arXiv subjects

Steve P. Lee

Publications and source records attributed to Steve P. Lee.

2 recordsLinked to original sources

arXiv2024

A generalized software framework for consolidation of radiotherapy planning and delivery data from diverse data sources

Aggregating large-scale radiotherapy planning and delivery data is crucial for advancing radiation oncology research and improving clinical practice, yet challenges persist due to the diversity of treatment planning systems (TPS), record and verify (R&V) systems, and complex data formats lacking standardized retrieval methods. We developed a robust software framework that automates the collection and integration of multi-institutional radiotherapy data from diverse TPS and R&V systems. By utilizing the unidirectional references of DICOM objects, our framework reconstructs complete patient datasets starting from Radiotherapy Treatment Records (RTRECORDs), managing tasks such as data queries, transfers, verification, and logging. It effectively maps DICOM linkages between RTRECORDs, RTPLANs, RTDOSEs, RTSTRUCTs, planning images, registrations, and associated diagnostic images, incorporating custom modules for data conversion and comprehensive error handling. Implemented across multiple institutions using various systems$-$ including ARIA, Eclipse, MOSAIQ, RayStation, MIM, Pinnacle$-$ the framework successfully collected data from two clinics over an 11-year period, aggregating data from 6,022 patients and 13,871 treatment plans with a success rate of 99.76% and an average processing time of approximately 18 minutes per patient. Ongoing efforts are extending data collection to clinics lacking DICOM Query/Retrieve capabilities, demonstrating the framework's adaptability to various clinical environments. This efficient automation of comprehensive data collection overcomes significant technical barriers, facilitating the creation of large-scale datasets that can accelerate advancements in radiation oncology.

physics.med-ph↗

arXiv2006

Characterization of Metastatic Tumor Formation by the Colony Size Distribution

Knowledge regarding the kinetics of metastatic tumor formation, as related to the growth of the primary tumor, represents a fundamental issue in cancer biology. Using an in vivo mammalian model, we show here that one can obtain useful information from the frequency distribution of the sizes of metastatic colonies in distant organs after serial sectioning and image reconstruction. To explain the experimental findings, we constructed a biophysical model based on the respective growth patterns of the primary tumor and metastases and a stochastic process of metastatic colony formation. Heterogeneous distributions of various biological parameters were considered. We found that the elementary assumption of exponential forms of growth for the primary tumor and metastatic colonies predicts a linear relation on a log-log plot of a metastatic colony size distribution, which was consistent with the experimental results. Furthermore, the slope of the curve signifies the ratio of growth rates of the primary and the metastases. Non-exponential (Gompertzian and logistic) tumor growth patterns were also incorporated into the theory to explain possible deviation from the log-log linear relation. The observed metastasis-free probability also supported the assumption of a time-dependent Poisson process. With this approach, we determined the mechanistic parameters governing the process of metastatogenesis in the lungs for two murine tumor cell lines (KHT and MCaK). Since biological parameters specified in the model could be obtained in the laboratory, a workable metastatic "assay" may be established for various malignancies and in turn contribute in formulating rational treatment regimens for subclinical metastases.

q-bio.TO↗