Objectives: In radiotherapy, delineation uncertainties are important as they contribute to systematic errors and can lead to geographical miss of the target. For margin computation, standard deviations (SDs) of all uncertainties must be included as SDs. The aim of this study was to quantify the interobserver delineation variation for stereotactic body radiotherapy (SBRT) of peripheral lung tumours using a cross-sectional study design.
Methods: 22 consecutive patients with 26 tumours were included. Positron emission tomography/CT scans were acquired for planning of SBRT. Three oncologists and three radiologists independently delineated the gross tumour volume. The interobserver variation was calculated as a mean of multiple SDs of distances to a reference contour, and calculated for the transversal plane (SD(trans)) and craniocaudal (CC) direction (SD(cc)) separately. Concordance indexes and volume deviations were also calculated.
Results: Median tumour volume was 13.0 cm(3), ranging from 0.3 to 60.4 cm(3). The mean SD(trans) was 0.15 cm (SD 0.08 cm) and the overall mean SD(cc) was 0.26 cm (SD 0.15 cm). Tumours with pleural contact had a significantly larger SD(trans) than tumours surrounded by lung tissue.
Conclusions: The interobserver delineation variation was very small in this systematic cross-sectional analysis, although significantly larger in the CC direction than in the transversal plane, stressing that anisotropic margins should be applied. This study is the first to make a systematic cross-sectional analysis of delineation variation for peripheral lung tumours referred for SBRT, establishing the evidence that interobserver variation is very small for these tumours.
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http://dx.doi.org/10.1259/bjr/76424694 | DOI Listing |
Antibodies (Basel)
December 2024
Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, USA.
Background: The complementarity-determining region (CDR) of antibodies represents the most diverse region both in terms of sequence and structural characteristics, playing the most critical role in antibody recognition and binding for immune responses. Over the past decades, several numbering schemes have been introduced to define CDRs based on sequence. However, the existence of diverse numbering schemes has led to potential confusion, and a comprehensive evaluation of these schemes is lacking.
View Article and Find Full Text PDFHum Reprod
December 2024
Department of Medical BioSciences, Radboudumc, Nijmegen, The Netherlands.
Study Question: How can we best achieve tissue segmentation and cell counting of multichannel-stained endometriosis sections to understand tissue composition?
Summary Answer: A combination of a machine learning-based tissue analysis software for tissue segmentation and a deep learning-based algorithm for segmentation-independent cell identification shows strong performance on the automated histological analysis of endometriosis sections.
What Is Known Already: Endometriosis is characterized by the complex interplay of various cell types and exhibits great variation between patients and endometriosis subtypes.
Study Design, Size, Duration: Endometriosis tissue samples of eight patients of different subtypes were obtained during surgery.
Discov Oncol
December 2024
Department of Cerebrovascular Disease, Suining First People's Hospital, No. 2 Wentao Road, High-Tech Zone, Suining, 629000, Sichuan, China.
The immune response plays a pivotal role in tumor progression and therapy. However, the influence of protein PAR polymerases (PARPs) modifications on cell infiltration within the tumor microenvironment (TME) remains insufficiently understood. In this study, the Clinical and RNA sequencing data we performed a comprehensive analysis of PARPs modification patterns, exploring their associations with TME cell infiltration were acquired from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) database.
View Article and Find Full Text PDFSci Total Environ
December 2024
Center for Climate Change Adaptation, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan. Electronic address:
Understanding multifaceted climate change risks and their interconnections is essential for effective adaptation strategies, which require comprehensive assessments of both climatic impact variations and social-environmental exposures/vulnerabilities. This study examines these interconnections and creates multitier delineations of future climate risks across Japan by overlaying homogeneous impact zones (HIZs) with exposure-vulnerability complexes (EVCs). We delineated eight EVC regions, each exhibiting similar patterns of exposure and vulnerability, via multivariate clustering and similarity search on the basis of future population and land cover/use data.
View Article and Find Full Text PDFSemantic surgical scene segmentation is crucial for accurately identifying and delineating different tissue types during surgery, enhancing outcomes and reducing complications. Hyperspectral imaging provides detailed information beyond visible color filters, offering an enhanced view of tissue characteristics. Combined with machine learning, it supports critical tumor resection decisions.
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