Background: After each cycle of [Lu]-DOTA-TATE peptide receptor radionuclide therapy (PRRT) dosimetry is performed to enable precise calculation of the radiation-absorbed dose to tumors and normal organs. Absorbed doses are routinely calculated from three quantitative single-photon emission computed tomography (SPECT) studies corrected by computed tomography (CT) acquired at t = 24 h, t = 96 h, and t = 168 h after the first cycle of treatment. After following cycles, a single SPECT/CT study is performed. The aim of the present study is to assess the feasibility of a "two time point" quantitative SPECT/CT protocol after the first PRRT cycle and its impact on patient management. Quantitative SPECT/CT data of 25 consecutive patients with metastatic neuroendocrine tumors after PRRT were retrospectively analyzed. Radiation-absorbed doses calculated using the standard protocol with three SPECT/CT studies acquired at (t, t, t) were compared to those obtained from three different "two time point" protocols with SPECT/CT studies performed at (t, t), (t, t), or (t, t).
Results: The best agreement for the cumulative doses absorbed by the kidneys, bone marrow, liver, spleen, and tumors with the conventional protocol was obtained with the (t, t) protocol with mean relative differences of - 1.0% ± 2.4%, 0.4% ± 3.1%, - 0.9% ± 4.0%, - 0.8% ± 1.1%, and - 0.5% ± 2.0%, respectively, and correlation coefficients of r = 0.99 for all. In all patients, there was no difference in the management decision of whether or not to stop PRRT because of unsafe absorbed dose to risk organs using either the standard protocol or the (t, t) protocol.
Conclusion: These preliminary results demonstrate that dosimetry calculations using two quantitative SPECT/CT studies acquired at 24 and 168 h after the first PRRT cycle are feasible and are in good agreement with the standard imaging protocol with no change in patient management decisions, while enabling improved patient comfort and reduced scanner and staff time.
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http://dx.doi.org/10.1186/s40658-020-0273-8 | DOI Listing |
J Clin Endocrinol Metab
January 2025
Department of Internal Medicine and Therapeutics, University of Pavia, 27100 Pavia, Italy.
Background: Thyroid nodules classified cytologically as low-risk indeterminate lesions (TIR3A) on fine-needle aspiration biopsy (FNAB) present a clinical challenge due to their uncertain malignancy risk. This single-center study aimed to evaluate the natural history of TIR3A nodules.
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JMIR Ment Health
January 2025
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States.
Background: Mental health concerns have become increasingly prevalent; however, care remains inaccessible to many. While digital mental health interventions offer a promising solution, self-help and even coached apps have not fully addressed the challenge. There is now a growing interest in hybrid, or blended, care approaches that use apps as tools to augment, rather than to entirely guide, care.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Department of Dermatology, Hospital Universitario Ramon y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain, Madrid, Spain.
Background: Psoriasis is an inflammatory disease primarily treated through molecular-targeted therapies. However, emerging evidence suggests that dietary interventions may also play a role in managing inflammation associated with this condition. The Mediterranean diet (MedDiet), prevalent in southern European countries, has been widely recognized for its ability to reduce cardiovascular mortality, largely due to its anti-inflammatory properties.
View Article and Find Full Text PDFJCO Clin Cancer Inform
January 2025
Department of Radiology, Dr BRAIRCH, All India Institute of Medical Sciences, New Delhi, India.
Purpose: To explore the perceived utility and effect of simplified radiology reports on oncology patients' knowledge and feasibility of large language models (LLMs) to generate such reports.
Materials And Methods: This study was approved by the Institute Ethics Committee. In phase I, five state-of-the-art LLMs (Generative Pre-Trained Transformer-4o [GPT-4o], Google Gemini, Claude Opus, Llama-3.
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