Background Targeted radionuclide therapy (TRT) is a fast‐growing field garnering much interest, with several clinical trials currently underway, that has a steady increase in development of treatment techniques. Unfortunately, within the field and many clinical trials, the dosimetry calculation techniques used remain relatively simple, often using a mix of S‐value calculations and kernel convolutions. Purpose The common TRT calculation techniques, although very quick, can often ignore important aspects of patient anatomy and radionuclide distribution, as well as the interplay there‐in. This paper introduces egs_mird, a new Monte Carlo (MC) application built in EGSnrc which allows users to model full patient tissue and density (using clinical CT images) and radionuclide distribution (using clinical PET images) for fast and detailed dose TRT calculation. Methods The novel application egs_mird is introduced along with a general outline of the structure of egs_mird simulations. The general structure of the code, and the track‐length (TL) estimator scoring implementation for variance reduction, is described. A new egs++ source class egs_internal_source, created to allow detailed patient‐wide source distribution, and a modified version of egs_radionuclide_source, changed to be able to work with egs_internal_source, are also described. The new code is compared to other MC calculations of S‐values kernels of 131I, 90Y, and 177Lu in the literature, along with further self‐validation using a histogram variant of the electron Fano test. Several full patient prostate 177Lu TRT prostate cancer treatment simulations are performed using a single set of patient DICOM CT and [18F]‐DCFPyL PET data. Results Good agreement is found between S‐value kernels calculated using egs_mird with egs_internal_source and those found in the literature. Calculating 1000 doses (individual voxel uncertainties of ∼0.05%) in a voxel grid Fano test for monoenergetic 500 keV electrons and 177Lu electrons results in 94% and 99% of the doses being within 0.1% of the expected dose, respectively. For a hypothetical 177Lu treatment, patient prostate, rectum, bone marrow, and bladder dose volume histograms (DVHs) results did not vary significantly when using the TL estimator and not modeling electron transport, modeling bone marrow explicitly (rather than using generic tissue compositions), and reducing activity to voxels containing partial or full calcifications to half or none, respectively. Dose profiles through different regions demonstrate there are some differences with model choices not seen in the DVH. Simulations using the TL estimator can be completed in under 15 min (∼30 min when using standard interaction scoring). Conclusion This work shows egs_mird to be a reliable MC code for computing TRT doses as realistically as the patient Computed Tomography (CT) and Positron Emission Tomography (PET) data allow. Furthermore, the code can compute doses to sub‐1% uncertainty within 15 min, with little to no optimization. Thus, this work supports t...
Background CNS tumor registries (CTR) has evolved to a key tool for data collection, evaluation of diagnostic and treatment of patients suffering from tumors of the central nervous system (tCNS) in the U.S, but CTR in Africa does not yet exist. In comparison to high-income countries (HIC), many low- and middle-income countries (LMIC) do not yet have national or central CNS tumor registries. Furthermore, appropriate diagnostic steps like MRI and pathological analysis are still scarce in many LMIC. Improving the availability of CTR in resource- limited regions could allow better understanding of some specificities of tCNS including incidence, prevalence, mortality and morbidity. However, CTR, MRI and pathological analysis tend to be costly and thus difficult to implement in the LMIC setting. Material and Methods A review of the current body of literature on tCNS in Africa was conducted using multiple scientific online data bases. Search terms included ,,CNS tumor registry,” “developing countries,” “low and middle income,” and other related terms as starting point for future initiatives. Results It was found that more than 1,3 billion people residing in Africa lack access to a continental CTR. There is no well established standards for reporting tCNS. Most tCNS are still underreported in many countries of Africa. The exact burden of tCNS in Africa is unknown. Although many successful, long-term, initiatives for international neurological and neurosurgical collaborations are published, any CTR of Africa similarly to the Central Brain Tumor Registry of the United States (CBTRUS) is lacking. Conclusion: Disparities in access to care for patients suffering from tCNS have been well published but well established solutions are still under investigations. Partnerships between centers in LMIC and HIC are making progress to better understand the burden of disease in LMIC and to create context-specific solutions for practice in the LMIC setting. Collaboration between the World Health Organisation, national centers for disease control in Africa, departments of neuroscience in LMIC and well established registries like the CBTRUS as well as other interested groups could be meaningful strategical steps to be initiated for the establishment of CTR in Africa. A CTR for Africa could lead to better comprehension of tCNS in Africa, thus facilitate prevention, diagnostic, treatment and research.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.