Publications by authors named "Nazanin Yaghmai"
Integration and evaluation of chest X-ray artificial intelligence in clinical practice.
J Med Imaging (Bellingham)
September 2023
Purpose: To integrate and evaluate an artificial intelligence (AI) system that assists in checking endotracheal tube (ETT) placement on chest x-rays (CXRs) in clinical practice.
Approach: In clinical use over 17 months, 214 CXR images were ordered to check ETT placement with AI assistance by intensive care unit (ICU) physicians. The system was built on the SimpleMind Cognitive AI platform and integrated into a clinical workflow.
Purpose: To quantitatively and qualitatively assess the impact of attending neuroradiology coverage on radiology resident perceptions of the on-call experience, referring physician satisfaction, and final report turnaround times.
Materials And Methods: 24/7/365 attending neuroradiologist coverage began in October 2016 at our institution. In March 2017, an online survey of referring physicians, (emergency medicine, neurosurgery, and stroke neurology) and radiology residents was administered at a large academic medical center.
Rationale And Objectives: The purpose of this paper is to describe the integration of a commercial chest CT computer-aided detection (CAD) system into the clinical radiology reporting workflow and perform an initial investigation of its impact on radiologist efficiency. It seeks to complement research into CAD sensitivity and specificity of stand-alone systems, by focusing on report generation time when the CAD is integrated into the clinical workflow.
Materials And Methods: A commercial chest CT CAD software that provides automated detection and measurement of lung nodules, ascending and descending aorta, and pleural effusion was integrated with a commercial radiology report dictation application.
Objective: The aims of this study were to estimate the dose to radiosensitive organs (glandular breast and lung) in patients of various sizes undergoing routine chest CT examinations with and without tube current modulation; to quantify the effect of tube current modulation on organ dose; and to investigate the relation between patient size and organ dose to breast and lung resulting from chest CT examinations.
Materials And Methods: Thirty voxelized models generated from images of patients were extended to include lung contours and were used to represent a cohort of women of various sizes. Monte Carlo simulation-based virtual MDCT scanners had been used in a previous study to estimate breast dose from simulations of a fixed-tube-current and a tube current-modulated chest CT examinations of each patient model.
Tube current modulation was designed to reduce radiation dose in CT imaging while maintaining overall image quality. This study aims to develop a method for evaluating the effects of tube current modulation (TCM) on organ dose in CT exams of actual patient anatomy. This method was validated by simulating a TCM and a fixed tube current chest CT exam on 30 voxelized patient models and estimating the radiation dose to each patient's glandular breast tissue.
View Article and Find Full Text PDFPurpose: To use Monte Carlo simulations of a current-technology multidetector computed tomographic (CT) scanner to investigate fetal radiation dose resulting from an abdominal and pelvic examination for a range of actual patient anatomies that include variation in gestational age and maternal size.
Materials And Methods: Institutional review board approval was obtained for this HIPAA-compliant retrospective study. Twenty-four models of maternal and fetal anatomy were created from image data from pregnant patients who had previously undergone clinically indicated CT examination.