Self-configuring nnU-Net for automatic delineation of the organs at risk and target in high-dose rate cervical brachytherapy, a low/middle-income country's experience.

BACKGROUND: The high-dose rate (HDR) brachytherapy treatment planning workflow for cervical cancer is a labor-intensive, time-consuming, and expertise-driven process. These issues are amplified in low/middle-income countries with large deficits in experienced healthcare professionals. Automation has the ability to substantially reduce bottlenecks in the planning process but often require a high level of expertise to develop. PURPOSE: To implement the out of the box self-configuring nnU-Net package for the auto-segmentation of the organs at risk (OARs) and high-risk CTV (HR CTV) for Ring-Tandem (R-T) HDR cervical brachytherapy treatment planning. METHODS: The computed tomography (CT) scans of 100 previously treated patients were used to train and test three different nnU-Net configurations (2D, 3DFR, and 3DCasc). The performance of the models was evaluated by calculating the Sørensen-dice similarity coefficient, Hausdorff distance (HD), 95th percentile Hausdorff distance, mean surface distance (MSD), and precision score for 20 test patients. The dosimetric accuracy between the manual and predicted contours was assessed by looking at the various dose volume histogram (DVH) parameters and volume differences. Three different radiation oncologists (ROs) scored the predicted bladder, rectum, and HR CTV contours generated by the best performing model. The manual contouring, prediction, and editing times were recorded. RESULTS: The mean DSC, HD, HD95, MSD and precision scores for our best performing model (3DFR) were 0.92/7.5 mm/3.0 mm/ 0.8 mm/0.91 for the bladder, 0.84/13.8 mm/5.3 mm/1.4 mm/0.84 for the rectum, and 0.81/8.5 mm/6.0 mm/2.2 mm/0.80 for the HR CTV. Mean dose differences (D2cc/90% ) and volume differences were 0.08 Gy/1.3 cm3 for the bladder, 0.02 Gy/0.7 cm3 for the rectum, and 0.33 Gy/1.5 cm3 for the HR CTV. On average, 65% of the generated contours were clinically acceptable, 33% requiring minor edits, 2% required major edits, and no contours were rejected. Average manual contouring time was 14.0 min, while the average prediction and editing times were 1.6 and 2.1 min, respectively. CONCLUSION: Our best performing model (3DFR) provided fast accurate auto generated OARs and HR CTV contours with a large clinical acceptance rate.

Customizable landmark-based field aperture design for automated whole-brain radiotherapy treatment planning.

PURPOSE: To develop and evaluate an automated whole-brain radiotherapy (WBRT) treatment planning pipeline with a deep learning-based auto-contouring and customizable landmark-based field aperture design. METHODS: The pipeline consisted of the following steps: (1) Auto-contour normal structures on computed tomography scans and digitally reconstructed radiographs using deep learning techniques, (2) locate the landmark structures using the beam's-eye-view, (3) generate field apertures based on eight different landmark rules addressing different clinical purposes and physician preferences. Two parallel approaches for generating field apertures were developed for quality control. The performance of the generated field shapes and dose distributions were compared with the original clinical plans. The clinical acceptability of the plans was assessed by five radiation oncologists from four hospitals. RESULTS: The performance of the generated field apertures was evaluated by the Hausdorff distance (HD) and mean surface distance (MSD) from 182 patients' field apertures used in the clinic. The average HD and MSD for the generated field apertures were 16 ± 7 and 7 ± 3 mm for the first approach, respectively, and 17 ± 7 and 7 ± 3 mm, respectively, for the second approach. The differences regarding HD and MSD between the first and the second approaches were 1 ± 2 and 1 ± 3 mm, respectively. A clinical review of the field aperture design, conducted using 30 patients, achieved a 100% acceptance rate for both the first and second approaches, and the plan review achieved a 100% acceptance rate for the first approach and a 93% acceptance rate for the second approach. The average acceptance rate for meeting lens dosimetric recommendations was 80% (left lens) and 77% (right lens) for the first approach, and 70% (both left and right lenses) for the second approach, compared with 50% (left lens) and 53% (right lens) for the clinical plans. CONCLUSION: This study provided an automated pipeline with two field aperture generation approaches to automatically generate WBRT treatment plans. Both quantitative and qualitative evaluations demonstrated that our novel pipeline was comparable with the original clinical plans.

Identifying the optimal deep learning architecture and parameters for automatic beam aperture definition in 3D radiotherapy.

PURPOSE: Two-dimensional radiotherapy is often used to treat cervical cancer in low- and middle-income countries, but treatment planning can be challenging and time-consuming. Neural networks offer the potential to greatly decrease planning time through automation, but the impact of the wide range of hyperparameters to be set during training on model accuracy has not been exhaustively investigated. In the current study, we evaluated the effect of several convolutional neural network architectures and hyperparameters on 2D radiotherapy treatment field delineation. METHODS: Six commonly used deep learning architectures were trained to delineate four-field box apertures on digitally reconstructed radiographs for cervical cancer radiotherapy. A comprehensive search of optimal hyperparameters for all models was conducted by varying the initial learning rate, image normalization methods, and (when appropriate) convolutional kernel size, the number of learnable parameters via network depth and the number of feature maps per convolution, and nonlinear activation functions. This yielded over 1700 unique models, which were all trained until performance converged and then tested on a separate dataset. RESULTS: Of all hyperparameters, the choice of initial learning rate was most consistently significant for improved performance on the test set, with all top-performing models using learning rates of 0.0001. The optimal image normalization was not consistent across architectures. High overlap (mean Dice similarity coefficient = 0.98) and surface distance agreement (mean surface distance < 2 mm) were achieved between the treatment field apertures for all architectures using the identified best hyperparameters. Overlap Dice similarity coefficient (DSC) and distance metrics (mean surface distance and Hausdorff distance) indicated that DeepLabv3+ and D-LinkNet architectures were least sensitive to initial hyperparameter selection. CONCLUSION: DeepLabv3+ and D-LinkNet are most robust to initial hyperparameter selection. Learning rate, nonlinear activation function, and kernel size are also important hyperparameters for improving performance.

Cancer in sub-Saharan Africa: a Lancet Oncology Commission.

In sub-Saharan Africa (SSA), urgent action is needed to curb a growing crisis in cancer incidence and mortality. Without rapid interventions, data estimates show a major increase in cancer mortality from 520 348 in 2020 to about 1 million deaths per year by 2030. Here, we detail the state of cancer in SSA, recommend key actions on the basis of analysis, and highlight case studies and successful models that can be emulated, adapted, or improved across the region to reduce the growing cancer crises. Recommended actions begin with the need to develop or update national cancer control plans in each country. Plans must include childhood cancer plans, managing comorbidities such as HIV and malnutrition, a reliable and predictable supply of medication, and the provision of psychosocial, supportive, and palliative care. Plans should also engage traditional, complementary, and alternative medical practices employed by more than 80% of SSA populations and pathways to reduce missed diagnoses and late referrals. More substantial investment is needed in developing cancer registries and cancer diagnostics for core cancer tests. We show that investments in, and increased adoption of, some approaches used during the COVID-19 pandemic, such as hypofractionated radiotherapy and telehealth, can substantially increase access to cancer care in Africa, accelerate cancer prevention and control efforts, increase survival, and save billions of US dollars over the next decade. The involvement of African First Ladies in cancer prevention efforts represents one practical approach that should be amplified across SSA. Moreover, investments in workforce training are crucial to prevent millions of avoidable deaths by 2030. We present a framework that can be used to strategically plan cancer research enhancement in SSA, with investments in research that can produce a return on investment and help drive policy and effective collaborations. Expansion of universal health coverage to incorporate cancer into essential benefits packages is also vital. Implementation of the recommended actions in this Commission will be crucial for reducing the growing cancer crises in SSA and achieving political commitments to the UN Sustainable Development Goals to reduce premature mortality from non-communicable diseases by a third by 2030.

Automation of radiation treatment planning for rectal cancer.

PURPOSE: To develop an automated workflow for rectal cancer three-dimensional conformal radiotherapy (3DCRT) treatment planning that combines deep learning (DL) aperture predictions and forward-planning algorithms. METHODS: We designed an algorithm to automate the clinical workflow for 3DCRT planning with field aperture creations and field-in-field (FIF) planning. DL models (DeepLabV3+ architecture) were trained, validated, and tested on 555 patients to automatically generate aperture shapes for primary (posterior-anterior [PA] and opposed laterals) and boost fields. Network inputs were digitally reconstructed radiographs, gross tumor volume (GTV), and nodal GTV. A physician scored each aperture for 20 patients on a 5-point scale (>3 is acceptable). A planning algorithm was then developed to create a homogeneous dose using a combination of wedges and subfields. The algorithm iteratively identifies a hotspot volume, creates a subfield, calculates dose, and optimizes beam weight all without user intervention. The algorithm was tested on 20 patients using clinical apertures with varying wedge angles and definitions of hotspots, and the resulting plans were scored by a physician. The end-to-end workflow was tested and scored by a physician on another 39 patients. RESULTS: The predicted apertures had Dice scores of 0.95, 0.94, and 0.90 for PA, laterals, and boost fields, respectively. Overall, 100%, 95%, and 87.5% of the PA, laterals, and boost apertures were scored as clinically acceptable, respectively. At least one auto-plan was clinically acceptable for all patients. Wedged and non-wedged plans were clinically acceptable for 85% and 50% of patients, respectively. The hotspot dose percentage was reduced from 121% (σ = 14%) to 109% (σ = 5%) of prescription dose for all plans. The integrated end-to-end workflow of automatically generated apertures and optimized FIF planning gave clinically acceptable plans for 38/39 (97%) of patients. CONCLUSION: We have successfully automated the clinical workflow for generating radiotherapy plans for rectal cancer for our institution.

Automatic contouring QA method using a deep learning-based autocontouring system.

PURPOSE: To determine the most accurate similarity metric when using an independent system to verify automatically generated contours. METHODS: A reference autocontouring system (primary system to create clinical contours) and a verification autocontouring system (secondary system to test the primary contours) were used to generate a pair of 6 female pelvic structures (UteroCervix [uterus + cervix], CTVn [nodal clinical target volume (CTV)], PAN [para-aortic lymph nodes], bladder, rectum, and kidneys) on 49 CT scans from our institution and 38 from other institutions. Additionally, clinically acceptable and unacceptable contours were manually generated using the 49 internal CT scans. Eleven similarity metrics (volumetric Dice similarity coefficient (DSC), Hausdorff distance, 95% Hausdorff distance, mean surface distance, and surface DSC with tolerances from 1 to 10 mm) were calculated between the reference and the verification autocontours, and between the manually generated and the verification autocontours. A support vector machine (SVM) was used to determine the threshold that separates clinically acceptable and unacceptable contours for each structure. The 11 metrics were investigated individually and in certain combinations. Linear, radial basis function, sigmoid, and polynomial kernels were tested using the combinations of metrics as inputs for the SVM. RESULTS: The highest contouring error detection accuracies were 0.91 for the UteroCervix, 0.90 for the CTVn, 0.89 for the PAN, 0.92 for the bladder, 0.95 for the rectum, and 0.97 for the kidneys and were achieved using surface DSCs with a thickness of 1, 2, or 3 mm. The linear kernel was the most accurate and consistent when a combination of metrics was used as an input for the SVM. However, the best model accuracy from the combinations of metrics was not better than the best model accuracy from a surface DSC as an input. CONCLUSIONS: We distinguished clinically acceptable contours from clinically unacceptable contours with an accuracy higher than 0.9 for the targets and critical structures in patients with cervical cancer; the most accurate similarity metric was surface DSC with a thickness of 1, 2, or 3 mm.

HIV status does not have an impact on positron emission tomography-computed tomography (PET-CT) findings or radiotherapy treatment recommendations in patients with locally advanced cervical cancer.

INTRODUCTION: Positron emission tomography-computed tomography (PET-CT) imaging is commonly used to identify nodal involvement in locally advanced cervical carcinoma, but its appropriateness for that purpose among HIV-positive patients has rarely been studied. We analyzed PET-CT findings and subsequent treatment prescribed in patients with locally advanced cervical carcinoma in Cape Town, South Africa. METHODS: We identified a cohort of consecutive cervical carcinoma patients International Federation of Gynecology and Obstetrics (FIGO) stage IIB to IIIB at our cancer center who underwent a planning 18-fluorodeoxyglucose (18FDG) PET-CT scan from January 2015 through December 2018. Demographics, PET-CT findings, and subsequent treatment prescribed were recorded. Patients were selected for PET-CT only if they had no signs of distant disease on staging chest X-ray or abdominal ultrasound; were deemed suitable for radical chemoradiation by the multi-disciplinary team; and had normal renal function. HIV-positive patients ideally had to have been established on continuous antiviral therapy for more than 3 months and to have a CD4 cell count above 150 cells/µL. Small cell and neuroendocrine carcinoma cases were excluded from the study. Differences in demographic and clinical measures between HIV-positive and HIV-negative patients were evaluated by means of t-tests for continuous variables and χ2 tests for categorical variables. RESULTS: Over a 4 year period, 278 patients-192 HIV-negative (69.1%) and 86 HIV-positive (30.9%)-met the inclusion criteria. HIV-positive patients had a median CD4 count of 475 cells/µL (IQR 307-612 cells/µL). More than 80% of patients had pelvic nodal involvement, and more than 40% had uptake in common iliac and/or para-aortic nodes. Nodal involvement was not associated with HIV status. Fifty-four patients (19.4%) had at least one site of distant metastatic disease. Overall, 235 patients (84.5%) were upstaged following PET-CT staging scan. Upstaging was not associated with HIV status (HIV-negative 83.9% vs HIV-positive 87.2%; p=0.47). Ten patients who did not return for radiotherapy were excluded from the analysis. Following their PET-CT scan, treatment intent changed for 124 patients (46.3%): 53.6% of HIV-positive patients and 42.9% of HIV-negative patients (p=0.11). CONCLUSION: We found no differences between HIV-positive or HIV-negative patients in nodal involvement or occult metastases, and PET-CT imaging did not lead to, or justify, treatment differences between the two groups. Future studies will evaluate survival and correlation of upstaging with outcome.

Five-year overall survival following chemoradiation among HIV-positive and HIV-negative patients with locally advanced cervical carcinoma in a South African cohort.

OBJECTIVES: In South Africa, where HIV prevalence among adults is 18.9%, cervical carcinoma is the second most common malignancy in women. However, oncology services are considerably more accessible in South Africa than in many neighbouring countries. This study reports five-year overall survival in a cohort of HIV-positive and -negative cervix carcinoma patients undergoing primary radiotherapy at a single institution in South Africa. METHODS: Prospective cohort study of all locally advanced cervix carcinoma patients referred for radiotherapy (EBRT) from July 2007 to November 2011. Overall survival (OS) was the primary end-point. RESULTS: A total of 492 patients commenced treatment with radical intent, including 71 HIV-positive patients (14.4%) and 421 HIV-negative patients (85.6%). Of the 433 who were prescribed standard fractionation EBRT, 384 were prescribed concurrent platinum-based chemotherapy (88.7%). Fewer HIV-positive than HIV-negative patients (58.5% vs. 76.1%; p = 0.007) completed ≥4 cycles. The OS of HIV-negative patients was 49.5% (95%CI; 44.6%-54.4%) at 5 years. The OS of HIV-positive patients was significantly lower, 35.9% (95% CI; 23.9%-48.0%) at 5 years (p = 0.002). In our Cox models, factors affecting outcome were HIV infection, stage IIIB disease, presence of hydronephrosis, and delivery of concurrent chemotherapy. CONCLUSION: In our large cohort, HIV-positive patients had poorer survival than HIV-negative patients, however nearly 40% survived 5 years, justifying provision of the best standard of care to HIV-positive patients with cervical carcinoma.

Evaluating the Role of F-18 Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Scanning in the Staging of Patients With Stage IIIB Cervical Carcinoma and the Impact on Treatment Decisions.

OBJECTIVE: FIGO (International Federation of Gynaecology and Obstetrics) staging is currently the most widely used clinical staging system for cervical cancer; however, this staging system has many shortcomings. One of these shortcomings is that lymph nodal status, specifically the para-aortic lymph nodal status, does not get taken into account. It is known that metabolic changes occur before changes are seen on anatomical imaging, and it is therefore possible to detect metastases earlier with the help of fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT). We hypothesized that by including an FDG PET/CT study as part of the staging investigations in patients with invasive cervical cancer, pretreatment staging would improve and management would change in a significant proportion of patients. METHODS/MATERIALS: Patients diagnosed with FIGO stage IIIB cervical cancer from September 2010 to December 2015 received an FDG PET/CT study as part of their staging workup. A whole-body FDG PET/CT was performed before initiation of treatment, and the results were interpreted by experienced nuclear medicine physicians and radiologists. We determined the percentage of patients in whom PET/CT changed the stage and/or altered management of the patient. RESULTS: There were 95 patients diagnosed with stage IIIB cervix cancer during the study period who received an FDG PET/CT as part of their staging workup. Eighty-eight patients were included in the final sample. Positron emission tomography/CT affected the management of 40% of patients, with 19% requiring a change in the radiation field due to identification of para-aortic nodal involvement and 21% upstaged to stage IVB. CONCLUSIONS: Fluorodeoxyglucose PET/CT is useful in assessing distant disease and evaluating nodal involvement in patients with invasive cervical cancer. Additional findings on the PET/CT that were missed by conventional imaging and clinical examination caused treatment change in a significant proportion of patients.

HIV Status and Acute Hematologic Toxicity Among Patients With Cervix Cancer Undergoing Radical Chemoradiation.

INTRODUCTION: Women infected with the human immunodeficiency virus (HIV) have a higher risk of developing cervix carcinoma than do other women who are thought to be more vulnerable to acute toxicities during chemoradiation. We compared HIV-positive/HIV-negative patients with cervix carcinoma at a single institution with respect to cancer treatment toxicities. METHODS AND MATERIALS: Among patients with stage Ib1-IIIb invasive cervical carcinoma who received radiation or chemoradiation with curative intent, we evaluated demographic and clinical characteristics of HIV-positive and HIV-negative patients. Treatment regimens were documented and toxicities scored as per Radiation Therapy Oncology Group guidelines. We developed logistic regression models for the associations of grade 3/4 toxicities with HIV status. RESULTS: Complete data were available on 213 patients, including 36 (16.8%) who were HIV positive. More than 85% of both HIV-positive and HIV-negative patients received a minimum of 68-Gy equivalent dose in 2-Gy-fraction external beam and high-dose-rate brachytherapy. More HIV-positive than HIV-negative patients were prescribed radiation alone (38.9% vs 24.29%, P = 0.01), experienced at least 1 grade 3/4 toxicity (38.9% vs 26.6%), or developed grade 3/4 leucopenia (30.6% vs 10.2%, P = 0.003).In a multivariable model, patients who developed a grade 3/4 toxicity were 4 times as likely to have received chemotherapy (odds ratio, 4.41 [95% confidence interval, 1.76-11.1]; P = 0.023) and twice as likely to be HIV positive (odds ratio 2.16 [95% confidence interval, 0.98-4.8]; P = 0.05) as women who did not experience such toxicities. CONCLUSIONS: HIV-positive patients with cervical carcinoma received adequate radiotherapy but were less likely than HIV-negative patients to complete chemotherapy. Few HIV-positive or HIV-negative patients who received radiotherapy without chemotherapy experienced grade 3/4 toxicity. However, among patients who received chemotherapy, those who were HIV positive were more likely than others to experience hematologic toxicity.

Artificial Intelligence-Based Radiotherapy Contouring and Planning to Improve Global Access to Cancer Care.

PURPOSE: Increased automation has been identified as one approach to improving global cancer care. The Radiation Planning Assistant (RPA) is a web-based tool offering automated radiotherapy (RT) contouring and planning to low-resource clinics. In this study, the RPA workflow and clinical acceptability were assessed by physicians around the world. METHODS: The RPA output for 75 cases was reviewed by at least three physicians; 31 radiation oncologists at 16 institutions in six countries on five continents reviewed RPA contours and plans for clinical acceptability using a 5-point Likert scale. RESULTS: For cervical cancer, RPA plans using bony landmarks were scored as usable as-is in 81% (with minor edits 93%); using soft tissue contours, plans were scored as usable as-is in 79% (with minor edits 96%). For postmastectomy breast cancer, RPA plans were scored as usable as-is in 44% (with minor edits 91%). For whole-brain treatment, RPA plans were scored as usable as-is in 67% (with minor edits 99%). For head/neck cancer, the normal tissue autocontours were acceptable as-is in 89% (with minor edits 97%). The clinical target volumes (CTVs) were acceptable as-is in 40% (with minor edits 93%). The volumetric-modulated arc therapy (VMAT) plans were acceptable as-is in 87% (with minor edits 96%). For cervical cancer, the normal tissue autocontours were acceptable as-is in 92% (with minor edits 99%). The CTVs for cervical cancer were scored as acceptable as-is in 83% (with minor edits 92%). The VMAT plans for cervical cancer were acceptable as-is in 99% (with minor edits 100%). CONCLUSION: The RPA, a web-based tool designed to improve access to high-quality RT in low-resource settings, has high rates of clinical acceptability by practicing clinicians around the world. It has significant potential for successful implementation in low-resource clinics.

Mapping of Radiation Oncology and Gynecologic Oncology Services Available to Treat the Growing Burden of Cervical Cancer in Africa.

PURPOSE: To meet the demand for cervical cancer care in Africa, access to surgical and radiation therapy services needs to be understood. We thus mapped the availability of gynecologic and radiation therapy equipment and staffing for treating cervical cancer. METHODS AND MATERIALS: We collected data on gynecologic and radiation oncology staffing, equipment, and infrastructure capacities across Africa. Data was obtained from February to July 2021 through collaboration with international partners using Research Electronic Data Capture. Cancer incidence was taken from the International Agency for Research on Cancer's GLOBOCAN 2020 database. Treatment capacity, including the numbers of radiation oncologists, radiation therapists, physicists, gynecologic oncologists, and hospitals performing gynecologic surgeries, was calculated per 1000 cervical cancer cases. Adequate capacity was defined as 2 radiation oncologists and 2 gynecologic oncologists per 1000 cervical cancer cases. RESULTS: Forty-three of 54 African countries (79.6%) responded, and data were not reported for 11 countries (20.4%). Respondents from 31 countries (57.4%) reported access to specialist gynecologic oncology services, but staffing was adequate in only 11 countries (20.4%). Six countries (11%) reported that generalist obstetrician-gynecologists perform radical hysterectomies. Radiation oncologist access was available in 39 countries (72.2%), but staffing was adequate in only 16 countries (29.6%). Six countries (11%) had adequate staffing for both gynecologic and radiation oncology; 7 countries (13%) had no radiation or gynecologic oncologists. Access to external beam radiation therapy was available in 31 countries (57.4%), and access to brachytherapy was available in 25 countries (46.3%). The number of countries with training programs in gynecologic oncology, radiation oncology, medical physics, and radiation therapy were 14 (26%), 16 (30%), 11 (20%), and 17 (31%), respectively. CONCLUSIONS: We identified areas needing comprehensive cervical cancer care infrastructure, human resources, and training programs. There are major gaps in access to radiation oncologists and trained gynecologic oncologists in Africa.

Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources.

Access to radiotherapy worldwide is limited. The Radiation Planning Assistant (RPA) is a fully automated, web-based tool that is being developed to offer fully automated radiotherapy treatment planning tools to clinics with limited resources. The goal is to help clinical teams scale their efforts, thus reaching more patients with cancer. The user connects to the RPA via a webpage, completes a Service Request (prescription and information about the radiotherapy targets), and uploads the patient's CT image set. The RPA offers two approaches to automated planning. In one-step planning, the system uses the Service Request and CT scan to automatically generate the necessary contours and treatment plan. In two-step planning, the user reviews and edits the automatically generated contours before the RPA continues to generate a volume-modulated arc therapy plan. The final plan is downloaded from the RPA website and imported into the user's local treatment planning system, where the dose is recalculated for the locally commissioned linac; if necessary, the plan is edited prior to approval for clinical use.

ARCHERY: a prospective observational study of artificial intelligence-based radiotherapy treatment planning for cervical, head and neck and prostate cancer - study protocol.

INTRODUCTION: Fifty per cent of patients with cancer require radiotherapy during their disease course, however, only 10%-40% of patients in low-income and middle-income countries (LMICs) have access to it. A shortfall in specialised workforce has been identified as the most significant barrier to expanding radiotherapy capacity. Artificial intelligence (AI)-based software has been developed to automate both the delineation of anatomical target structures and the definition of the position, size and shape of the radiation beams. Proposed advantages include improved treatment accuracy, as well as a reduction in the time (from weeks to minutes) and human resources needed to deliver radiotherapy. METHODS: ARCHERY is a non-randomised prospective study to evaluate the quality and economic impact of AI-based automated radiotherapy treatment planning for cervical, head and neck, and prostate cancers, which are endemic in LMICs, and for which radiotherapy is the primary curative treatment modality. The sample size of 990 patients (330 for each cancer type) has been calculated based on an estimated 95% treatment plan acceptability rate. Time and cost savings will be analysed as secondary outcome measures using the time-driven activity-based costing model. The 48-month study will take place in six public sector cancer hospitals in India (n=2), Jordan (n=1), Malaysia (n=1) and South Africa (n=2) to support implementation of the software in LMICs. ETHICS AND DISSEMINATION: The study has received ethical approval from University College London (UCL) and each of the six study sites. If the study objectives are met, the AI-based software will be offered as a not-for-profit web service to public sector state hospitals in LMICs to support expansion of high quality radiotherapy capacity, improving access to and affordability of this key modality of cancer cure and control. Public and policy engagement plans will involve patients as key partners.

Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant.

PURPOSE: Automation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) to use automated contouring and treatment planning algorithms to support the efforts of oncologists in low- and middle-income countries, allowing them to scale their efforts and treat more patients safely and efficiently (to increase access). DESIGN: In this review, we discuss the development of the RPA, with a particular focus on clinical acceptability and safety/risk across jurisdictions as these are important indicators for the successful future deployment of the RPA to increase radiotherapy availability and ameliorate global disparities in access to radiation oncology. RESULTS: RPA tools will be offered through a webpage, where users can upload computed tomography data sets and download automatically generated contours and treatment plans. All interfaces have been designed to maximize ease of use and minimize risk. The current version of the RPA includes automated contouring and planning for head and neck cancer, cervical cancer, breast cancer, and metastases to the brain. CONCLUSION: The RPA has been designed to bring high-quality treatment planning to more patients across the world, and it may encourage greater investment in treatment devices and other aspects of cancer treatment.

The American Brachytherapy Society and Indian Brachytherapy Society consensus statement for the establishment of high-dose-rate brachytherapy programs for gynecological malignancies in low- and middle-income countries.

PURPOSE: The global cervical cancer burden is disproportionately high in low- and middle-income countries (LMICs), and outcomes can be governed by the accessibility of appropriate screening and treatment. High-dose-rate (HDR) brachytherapy plays a central role in cervical cancer treatment, improving local control and overall survival. The American Brachytherapy Society (ABS) and Indian Brachytherapy Society (IBS) collaborated to provide this succinct consensus statement guiding the establishment of brachytherapy programs for gynecological malignancies in resource-limited settings. METHODS AND MATERIALS: ABS and IBS members with expertise in brachytherapy formulated this consensus statement based on their collective clinical experience in LMICs with varying levels of resources. RESULTS: The ABS and IBS strongly encourage the establishment of HDR brachytherapy programs for the treatment of gynecological malignancies. With the consideration of resource variability in LMICs, we present 15 minimum component requirements for the establishment of such programs. Guidance on these components, including discussion of what is considered to be essential and what is considered to be optimal, is provided. CONCLUSIONS: This ABS/IBS consensus statement can guide the successful and safe establishment of HDR brachytherapy programs for gynecological malignancies in LMICs with varying levels of resources.

Completion of and early response to chemoradiation among human immunodeficiency virus (HIV)-positive and HIV-negative patients with locally advanced cervical carcinoma in South Africa.

BACKGROUND: Very few published studies have dealt with the management of locally advanced cervix carcinoma among human immunodeficiency virus (HIV)-positive patients. The objective of this study was to compare the clinical characteristics, radiation and chemotherapy treatments, and outcomes in a cohort of HIV-positive and HIV-negative women with cervical cancer. METHODS: The authors reviewed the charts of 59 HIV-positive patients and 324 HIV-negative patients who had stage IB1 to IIIB cervical carcinoma and who received radiation therapy. Demographic and clinical characteristics were compared at the time of diagnosis; and radiation doses, chemotherapy cycles, and responses were compared at the time of brachytherapy and at 6-week follow-up. Logistic regression models of response to treatment were developed. RESULTS: Forty-nine HIV-positive patients (88.1%) but only 213 HIV-negative patients (65.7%) presented with stage IIIB disease (P = .009). Forty-seven HIV-positive patients (79.7%) and 291 HIV-negative patients (89.8%) completed the equivalent dose of 68 Grays (Gy) external-beam radiation and high-dose-rate brachytherapy. (P = .03). Of the 333 patients who commenced concurrent chemotherapy, 26 HIV-positive patients (53.1%) and 212 HIV-negative patients (74.6%) completed ≥4 weekly cycles of platinum-based treatment. Follow-up was censured at 6 weeks. In models that included age, disease stage, HIV status, and treatment, a poor response at 6 weeks was associated only with stage IIIB disease (odds ratio, 2.39; 95% confidence interval, 1.45-3.96) and receiving an equivalent radiation dose in 2-Gy fractions of <68 Gy (OR, 3.14; 95% CI, 1.24-7.94). CONCLUSIONS: HIV-positive patients fared worse than HIV-negative patients because of later presentation and a decreased likelihood of completing treatment. The current findings emphasize the importance of completing irradiation therapy. Further studies will address the association of these variables with survival.

Barriers and Facilitators of Implementing Automated Radiotherapy Planning: A Multisite Survey of Low- and Middle-Income Country Radiation Oncology Providers.

PURPOSE: Global access to radiotherapy (RT) is inequitable, with obstacles to implementing modern technologies in low- and middle- income countries (LMICs). The Radiation Planning Assistant (RPA) is a web-based automated RT planning software package intended to increase accessibility of high-quality RT planning. We surveyed LMIC RT providers to identify barriers and facilitators of future RPA deployment and uptake. METHODS: RT providers underwent a pilot RPA teaching session in sub-Saharan Africa (Botswana, South Africa, and Tanzania) and Central America (Guatemala). Thirty providers (30 of 33, 90.9% response rate) participated in a postsession survey. RESULTS: Respondents included physicians (n = 10, 33%), physicists (n = 9, 30%), dosimetrists (n = 8, 27%), residents/registrars (n = 1, 3.3%), radiation therapists (n = 1, 3.3%), and administrators (n = 1, 3.3%). Overall, 86.7% expressed interest in RPA; more respondents expected that RPA would be usable in 2 years (80%) compared with now (60%). Anticipated barriers were lack of reliable internet (80%), potential subscription fees (60%), and need for functionality in additional disease sites (48%). Expected facilitators included decreased workload (80%), decreased planning time (72%), and ability to treat more patients (64%). Forty-four percent anticipated that RPA would help transition from 2-dimensional to 3-dimensional techniques and 48% from 3-dimensional to intensity-modulated radiation treatment. Of a maximum acceptability/feasibility score of 60, physicians (45.6, standard deviation [SD] = 7.5) and dosimetrists (44.3, SD = 9.1) had lower scores than the mean for all respondents (48.3, SD = 7.7) although variation in scores by roles was not significantly different (P = .21). CONCLUSION: These data provide an early assessment and create an initial framework to identify stakeholder needs and establish priorities to address barriers and promote facilitators of RPA deployment and uptake across global sites, as well as to tailor to needs in LMICs.

Clinical acceptability of fully automated external beam radiotherapy for cervical cancer with three different beam delivery techniques.

PURPOSE: To fully automate CT-based cervical cancer radiotherapy by automating contouring and planning for three different treatment techniques. METHODS: We automated three different radiotherapy planning techniques for locally advanced cervical cancer: 2D 4-field-box (4-field-box), 3D conformal radiotherapy (3D-CRT), and volumetric modulated arc therapy (VMAT). These auto-planning algorithms were combined with a previously developed auto-contouring system. To improve the quality of the 4-field-box and 3D-CRT plans, we used an in-house, field-in-field (FIF) automation program. Thirty-five plans were generated for each technique on CT scans from multiple institutions and evaluated by five experienced radiation oncologists from three different countries. Every plan was reviewed by two of the five radiation oncologists and scored using a 5-point Likert scale. RESULTS: Overall, 87%, 99%, and 94% of the automatically generated plans were found to be clinically acceptable without modification for the 4-field-box, 3D-CRT, and VMAT plans, respectively. Some customizations of the FIF configuration were necessary on the basis of radiation oncologist preference. Additionally, in some cases, it was necessary to renormalize the plan after it was generated to satisfy radiation oncologist preference. CONCLUSION: Approximately, 90% of the automatically generated plans were clinically acceptable for all three planning techniques. This fully automated planning system has been implemented into the radiation planning assistant for further testing in resource-constrained radiotherapy departments in low- and middle-income countries.