Zeitschrift fur Medizinische Physik This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Time-integrated radiation risk metrics and interpopulation variability of survival
Z Med Phys. 2023 Sep 3:S0939-3889(23)00091-0. doi: 10.1016/j.zemedi.2023.08.002. Online ahead of print.ABSTRACTTask Group 115 of the International Commission on Radiological Protection is focusing on mission-related exposures to space radiation and concomitant health risks for space crew members including, among others, risk of cancer development. Uncertainties in cumulative radiation risk estimates come from the stochastic nature of the considered health outcome (i.e., cancer), uncertainties of statistical inference and model parameters, unknown secular trends used for projections of population statistics and unknown vari...
Source: Zeitschrift fur Medizinische Physik - September 5, 2023 Category: Radiology Authors: Alexander Ulanowski Nobuhiko Ban Kotaro Ozasa Werner R ühm Edward Semones Mark Shavers Ludovic Vaillant Source Type: research

Compartment-specific < sup > 129 < /sup > Xe HyperCEST z spectroscopy and chemical shift imaging of cucurbit[6]uril in spontaneously breathing rats
Z Med Phys. 2023 Sep 1:S0939-3889(23)00094-6. doi: 10.1016/j.zemedi.2023.08.005. Online ahead of print.ABSTRACT129Xe hyperpolarized gas chemical exchange saturation transfer (HyperCEST) MRI has been suggested as molecular imaging modality but translation to in vivo imaging has been slow, likely due to difficulties of synthesizing suitable molecules. Cucurbit[6]uril-either in readily available non-functionalized or potentially in functionalized form-may, combined with 129Xe HyperCEST MRI, prove useful as a switchable 129Xe MR contrast agent but the likely differential properties of contrast generation in individual chemical...
Source: Zeitschrift fur Medizinische Physik - September 4, 2023 Category: Radiology Authors: Agilo Luitger Kern Marcel Gutberlet Regina Rumpel Inga Bruesch Jens M Hohlfeld Frank Wacker Bennet Hensen Source Type: research

PSMA-PET improves deep learning-based automated CT kidney segmentation
CONCLUSION: This study shows that deep-learning based kidney segmentation can be significantly improved through the addition of a PET-based pre-segmentation. The presented method was shown to be especially beneficial for kidneys with cysts or kidneys that are closely adjacent to other organs such as the spleen, liver or pancreas. In the future, this could lead to a considerable reduction in the time required for dosimetry calculations as well as an improvement in the results.PMID:37666698 | DOI:10.1016/j.zemedi.2023.08.006 (Source: Zeitschrift fur Medizinische Physik)
Source: Zeitschrift fur Medizinische Physik - September 4, 2023 Category: Radiology Authors: Julian Leube Matthias Horn Philipp E Hartrampf Andreas K Buck Michael Lassmann Johannes Tran-Gia Source Type: research

Development and clinical implementation of a digital system for risk assessments for radiation therapy
Z Med Phys. 2023 Sep 2:S0939-3889(23)00092-2. doi: 10.1016/j.zemedi.2023.08.003. Online ahead of print.ABSTRACTBefore introducing new treatment techniques, an investigation of hazards due to unintentional radiation exposures is a reasonable activity for proactively increasing patient safety. As dedicated software is scarce, we developed a tool for risk assessment to design a quality management program based on best practice methods, i.e., process mapping, failure modes and effects analysis and fault tree analysis. Implemented as a web database application, a single dataset was used to describe the treatment process and its...
Source: Zeitschrift fur Medizinische Physik - September 4, 2023 Category: Radiology Authors: Dominik Kornek David Menichelli J örg Leske Michael Hofmann David Antkiewicz Tobias Brandt Oliver J Ott Michael Lotter Marga Lang-Welzenbach Rainer Fietkau Christoph Bert Source Type: research

Automated prognosis of renal function decline in ADPKD patients using deep learning
Z Med Phys. 2023 Aug 21:S0939-3889(23)00090-9. doi: 10.1016/j.zemedi.2023.08.001. Online ahead of print.ABSTRACTAn accurate prognosis of renal function decline in Autosomal Dominant Polycystic Kidney Disease (ADPKD) is crucial for early intervention. Current biomarkers used are height-adjusted total kidney volume (HtTKV), estimated glomerular filtration rate (eGFR), and patient age. However, manually measuring kidney volume is time-consuming and subject to observer variability. Additionally, incorporating automatically generated features from kidney MRI images, along with conventional biomarkers, can enhance prognostic imp...
Source: Zeitschrift fur Medizinische Physik - August 23, 2023 Category: Radiology Authors: Anish Raj Fabian Tollens Anna Caroli Dominik N örenberg Frank G Z öllner Source Type: research