Background: Three-dimensional Quantitative Transmission (QT) ultrasound imaging is an emerging modality for improving the detection and diagnosis of breast cancer. QT ultrasound has high resolution and high contrast to noise ratio, making it effective in evaluating breast tissue. This study compares radiologists' performance of noncancer recall rates and lesion detection rates using QT Ultrasound versus full-field digital mammography (FFDM) in a cross section of female subjects.
Materials And Methods: In this multi-reader multi-case (MRMC) study, we examined retrospective data from two clinical trials conducted at five sites. All subjects received FFDM and QT scans within 90 days. Data were analyzed in a reader study with full factorial design involving 22 radiologists and 108 breast cases (42 normal, 39 pathology-confirmed benign, and 27 pathology-confirmed cancer cases). The main results used a random-reader random-case analysis adjusted for location bias performed after a primary predefined random-reader fixed-case analysis.
Results: The readers' mean rate of detecting lesions of any type was 4% higher (p-value > 0.05) with QT imaging. The mean non-cancer recall rate improved significantly, showing a decrease of 16% with QT (p-value = 0.03), at the expense of a 2% decrease in the mean cancer recall rate (p-value >0.05) in comparison to FFDM. Combining performance on cancer and noncancer recall rates, the mean area under the receiver operator curve of confidence scores improved significantly by 10% with QT (p-value = 0.01).
Conclusion: This MRMC study indicates that QT improves non-cancer recall rates without substantially affecting cancer recall rates. The main limitation is the small number of cases from retrospective data. A larger prospective MRMC study is warranted for further assessment.
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http://dx.doi.org/10.1016/j.acra.2020.11.011 | DOI Listing |
Front Child Adolesc Psychiatry
June 2024
Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA, United States.
Introduction: Rising rates of adolescent overdose deaths attributed to counterfeit prescription drugs purchased using social media have drawn national attention to how these platforms might influence substance use. Research suggests a significant relationship exists between exposure to substance-related social media content and use of drugs and alcohol, but most studies are cross-sectional and limited by recall bias. This study used an ecological momentary assessment (EMA) protocol to collect longitudinal data on social media use and online drug-related exposures associated with youth substance use.
View Article and Find Full Text PDFInt Breastfeed J
January 2025
Division of Epidemiology & Biostatistics, Faculty of Medicine and Health Sciences, Stellenbosch University, Francie van Zijl Drive, PO Box 241, Cape Town, 8000, South Africa.
Background: Despite efforts to promote optimal breastfeeding practices, the practice of exclusive breastfeeding is low in South Africa. We conducted a trial to determine whether text messaging plus motivational interviewing prolonged exclusive breastfeeding during the first six months of life and improved child health outcomes.
Methods: We conducted a randomized parallel group-controlled trial between July 2022 and May 2024, at a secondary-level healthcare facility.
Mem Cognit
January 2025
College of Education, Psychology and Social Work, Flinders University, GPO Box 2100, Adelaide, South Australia, 5042, Australia.
People show enhanced memory recall for disgust over fear, despite both being highly negative and arousing emotions. But does disgust's 'stickiness' in memory result in more false memories for disgust versus fear? Existing research finds low false-memory rates for disgust and fear, perhaps from using image lures depicting content unrelated to target images. Therefore, we presented 111 participants with disgust, fear, (and neutral) images during an attention-monitoring task.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Clinical Pharmacy, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Integrating machine learning (ML) models into healthcare systems is a rapidly evolving field with the potential to revolutionize care delivery. This study aimed to classify fertility rates and identify significant predictors using ML models among reproductive women in Ethiopia. This study utilized eight ML models in 5864 reproductive-age women using Ethiopian Demographic Health Survey (EDHS), 2019 data.
View Article and Find Full Text PDFBrain Behav
January 2025
Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada.
Introduction: Patients with bipolar disorder (BD) demonstrate episodic memory deficits, which may be hippocampal-dependent and may be attenuated in lithium responders. Induced pluripotent stem cell-derived CA3 pyramidal cell-like neurons show significant hyperexcitability in lithium-responsive BD patients, while lithium nonresponders show marked variance in hyperexcitability. We hypothesize that this variable excitability will impair episodic memory recall, as assessed by cued retrieval (pattern completion) within a computational model of the hippocampal CA3.
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