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Author(s): Rohit Singh Chauhan (corresponding author) [1]; Anusheel Munshi [2]; Anirudh Pradhan [3] INTRODUCTION The growing global burden of cancer has become a major concern, with projections indicating a 47% [...], Aim: This article examines India's present radiotherapy (RT) machine status and requirements, geographical distribution, and infrastructure need in six regional areas, which include 31 member states and union territories (UTs). It also considers the influence of the COVID-19 pandemic on India's teletherapy sector. Materials and Methods: Data from reliable resources, including Atomic Energy Regulatory Board, Global Cancer Observatory, and Directory of Radiotherapy Centres databases, were used to analyze the current status of RT machine (RTM) density, regional disparity, and COVID-19 impact on infrastructure growth-rate. Results: In India, the number of functioning RTM and facilities are 823 and 554, respectively, with an average of 1.5 RTM per institute, of which 69.4% have only one RTM. Over the past 22 years, there has been a paradigm shift towards medical linear accelerator (linac) installation instead of telecobalt machines. Presently, there is a teletherapy density of 0.6 RTM per million population, and there is a shortfall of 1209 RTMs. There is a considerable regional disparity in the distribution of RTMs, ranging from (0.08 RTM/million-2.94 RTM/million) across different regions. There is a significant demand for RTMs in the Northern region (480) and the state of Uttar Pradesh (279). The COVID-19 pandemic temporarily impacted India's RT growth rate, reducing it from 5% to 1.9% in 2020-2021. Conclusions: New policies must be established to accelerate the rate of RT installation growth. To better serve local populations and save patient costs, this article proposes that RT facilities be dispersed equitably across states. Keywords: COVID-19, health policy, oncology, particle accelerators, radiotherapy

Aim: Cancer is a significant public health concern, and National Cancer Control Programs (NCCPs) are crucial for reducing its burden. However, assessing the progress of NCCPs is challenging due to the complexity of cancer control outcomes and the various factors that influence them. Composite indicators can provide a comprehensive and accurate assessment of NCCP progress. Materials and Methods: The dataset was compiled for 144 countries and comprised eight composite indices and two high-level comparative indicators (mortality-to-cancer incidence ratio [MIR] and 5-year cancer prevalence-to-incidence ratio [PCIR]) representing NCCP outcomes. Two large databases and six annual composite index reports were consulted. Linear regression analysis and Pearson correlation coefficients were used to establish a relationship between indicators and NCCP outcomes. A multiple regression machine learning model was generated to further improve the accuracy of NCCP outcome prediction. Results: High-income countries had the highest cancer incidence, whereas low-income countries had the highest MIR. Linear regression analysis indicated a negative trend between all composite indicators and MIR, whereas a positive trend was observed with PCIR. The Human Development Index and the Legatum Prosperity Index had the highest adjusted R2 values for MIR (0.74 and 0.73) and PCIR (0.86 and 0.81), respectively. Multiple linear regression modeling was performed, and the results indicated a low mean squared error score (-0.02) and a high R2 score (0.86), suggesting that the model accurately predicts NCCP outcomes. Conclusions: Overall, composite indicators can be an effective tool for evaluating NCCP, and the results of this study can aid in the development and keeping track of NCCP progress for better cancer control. [ABSTRACT FROM AUTHOR]

Purpose: Rising cancer incidences, complex treatment techniques, and workflows have all impacted the radiotherapy scheduling process. Intelligent appointment scheduling is needed to help radiotherapy users adapt to new practices. Materials and Methods: We utilized van Herk’s safety margin formula to determine the radiotherapy department’s treatment scheduling window (TSW). In addition, we examined the influence of in‑room imaging on linac occupancy time (LOT). Varian Aria™ software version 15.1 was used to collect retrospective data on LOT, treatment site, intent, techniques, special protocol, and in‑room imaging. Results: Treatment scheduling windows varied across treatment sites. The mean TSW using van Herk’s formalism was 31.5 min, significantly longer than the current TSW of 15 min (P = 0.036), with the pelvic site having the longest (43.8 min) and the brain site having the shortest (12 min). 28% of patients exceeded the in‑practice TSW of 15 min. 46.2% of patients had multiple images per fraction, with the proportion being highest in pelvic patients(33%). Patients treated with palliative intent, intensity‑modulated radiotherapy, special protocols (bladder protocol and gating), and multiple in‑room images per fraction had significantly higher LOT. High treatment time uncertainty was observed in the pelvic and thorax sites, indicating the impact of in‑room imaging frequency and on‑couch treatment decisions on overall treatment time and indicating that current treatment practices should be reviewed and modified if necessary. Conclusions: The time margin recipe can customize the treatment scheduling window and improve treatment practices. This formalism can help manage the radiotherapy department’s workload and reduce patient wait times. [ABSTRACT FROM AUTHOR]

Radial scars or complex sclerosing lesions are common benign lesions in the breast with characteristic radiological and pathological features. The pathological diagnosis of carcinoma arising in this setting requires careful amalgamation of clinical, radiological and morphological details. Ancillary techniques like immunohistochemistry aid in the diagnosis. We report an unusual case of a secretory carcinoma arising in the background of a radial scar.