The clinical utility of magnetic resonance imaging (MRI) in judging therapeutic response of bone metastases was evaluated in 18 patients with advanced breast cancer. Treatment efficacy was assessed by MRI and conventional methods such as plain radiograph, bone scan, pain and analgesic scale, and serum CA15-3. The response by MRI was evaluated mainly on T1-weighted sequences by measuring the volume of the bone lesion and soft tissue component. The patient was assumed to be a conventional responder if a complete or partial response was observed in any of the conventional methods described above. Response was most concordant between plain radiographs and MRI findings (91%, 10/11, 95% confidence interval [CI]: 58.7-99.8). The rate of concordance was 61% (11/18, 95% CI 35.8-82.7) for all conventional methods and MRI. MRI revealed response in four patients in whom progressive disease was observed by bone scan and the marker response was not measurable. This pilot study suggests that posttherapy evaluation with MRI may provide useful clinical information in breast cancer patients with bone metastases and may be a valuable adjunct to conventional methods with conflicting results.
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http://dx.doi.org/10.3109/07357909909032842 | DOI Listing |
Respir Med
January 2025
Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Clalit Health Services, Dan Petah Tikva District, Petah Tikva, Israel. Electronic address:
Background: Morbid obesity in adolescents impacts respiratory function, often leading to reduced lung volume and obstructive ventilatory defects. However, standard spirometric values frequently remain within normal ranges.
Objectives: We hypothesized that Lung Clearance Index (LCI) is a more sensitive marker for detecting airway dysfunction in adolescents with morbid obesity than conventional lung function tests.
Forensic Sci Int
January 2025
Leverhulme Research Centre for Forensic Science, Department of Science and Engineering, University of Dundee, Dundee DD1 4HN, UK.
The evaluation of the shedding capacity of a garment is crucial in forensic analysis to understand fibre transfer mechanisms during contact activities. While adhesive tapes are commonly used, the lack of standardised pressure application -often done manually- poses a challenge. In addition, while previous studies have examined the effects of washing on fibre evidence, there is a notable absence in the literature regarding its impact on garment shedding capacity.
View Article and Find Full Text PDFAnn Phys Rehabil Med
January 2025
University Grenoble Alpes, UMR CNRS 5105 Neuropsychology and NeuroCognition, CHU Grenoble Alpes, Dept of NeuroRehabilitation South Hospital, Cs 10217-38043 Grenoble cedex 9, France. Electronic address:
Background: Many signs of spatial dysgraphia and drawing errors after right hemispheric stroke (RHS) have been attributed to spatial neglect or impaired sensory feedback. Counterclockwise (contralesional) tilts of graphomotor productions remained to be explained.
Objective: To test whether graphomotor tilts stem from a tilted representation of verticality transposed to the top/bottom axis of the sheet of paper, using data from the DOBRAS cohort.
J Pharm Biomed Anal
January 2025
Sabanci University Nanotechnology Research and Application Center (SUNUM), Istanbul 34956, Turkey.
This study aimed to determine the chromatographic retention and dissociation/protonation constant (pK) values of lapatinib and tamoxifen, key drugs used in metastatic breast cancer treatment, at 37°C using both conventional and green high-performance liquid chromatography (HPLC) methods. Qualitative analysis was conducted on an XTerra C18 column (250 ×4.6 mm I.
View Article and Find Full Text PDFNeural Netw
December 2024
Department of Earth Science and Engineering, Imperial College London, Prince Consort Road, London SW7 2BP, UK; Centre for AI-Physics Modelling, Imperial-X, White City Campus, Imperial College London, W12 7SL, UK.
Machine learning (ML) has benefited from both software and hardware advancements, leading to increasing interest in capitalising on ML throughout academia and industry. There have been efforts in the scientific computing community to leverage this development via implementing conventional partial differential equation (PDE) solvers with machine learning packages, most of which rely on structured spatial discretisation and fast convolution algorithms. However, unstructured meshes are favoured in problems with complex geometries.
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