Optimizing Electronic Release of Imaging Results through an Online Patient Portal.

Purpose To determine an optimal embargo period preceding release of radiologic test results to an online patient portal. Materials and Methods This prospective discrete choice conjoint survey with modified orthogonal design was administered to patients by trained interviewers at four outpatient sites and two institutions from December 2016 to February 2018. Three preferences for receiving imaging results associated with a possible or known cancer diagnosis were evaluated: delay in receipt of results (1, 3, or 14 days), method of receipt (online portal, physician's office, or phone), and condition of receipt (before, at the same time as, or after health care provider). Preferences (hereafter, referred to as utilities) were derived from parameter estimates (ß) of multinomial regression stratified according to study participant and choice set. Results Among 464 screened participants, the response and completion rates were 90.5% (420 of 464) and 99.5% (418 of 420), respectively. Participants preferred faster receipt of results (P < .001) from their physician (P < .001) over the telephone (P < .001). Each day of delay decreased preference by 13 percentage points. Participants preferred immediate receipt of results through an online portal (utility, -.57) if made to wait more than 6 days to get results in the office and more than 11 days to get results by telephone. Compared with receiving results in their physician's office on day 7 (utility, -.60), participants preferred immediate release through the online portal without physician involvement if followed by a telephone call within 6 days (utility, -0.49) or an office visit within 2 days (utility, -.53). Older participants preferred physician-directed communication (P < .001). Conclusion The optimal embargo period preceding release of results through an online portal depends on the timing of traditional telephone- and office-based styles of communication. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Arenson et al in this issue.

Three-dimensional printing of patient-specific computed tomography lung phantoms: a reader study.

In modern clinical decision-support algorithms, heterogeneity in image characteristics due to variations in imaging systems and protocols hinders the development of reproducible quantitative measures including for feature extraction pipelines. With the help of a reader study, we investigate the ability to provide consistent ground-truth targets by using patient-specific 3D-printed lung phantoms. PixelPrint was developed for 3D-printing lifelike computed tomography (CT) lung phantoms by directly translating clinical images into printer instructions that control density on a voxel-by-voxel basis. Data sets of three COVID-19 patients served as input for 3D-printing lung phantoms. Five radiologists rated patient and phantom images for imaging characteristics and diagnostic confidence in a blinded reader study. Effect sizes of evaluating phantom as opposed to patient images were assessed using linear mixed models. Finally, PixelPrint's production reproducibility was evaluated. Images of patients and phantoms had little variation in the estimated mean (0.03-0.29, using a 1-5 scale). When comparing phantom images to patient images, effect size analysis revealed that the difference was within one-third of the inter- and intrareader variabilities. High correspondence between the four phantoms created using the same patient images was demonstrated by PixelPrint's production repeatability tests, with greater similarity scores between high-dose acquisitions of the phantoms than between clinical-dose acquisitions of a single phantom. We demonstrated PixelPrint's ability to produce lifelike CT lung phantoms reliably. These phantoms have the potential to provide ground-truth targets for validating the generalizability of inference-based decision-support algorithms between different health centers and imaging protocols and for optimizing examination protocols with realistic patient-based phantoms. Classification: CT lung phantoms, reader study.

Association of Thoracic MRI Findings With Specialty and Training.

STUDY DESIGN: Retrospective. OBJECTIVE: To compare the rate of positive pathology on thoracic MRI ordered by surgical spine specialists to those ordered by nonsurgical spine specialists. METHODS: Outpatient thoracic MRIs from January-March 2019 were evaluated from a single academic health care system. Studies without a known ordering provider, imaging report, or patients with known presence of malignancy, multiple sclerosis, recent trauma, or surgery were excluded (n = 320). Imaging studies were categorized by type of provider placing the order (resident, attending, or advanced practice practitioner) and department. MRIs were deemed positive if they showed relevant pathology that correlated with indication for exam as determined by a radiologist. One-sided chi-squared analysis was performed to determine statistical significance. RESULTS: Overall, our data demonstrated 17.2% of studies with positive pathology. Compared to nonspecialty clinicians, subspecialists showed 35/184 (19.0%) positivity rate versus the non-specialist with 20/136 (14.7%) positivity rate (P = .156). Posthoc analysis demonstrated that surgical specialists who order thoracic MRIs yield significantly higher positivity rates at 19/79 (24.0%) compared to nonsurgical specialists at 36/241 (14.9%) (P < .05). Overall, neurosurgery demonstrated the highest rate of positive thoracic MRIs at 14/40 (35.0%). Comparison between the rate of positivity between physicians and advanced practitioners was insignificant (P > .05). CONCLUSIONS: Clinical diagnosis of symptomatic thoracic spine degenerative disease requires an expert physical exam combined with careful attention to radiology findings. Although the percent of relevant pathology on thoracic MRI is low, our data suggests evaluation by a surgical specialist should precede ordering a thoracic spine MRI.