Background: Parkinson's disease (PD) is the second most common neurodegenerative disorder. Early detection is crucial for treatment and slowing disease progression.
Hypothesis: Simultaneous alterations in mean susceptibility (MS) from quantitative susceptibility mapping (QSM) and mean kurtosis (MK) from diffusion kurtosis imaging (DKI) can serve as reliable neuroimaging biomarkers for early-stage PD (ESPD) in the basal ganglia nuclei, including the substantia nigra (SN), putamen (PUT), globus pallidus (GP), and caudate nucleus (CN).
Study Type: Systematic review and meta-analysis.
Population: One hundred eleven patients diagnosed with ESPD and 81 healthy controls (HCs) were included from four studies that utilized both QSM and DKI in both subject groups.
Field Strength/sequence: Three-dimensional multi-echo gradient echo sequence for QSM and spin echo planar imaging sequence for DKI at 3 Tesla.
Assessment: A systematic review and meta-analysis using PRISMA guidelines searched PubMed, Web of Science, and Scopus.
Statistical Tests: Random-effects model, standardized mean difference (SMD) to compare MS and MK between ESPD patients and HCs, I statistic for heterogeneity, Newcastle-Ottawa Scale (NOS) for risk of bias, and Egger's test for publication bias. A P-value <0.05 was considered significant.
Results: MS values were significantly higher in SN (SMD 0.72, 95% CI 0.31 to 1.12), PUT (SMD 0.68, 95% CI 0.29 to 1.07), and GP (SMD 0.53, 95% CI 0.19 to 0.87) in ESPD patients compared to HCs. CN did not show a significant difference in MS values (P = 0.15). MK values were significantly higher only in SN (SMD = 0.72, 95% CI 0.16 to 1.27). MK values were not significantly different in PUT (P = 1.00), GP (P = 0.97), and CN (P = 0.59). Studies had high quality (NOS 7-8) and no publication bias (P = 0.967).
Data Conclusion: Simultaneous use of MS and MK may be useful as an early neuroimaging biomarker for ESPD detection and its differentiation from HCs, with significant differences observed in the SN.
Evidence Level: 2 TECHNICAL EFFICACY: Stage 2.
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http://dx.doi.org/10.1002/jmri.29569 | DOI Listing |
Ann Intern Med
January 2025
Durham VA Health Care System, Durham; and Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina (K.M.G.).
Background: Tissue-based genomic classifiers (GCs) have been developed to improve prostate cancer (PCa) risk assessment and treatment recommendations.
Purpose: To summarize the impact of the Decipher, Oncotype DX Genomic Prostate Score (GPS), and Prolaris GCs on risk stratification and patient-clinician decisions on treatment choice among patients with localized PCa considering first-line treatment.
Data Sources: MEDLINE, EMBASE, and Web of Science published from January 2010 to August 2024.
J Med Internet Res
January 2025
Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Background: Delayed cerebral ischemia (DCI) is a primary contributor to death after subarachnoid hemorrhage (SAH), with significant incidence. Therefore, early determination of the risk of DCI is an urgent need. Machine learning (ML) has received much attention in clinical practice.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Basic and Community Nursing, School of Nursing, Nanjing Medical University, NanJing, China.
Background: Telehealth interventions can effectively support caregivers of people with dementia by providing care and improving their health outcomes. However, to successfully translate research into clinical practice, the content and details of the interventions must be sufficiently reported in published papers.
Objective: This study aims to evaluate the completeness of a telehealth intervention reporting in randomized controlled trials (RCTs) conducted for caregivers of people with dementia.
JMIR Ment Health
January 2025
Division of Psychology and Mental Health, University of Manchester, Manchester, United Kingdom.
Background: Digital mental health interventions (DMHIs) to monitor and improve the health of people with psychosis or bipolar disorder show promise; however, user engagement is variable, and integrated clinical use is low.
Objective: This prospectively registered systematic review examined barriers and facilitators of clinician and patient engagement with DMHIs, to inform implementation within real-world settings.
Methods: A systematic search of 7 databases identified empirical studies reporting qualitative or quantitative data about factors affecting staff or patient engagement with DMHIs aiming to monitor or improve the mental or physical health of people with psychosis or bipolar disorder.
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