First measurements of radon-220 diffusion in mice tumors, towards treatment planning in diffusing alpha-emitters radiation therapy

Alpha-DaRT is a new method for treating solid tumors with alpha particles, relying on the release of the alpha-emitting daughter atoms of radium-224 from sources inserted into the tumor. The most important model parameters for Alpha-DaRT dosimetry are the diffusion lengths of radon-220 and lead-212, and their estimation is essential for treatment planning. The aim of this work is to provide first experimental estimates for the diffusion length of radon-220. The diffusion length of radon-220 was estimated from autoradiography measurements of histological sections taken from 24 mice-borne subcutaneous tumors of five different types. Experiments were done in two sets: fourteen in-vivo tumors, where during the treatment the tumors were still carried by the mice with active blood supply, and ten ex-vivo tumors, where the tumors were excised before source insertion and kept in a medium at 37 degrees C with the source inside. The measured diffusion lengths of radon-220 lie in the range 0.25-0.6 mm, with no significant difference between the average values measured in in-vivo and ex-vivo tumors: 0.40 $\pm$ 0.08 mm for in-vivo vs. 0.39 $\pm$ 0.07 mm for ex-vivo. However, in-vivo tumors display an enhanced spread of activity 2-3 mm away from the source. This effect is not explained by the current model and is much less pronounced in ex-vivo tumors. The average measured radon-220 diffusion lengths in both in-vivo and ex-vivo tumors lie close to the upper limit of the previously estimated range of 0.2-0.4 mm. The observation that close to the source there is no apparent difference between in-vivo and ex-vivo tumors, and the good agreement with the theoretical model in this region suggest that the spread of radon-220 is predominantly diffusive in this region. The departure from the model prediction in in-vivo tumors at large radial distances may hint at potential vascular contribution

Assessing the Performance of a New Artificial Intelligence–Driven Diagnostic Support Tool Using Medical Board Exam Simulations: Clinical Vignette Study

BackgroundDiagnostic decision support systems (DDSS) are computer programs aimed to improve health care by supporting clinicians in the process of diagnostic decision-making. Previous studies on DDSS demonstrated their ability to enhance clinicians’ diagnostic skills, prevent diagnostic errors, and reduce hospitalization costs. Despite the potential benefits, their utilization in clinical practice is limited, emphasizing the need for new and improved products. ObjectiveThe aim of this study was to conduct a preliminary analysis of the diagnostic performance of “Kahun,” a new artificial intelligence-driven diagnostic tool. MethodsDiagnostic performance was evaluated based on the program’s ability to “solve” clinical cases from the United States Medical Licensing Examination Step 2 Clinical Skills board exam simulations that were drawn from the case banks of 3 leading preparation companies. Each case included 3 expected differential diagnoses. The cases were entered into the Kahun platform by 3 blinded junior physicians. For each case, the presence and the rank of the correct diagnoses within the generated differential diagnoses list were recorded. Each diagnostic performance was measured in two ways: first, as diagnostic sensitivity, and second, as case-specific success rates that represent diagnostic comprehensiveness. ResultsThe study included 91 clinical cases with 78 different chief complaints and a mean number of 38 (SD 8) findings for each case. The total number of expected diagnoses was 272, of which 174 were different (some appeared more than once). Of the 272 expected diagnoses, 231 (87.5%; 95% CI 76-99) diagnoses were suggested within the top 20 listed diagnoses, 209 (76.8%; 95% CI 66-87) were suggested within the top 10, and 168 (61.8%; 95% CI 52-71) within the top 5. The median rank of correct diagnoses was 3 (IQR 2-6). Of the 91 expected diagnoses, 62 (68%; 95% CI 59-78) of the cases were suggested within the top 20 listed diagnoses, 44 (48%; 95% CI 38-59) within the top 10, and 24 (26%; 95% CI 17-35) within the top 5. Of the 91 expected diagnoses, in 87 (96%; 95% CI 91-100), at least 2 out of 3 of the cases’ expected diagnoses were suggested within the top 20 listed diagnoses; 78 (86%; 95% CI 79-93) were suggested within the top 10; and 61 (67%; 95% CI 57-77) within the top 5. ConclusionsThe diagnostic support tool evaluated in this study demonstrated good diagnostic accuracy and comprehensiveness; it also had the ability to manage a wide range of clinical findings

APR-246 as a radiosensitization strategy for mutant p53 cancers treated with alpha-particles-based radiotherapy

Abstract Radiation therapy (RT) remains a common treatment for cancer patients worldwide, despite the development of targeted biological compounds and immunotherapeutic drugs. The challenge in RT lies in delivering a lethal dose to the cancerous site while sparing the surrounding healthy tissues. Low linear energy transfer (low-LET) and high linear energy transfer (high-LET) radiations have distinct effects on cells. High-LET radiation, such as alpha particles, induces clustered DNA double-strand breaks (DSBs), potentially inducing cell death more effectively. However, due to limited range, alpha-particle therapies have been restricted. In human cancer, mutations in TP53 (encoding for the p53 tumor suppressor) are the most common genetic alteration. It was previously reported that cells carrying wild-type (WT) p53 exhibit accelerated senescence and significant rates of apoptosis in response to RT, whereas cells harboring mutant p53 (mutp53) do not. This study investigated the combination of the alpha-emitting atoms RT based on internal Radium-224 (224Ra) sources and systemic APR-246 (a p53 reactivating compound) to treat tumors with mutant p53. Cellular models of colorectal cancer (CRC) or pancreatic ductal adenocarcinoma (PDAC) harboring mutant p53, were exposed to alpha particles, and tumor xenografts with mutant p53 were treated using 224Ra source and APR-246. Effects on cell survival and tumor growth, were assessed. The spread of alpha emitters in tumors was also evaluated as well as the spatial distribution of apoptosis within the treated tumors. We show that mutant p53 cancer cells exhibit radio-sensitivity to alpha particles in vitro and to alpha-particles-based RT in vivo. APR-246 treatment enhanced sensitivity to alpha radiation, leading to reduced tumor growth and increased rates of tumor eradication. Combining alpha-particles-based RT with p53 restoration via APR-246 triggered cell death, resulting in improved therapeutic outcomes. Further preclinical and clinical studies are needed to provide a promising approach for improving treatment outcomes in patients with mutant p53 tumors