Integration and evaluation of chest X-ray artificial intelligence in clinical practice.

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. It automatically identified the ETT and checked its placement relative to the trachea and carina. The ETT overlay and misplacement alert messages generated by the AI system were compared with radiology reports as the reference. A survey study was also conducted to evaluate usefulness of the AI system in clinical practice. Results: The alert messages indicating that either the ETT was misplaced or not detected had a positive predictive value of 42% (21/50) and negative predictive value of 98% (161/164) based on the radiology reports. In the survey, radiologist and ICU physician users indicated that they agreed with the AI outputs and that they were useful. Conclusions: The AI system performance in real-world clinical use was comparable to that seen in previous experiments. Based on this and physician survey results, the system can be deployed more widely at our institution, using insights gained from this evaluation to make further algorithm improvements and quality assurance of the AI system.

24/7/365 Neuroradiologist Coverage Improves Resident Perception of Educational Experience, Referring Physician Satisfaction, and Turnaround Time.

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. Referring physicians were queried regarding their perceptions of patient care, report accuracy, timeliness, and availability of attending radiologists before and after the implementation of overnight neuroradiology coverage. Radiology residents were asked about their level of independence, workload, and education while on-call. Turnaround time (TAT) was measured over a 5-month period before and after the implementation of overnight neuroradiology coverage. RESULTS: A total of 28 of 64 referring physicians surveyed responded, for a response rate of 67%. Specifically, 19 of 23 second (junior resident on-call) and third year radiology residents (senior resident on-call) replied, 4 of 4 stroke neurology fellows replied, 8 of 21 neurosurgery residents, and 16 of 39 emergency medicine residents replied. Ninety-five percent of radiology residents stated they had adequate independence on call, 100% felt they have enough faculty support while on call, and 84% reported that overnight attending coverage has improved the educational value of their on-call experience. Residents who were present both before and after the implementation of TAT metrics thought their education, and independence had been positively affected. After overnight neuroradiology coverage, 85% of emergency physicians perceived improved accuracy of reports, 69% noted improved timeliness, and 77% found that attending radiologists were more accessible for consultation. The surveyed stroke neurology fellows and neurosurgery residents reported positive perception of the TAT, report quality, and availability of accessibility of attending radiologist. CONCLUSIONS: In concordance with prior results, overnight attending coverage significantly reduced turnaround time. As expected, referring physicians report increased satisfaction with overnight attending coverage, particularly with respect to patient care and report accuracy. In contrast to some prior studies, radiology residents reported both improved educational value of the on-call shifts and preserved independence. This may be due to the tasking the overnight neuroradiology attending with dual goals of optimized TAT, and trainee growth. Unique implementation including subspecialty trained attendings may facilitate radiology resident independence and educational experience with improved finalized report turnaround.

Integration of Chest CT CAD into the Clinical Workflow and Impact on Radiologist Efficiency.

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. The CAD system automatically prepopulated a radiology report template, thus offering the potential for increased efficiency. The integrated system was evaluated using 40 scans from a publicly available lung nodule database. Each scan was read using two methods: (1) without CAD analytics, i.e., manually populated report with measurements using electronic calipers, and (2) with CAD analytics to prepopulate the report for reader review and editing. Three radiologists participated as readers in this study. RESULTS: CAD assistance reduced reading times by 7%-44%, relative to the conventional manual method, for the three radiologists from opening of the case to signing of the final report. CONCLUSION: This study provides an investigation of the impact of CAD and measurement on chest CTs within a clinical reporting workflow. Prepopulation of a report with automated nodule and aorta measurements yielded substantial time savings relative to manual measurement and entry.

Dose to radiosensitive organs during routine chest CT: effects of tube current modulation.

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. In this study, lung doses were estimated for each simulated examination, and the percentage organ dose reduction attributed to tube current modulation was correlated with patient size for both glandular breast and lung tissues. RESULTS: The average radiation dose to lung tissue from a chest CT scan obtained with fixed tube current was 23 mGy. The use of tube current modulation reduced the lung dose an average of 16%. Reductions in organ dose (up to 56% for lung) due to tube current modulation were more substantial among smaller patients than larger. For some larger patients, use of tube current modulation for chest CT resulted in an increase in organ dose to the lung as high as 33%. For chest CT, lung dose and breast dose estimates had similar correlations with patient size. On average the two organs receive approximately the same dose effects from tube current modulation. CONCLUSION: The dose to radiosensitive organs during fixed-tube-current and tube current-modulated chest CT can be estimated on the basis of patient size. Organ dose generally decreases with the use of tube current-modulated acquisition, but patient size can directly affect the dose reduction achieved.

Monte Carlo simulations to assess the effects of tube current modulation on breast dose for multidetector CT.

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. This new method for estimating organ dose was compared with other conventional estimates of dose reduction. Thirty detailed voxelized models of patient anatomy were created based on image data from female patients who had previously undergone clinically indicated CT scans including the chest area. As an indicator of patient size, the perimeter of the patient was measured on the image containing at least one nipple using a semi-automated technique. The breasts were contoured on each image set by a radiologist and glandular tissue was semi-automatically segmented from this region. Previously validated Monte Carlo models of two multidetector CT scanners were used, taking into account details about the source spectra, filtration, collimation and geometry of the scanner. TCM data were obtained from each patient's clinical scan and factored into the model to simulate the effects of TCM. For each patient model, two exams were simulated: a fixed tube current chest CT and a tube current modulated chest CT. X-ray photons were transported through the anatomy of the voxelized patient models, and radiation dose was tallied in the glandular breast tissue. The resulting doses from the tube current modulated simulations were compared to the results obtained from simulations performed using a fixed mA value. The average radiation dose to the glandular breast tissue from a fixed tube current scan across all patient models was 19 mGy. The average reduction in breast dose using the tube current modulated scan was 17%. Results were size dependent with smaller patients getting better dose reduction (up to 64% reduction) and larger patients getting a smaller reduction, and in some cases the dose actually increased when using tube current modulation (up to 41% increase). The results indicate that radiation dose to glandular breast tissue generally decreases with the use of tube current modulated CT acquisition, but that patient size (and in some cases patient positioning) may affect dose reduction.

Radiation dose to the fetus for pregnant patients undergoing multidetector CT imaging: Monte Carlo simulations estimating fetal dose for a range of gestational age and patient size.

PURPOSE: 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. Gestational age ranged from less than 5 weeks to 36 weeks. Simulated helical scans of the abdominal and pelvic region were performed, and a normalized dose (in milligrays per 100 mAs) was calculated for each fetus. Stepwise multiple linear regression was performed to analyze the correlation of dose with gestational age and anatomic measurements of maternal size and fetal location. Results were compared with several existing fetal dose estimation methods. RESULTS: Normalized fetal dose estimates from the Monte Carlo simulations ranged from 7.3 to 14.3 mGy/100 mAs, with an average of 10.8 mGy/100 mAs. Previous methods yielded values of 10-14 mGy/100 mAs. The correlation between gestational age and fetal dose was not significant (P = .543). Normalized fetal dose decreased linearly with increasing patient perimeter (R(2) = 0.681, P < .001), and a two-factor model with patient perimeter and fetal depth demonstrated a strong correlation with fetal dose (R(2) = 0.799, P < .002). CONCLUSION: A method for the estimation of fetal dose from models of actual patient anatomy that represented a range of gestational age and patient size was developed. Fetal dose correlated with maternal perimeter and varied more than previously recognized. This correlation improves when maternal size and fetal depth are combined.