinical status were conducted. A brief history of Amifostine is given, from its development at Walter Reid Institute of Research to its approval for clinical use. The mechanism of action of Amifostine is explored. The results of a complete literature review of all prospective randomized trials to date involving the use of Amifostine in radiation therapy are presented. The results are arranged by treatment site and salient findings discussed. Side effects and complications to consider in using Amifostine are reviewed. Key Messages: Amifostine has been explored as a radiation protectant in most radiation treatment sites. Studies have demonstrated efficacy of Amifostine in all treatment sites reviewed, but results are heterogeneous. The heterogeneity of studies looking at Amifostine as a clinical radiation protectant has precluded a definitive answer on its efficacy. Complicating its clinical use is its toxicity and delivery requirements. Amifostine has largely fallen out of use with the advent of intensity modulated radiation therapy (IMRT). However, side effects with IMRT remain a challenge and concern. The use of Amifostine in the IMRT era has been poorly explored and is worthy of future study.