Objectives: This scoping review was conducted to determine the barriers and enablers associated with the acceptance of artificial intelligence/machine learning (AI/ML)-enabled innovations into radiology practice from a physician’s perspective. Methods: A systematic search was performed using Ovid Medline and Embase. Keywords were used to generate refined queries with the inclusion of computer-aided diagnosis, artificial intelligence, and barriers and enablers. Three reviewers assessed the articles, with a fourth reviewer used for disagreements. The risk of bias was mitigated by including both quantitative and qualitative studies. Results: An electronic search from January 2000 to 2023 identified 513 studies. Twelve articles were found to fulfill the inclusion criteria: qualitative studies (n = 4), survey studies (n = 7), and randomized controlled trials (RCT) (n = 1). Among the most common barriers to AI implementation into radiology practice were radiologists’ lack of acceptance and trust in AI innovations; a lack of awareness, knowledge, and familiarity with the technology; and perceived threat to the professional autonomy of radiologists. The most important identified AI implementation enablers were high expectations of AI’s potential added value; the potential to decrease errors in diagnosis; the potential to increase efficiency when reaching a diagnosis; and the potential to improve the quality of patient care. Conclusions: This scoping review found that few studies have been designed specifically to identify barriers and enablers to the acceptance of AI in radiology practice. The majority of studies have assessed the perception of AI replacing radiologists, rather than other barriers or enablers in the adoption of AI. To comprehensively evaluate the potential advantages and disadvantages of integrating AI innovations into radiology practice, gathering more robust research evidence on stakeholder perspectives and attitudes is essential.

BACKGROUND AND PURPOSE: Neuronal ceroid lipofuscinoses are a group of neurodegenerative disorders characterized by the accumulation of autofluorescent lipopigments in neuronal cells. As a result of storage material in the brain and retina, clinical manifestations include speech delay, cognitive dysfunction, motor regression, epilepsy, vision loss, and early death. At present, 14 different ceroid lipofuscinosis (CLN) genes are known. Recently, the FDA approved the use of recombinant human proenzyme of tripeptidyl-peptidase 1 for CLN2 disease, while phase I/IIa clinical trials for gene therapy in CLN3 and CLN6 are ongoing. Early diagnosis is, therefore, key to initiating treatment and arresting disease progression. Neuroimaging features of CLN1, CLN2, CLN3, and CLN5 diseases are well-described, with sparse literature on other subtypes. We aimed to investigate and expand the MR imaging features of genetically proved neuronal ceroid lipofuscinoses subtypes at our institution and also to report the time interval between the age of disease onset and the diagnosis of neuronal ceroid lipofuscinoses. MATERIALS AND METHODS: We investigated and analyzed the age of disease onset and neuroimaging findings (signal intensity in periventricular, deep, and subcortical white matter, thalami, basal ganglia, posterior limb of the internal capsule, insular/subinsular regions, and ventral pons; and the presence or absence of supratentorial and/or infratentorial atrophy) of patients with genetically proved neuronal ceroid lipofuscinoses at our institution. This group consisted of 24 patients who underwent 40 brain MR imaging investigations between 1993 and 2019, with a male preponderance (male/female ratio = 15:9). RESULTS: The mean ages of disease onset, first brain MR imaging, and diagnosis of neuronal ceroid lipofuscinoses were 4.70 ± 3.48 years, 6.76 ± 4.49 years, and 7.27 ± 4.78 years, respectively. Findings on initial brain MR imaging included T2/FLAIR hypointensity in the thalami (n = 22); T2/FLAIR hyperintensity in the periventricular and deep white matter (n = 22), posterior limb of the internal capsule (n = 22), ventral pons (n = 19), and insular/subinsular region (n = 18); supratentorial (n = 21) and infratentorial atrophy (n = 20). Eight of 9 patients who had follow-up neuroimaging showed progressive changes. CONCLUSIONS: We identified reported classic neuroimaging features in all except 1 patient with neuronal ceroid lipofuscinoses in our study. CLN2, CLN5, and CLN7 diseases showed predominant cerebellar-over-cerebral atrophy. We demonstrate that abnormal signal intensity in the deep white matter, posterior limb of the internal capsule, and ventral pons is more common than previously reported in the literature. We report abnormal signal intensity in the insular/subinsular region for the first time. The difference in the median time from disease onset and diagnosis was 1.5 years.

BACKGROUND AND PURPOSE: MRI is routinely performed following brain AVM after treatment in children. Our aim was to determine the predictive values of contrast-enhanced MR imaging and TOF-MRA for brain AVM recurrence in children, compared with conventional angiography and the role of 3D rotational angiography–MR imaging fusion in these cases. MATERIALS AND METHODS: We included all pediatric patients with brain AVMs during an 18-year period with angiographically documented obliteration after treatment. Patients underwent 3T MR imaging, including contrast-enhanced MR imaging, TOF-MRA, and conventional angiography, with a subset undergoing 3D rotational angiography. The predictive values of contrast-enhanced MR imaging and TOF-MRA for brain AVM recurrence were determined. CTA sections reconstructed from 3D rotational angiography were coregistered with and fused to 3D-T1WI for analysis. RESULTS: Thirty-nine children (10.8 ± 3.9 years of age; range, 2–17 years; male/female ratio, 19:20; mean Spetzler-Martin grade, 1.9 ± 0.6) met the inclusion criteria. Of these, 13 had angiographically confirmed brain AVM recurrence, 8 following surgery and 5 following embolization. Sensitivity, specificity, and positive and negative predictive values for recurrence were the following: contrast-enhanced MR imaging: 84.6%, 38.5%, 40.7%, 81.8%; TOF-MRA: 50.0%, 96.1%, 85.7%, 79.3%; both: 75.0%, 90.9%, 85.7%, 83.3%. 3D rotational angiography–MR imaging fused images confirmed or excluded recurrence in all available cases (13/13). Embolization-only treatment was a significant predictor of recurrence (OR = 32.4, P = .006). MR imaging features predictive of recurrence included a tuft of vessels on TOF-MRA and nodular juxtamural/linear enhancement with a draining vein on contrast-enhanced MR imaging. CONCLUSIONS: MR imaging is useful for surveillance after brain AVM treatment in children, but conventional angiography is required for definitive diagnosis of recurrence. TOF-MRA and contrast-enhanced MR imaging provide complementary information for determining brain AVM recurrence and should be interpreted in conjunction. 3D rotational angiography–MR imaging fusion increases the diagnostic confidence regarding brain AVM recurrence and is therefore suited for intraoperative neuronavigation.

Currently there is no consensus agreement on the degree of enhancement in normal temporomandibular joints (TMJ) in children, which makes it difficult for clinicians to distinguish between the presence/absence of mild synovitis. Quantitative measurements of synovial and condylar enhancement may be useful additions to current qualitative methods on early MRI diagnosis and follow up of TMJ involvement in JIA. The purpose of the study is to establish thresholds/tendencies for quantitative measures that enable distinction between mild TMJ involvement and normal TMJ appearance based on the degree of synovial and bone marrow enhancement in JIA patients. TMJ MRI examinations in 67 children with JIA and in 24 non-rheumatologic children who underwent MRI for neurologic/orbit indications were retrospectively assessed. As a priori determined TMJs of JIA patients were categorized into three groups by experienced staff radiologists based on the degree of synovial and condylar enhancement: no active disease (rheumatologic control), mild and moderate/severe findings. The signal intensity (SI) of the synovial tissue around each condyle and of the bone marrow was measured to calculate the enhancement ratio (ER) and relative SI change. The ER was calculated using signal to noise ratios, while relative SI change was calculated using signal intensities alone. Quantitative measurements of synovial and condylar enhancement of TMJs with mild or moderate/severe findings were compared with the rheumatologic and non-rheumatologic controls. Mean ER values were significantly different between the TMJs without active disease and those with mild and moderate/severe synovial enhancement, with highest values in the moderate/severe group (P < 0.0001). Similar findings were seen for condylar enhancement with P < 0.005. Relative SI change was unable to differentiate TMJs with mild synovitis from the two controls (P > 0.10). 27/60 (45 %) TMJs without active disease had osteochondral changes. 8/40 (20 %) TMJs in the mild group did not demonstrate any synovial thickening. Quantitative signal to noise ratios of TMJ synovial and condylar enhancement generate thresholds/tendencies, which offer additional information to differentiate mild synovitis from normal TMJs in JIA patients. Osteochondral changes and synovial thickening may not be reliable indicators of active TMJ involvement and should be differentiated from synovial enhancement.

OBJECTIVE. The purpose of this article is to evaluate virtual monochromatic spectral imaging and metal artifact reduction software for reducing metal artifact and to compare it with conventional single-energy CT (SECT) in an animal model. MATERIALS AND METHODS. Postmortem juvenile (n = 5) and adult (n = 1) swine specimens were scanned with SECT followed by a dual-energy CT (DECT) pediatric protocol after the insertion of two rods into their paraspinal thoracolumbar regions. Virtual monochromatic spectral images were extrapolated from DECT images at five monoenergetic levels (64, 69, 75, 88, and 105 keV) with and without the use of metal artifact reduction software. Images were evaluated by a 5-point scoring system for the extent of metallic artifacts and image interpretability in soft-tissue and bone windows. The density in the most pronounced artifact was measured. CT dose index was recorded. RESULTS. In studies without metal artifact reduction software, higher energy reconstructions resulted in fewer artifacts and better image interpretability in both soft-tissue and bone windows (p < 0.0001). Artifact density decreased from −792 HU at 64 keV to −128 HU at 105 keV without the use of metal artifact reduction software. No difference was noted in attributes' scores or in artifact density in studies using metal artifact reduction software (p > 0.05). DECT studies showed lower scores compared with SECT with regard to all attributes. A new faint perimetallic hypodense halo was seen in all studies with metal artifact reduction software. The CT dose index of DECT was 1.18–3.56 times higher than that of SECT techniques. CONCLUSION. DECT at all energy levels with metal artifact reduction software and higher energy extrapolations without metal artifact reduction software reduced metallic artifact and enhanced image interpretability compared with SECT. Radiation dose with DECT could be significantly higher than SECT.