Background
Theoretically, artificial intelligence can provide an accurate automatic solution to measure right ventricular (RV) ejection fraction (RVEF) from cardiovascular magnetic resonance (CMR) images, despite the complex RV geometry. However, in our recent study, commercially available deep learning (DL) algorithms for RVEF quantification performed poorly in some patients. The current study was designed to test the hypothesis that quantification of RV function could be improved in these patients by using more diverse CMR datasets in addition to domain-specific quantitative performance evaluation metrics during the cross-validation phase of DL algorithm development.
Methods
We identified 100 patients from our prior study who had the largest differences between manually measured and automated RVEF values. Automated RVEF measurements were performed using the original version of the algorithm (DL1), an updated version (DL2) developed from a dataset that included a wider range of RV pathology and validated using multiple domain-specific quantitative performance evaluation metrics, and conventional methodology performed by a core laboratory (CORE). Each of the DL-RVEF approaches was compared against CORE-RVEF reference values using linear regression and Bland–Altman analyses. Additionally, RVEF values were classified into 3 categories: ≤ 35%, 35–50%, and ≥ 50%. Agreement between RVEF classifications made by the DL approaches and the CORE measurements was tested.
Results
CORE-RVEF and DL-RVEFs were obtained in all patients (feasibility of 100%). DL2-RVEF correlated with CORE-RVEF better than DL1-RVEF (r = 0.87 vs. r = 0.42), with narrower limits of agreement. As a result, DL2 algorithm also showed increasing accuracy from 0.53 to 0.80 for categorizing RV function.
Conclusions
The use of a new DL algorithm cross-validated on a dataset with a wide range of RV pathology using multiple domain-specific metrics resulted in a considerable improvement in the accuracy of automated RVEF measurements. This improvement was demonstrated in patients whose images were the most challenging and resulted in the largest RVEF errors. These findings underscore the critical importance of this strategy in the development of DL approaches for automated CMR measurements.
Study Design:
Prospective cohort study.
Summary of Background Data:
C-arm fluoroscopy and O-arm navigation are vital tools in modern spine surgeries, but their repeated usage can endanger spine surgeons. Although a surgeon’s chest and abdomen are protected by lead aprons, the eyes and extremities generally receive less protection.
Objective:
In this study, we compare differences in intraoperative radiation exposure across the protected and unprotected regions of a surgeon’s body.
Methods:
Sixty-five consecutive spine surgeries were performed by a single spine-focused neurosurgeon over 9 months. Radiation exposure to the primary surgeon was measured through dosimeters worn over the lead apron, under the lead apron, on surgical loupes, and as a ring on the dominant hand. Differences were assessed with rigorous statistical testing and radiation exposure per surgical case was extrapolated.
Results:
During the study, the measured radiation exposure over the apron, 176 mrem, was significantly greater than that under the apron, 8 mrem (P = 0.0020), demonstrating a shielding protective effect. The surgeon’s dominant hand was exposed to 329 mrem whereas the eyes were exposed to 152.5 mrem of radiation. Compared with the surgeon’s protected abdominal area, the hands (P = 0.0002) and eyes (P = 0.0002) received significantly greater exposure. Calculated exposure per case was 2.8 mrem for the eyes and 5.1 mrem for the hands. It was determined that a spine-focused neurosurgeon operating 400 cases annually will incur a radiation exposure of 60,750 mrem to the hands and 33,900 mrem to the eyes over a 30-year career.
Conclusions:
Our study found that spine surgeons encounter significantly more radiation exposure to the eyes and the extremities compared with protected body regions. Lifetime exposure exceeds the annual limits set by the International Commission on Radiologic Protection for the extremities (50,000 mrem/y) and the eyes (15,000 mrem/y), calling for increased awareness about the dangerous levels of radiation exposure that a spine surgeon incurs over one’s career.
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