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Parkinson’s disease (PD) is a movement disorder that develops due to degenerative loss of dopaminergic cells in the substantia nigra of the midbrain. Recent advances in MRI techniques have demonstrated various imaging findings that can reflect the underlying pathophysiological processes occurring in Parkinson’s disease. Many imaging studies have shown that such findings can assist in the diagnosis of Parkinson’s disease and its differentiation from atypical parkinsonism. In this review, we present MRI techniques that can be used in clinical assessment, such as nigrosome imaging and neuromelanin imaging, and we provide the detailed imaging features of Parkinson’s disease reflecting nigrostriatal degeneration.

ObjectiveGrade II diffuse gliomas (DGs) with isocitrate dehydrogenase (IDH) mutations are associated with better prognosis than their IDH wild-type counterparts. We sought to determine the MRI characteristics associated with IDH mutational status and ascertain whether MRI considered in combination with IDH mutational status can better predict the clinical outcomes of grade II DGs.Materials and methodsPreoperative MRI examinations were retrospectively studied for qualitative tumor characteristics, including location, extent, cortical involvement, margin sharpness, cystic component, mineralization or hemorrhage, and contrast enhancement. Quantitative diffusion and perfusion metrics were also assessed. Logistic regression and ROC analyses were used to evaluate the relationship between MRI features and IDH mutational status. The association between IDH mutational status, 1p19q codeletion, MRI features, extent of resection, and clinical outcomes was assessed by Kaplan-Meier and Cox proportional hazards models.ResultsOf 100 grade II DGs, 78 were IDH mutant and 22 were IDH wild type. IDH wild-type tumors were associated with older age, multifocality, brainstem involvement, lack of cystic change, and a lower apparent diffusion coefficient (ADC). Multivariable regression showed that age older than 45 years as well as low minimum ADC (ADCmin), mean ADC, and maximum ADC values were independently associated with IDH mutational status. Of these, an ADCmin threshold of 0.9 × 10-3 mm2/s or less provided the greatest sensitivity and specificity (91% and 76%, respectively) in defining IDH wild-type grade II DGs. Combining low ADCmin with IDH wild-type status conferred worse outcomes than did IDH wild-type status alone.ConclusionIDH wild-type grade II DGs are associated with a lower ADC and poor clinical outcomes. Combining IDH mutational status and ADC may allow more accurate prediction of clinical outcomes for patients with grade II DGs.

Abstract Background An open‐label single‐arm phase 2 study was conducted to evaluate the role of levetiracetam as a sensitizer of concurrent chemoradiotherapy (CCRT) for patients with newly diagnosed glioblastoma. This study aimed to determine the survival benefit of levetiracetam in conjunction with the standard treatment for glioblastoma. Methods Major eligibility requirements included histologically proven glioblastoma in the supratentorial region, patients 18 years or older, and Eastern Cooperative Oncology Group (ECOG) performance status of 0–2. Levetiracetam was given at 1,000–2,000 mg daily in two divided doses during CCRT and adjuvant chemotherapy thereafter. The primary and the secondary endpoints were 6‐month progression‐free survival (6mo‐PFS) and 24‐month overall survival (24mo‐OS), respectively. Outcomes of the study group were compared to those of an external control group. Results Between July 2016 and January 2019, 76 patients were enrolled, and 73 patients were included in the final analysis. The primary and secondary outcomes were improved in the study population compared to the external control (6mo‐PFS, 84.9% vs. 72.3%, p = 0.038; 24mo‐OS, 58.0% vs. 39.9%, p = 0.018), but the differences were less prominent in a propensity score‐matched analysis (6mo‐PFS, 88.0% vs. 76.9%, p = 0.071; 24mo‐OS, 57.1% vs. 38.8%, p = 0.054). In exploratory subgroup analyses, some results suggested that patients with ages under 65 years or unmethylated MGMT promoter might have a greater survival benefit from the use of levetiracetam. Conclusions The use of levetiracetam during CCRT in patients with newly diagnosed glioblastoma may result in improved outcomes, but further investigations are warranted.

Abstract Temporalis muscle thickness (TMT) on brain magnetic resonance imaging (MRI) is correlated with sarcopenia and can be a predictive marker for survival in patients with brain tumors, but the association of TMT on head and neck computed tomography (CT) with survival in head and neck squamous cell carcinoma (HNSCC) remains unclear. We investigated whether TMT on CT could predict progression-free survival (PFS) in patients with HNSCC. A total of 106 patients with newly diagnosed HNSCC were included in this retrospective study. The patients underwent baseline head and neck CT and/or MRI between July, 2008 and August, 2018. The correlation between TMT on CT and MRI was tested using intraclass correlation coefficient (ICC). The cut-off value of TMT on CT for determining tumor progression was identified using receiver-operating characteristic curve analysis. Uni- and consecutive multi-variable Cox regression models were used to verify the association between TMT and PFS. TMT on CT and MRI showed excellent correlation (ICC, 0.894). After a mean follow-up of 37 months, 49 out of 106 patients showed locoregional recurrence and/or distant metastasis. The cut-off TMT of 6.47 mm showed good performance in predicting tumor progression (area under the curve, 0.779). The Cox regression model showed that TMT ≤ 6.24 mm (median value in study population) was a significant contributing factor for predicting shorter PFS (hazard ratio 0.399; 95% confidence interval 0.209–0.763; P = .005). TMT may be used as a surrogate parameter for pre-treatment sarcopenia and could help predict PFS in patients with HNSCC.

Abstract Autoimmune and autoinflammatory inner ear diseases (AIED/AID) are characterized by the symptom of sensorineural hearing loss (SNHL). To date, standardized diagnostic tools for AIED/AID are lacking, and clinically differentiating AIED/AID from chronic otitis media (COM) with SNHL is challenging. This retrospective study aimed to construct a magnetic resonance imaging (MRI)-based decision tree using classification and regression tree (CART) analysis to distinguish AIED/AID from COM. In total, 67 patients were enrolled between January 2004 and October 2019, comprising AIED/AID (n = 18), COM (n = 24), and control groups (n = 25). All patients underwent 3 T temporal bone MRI, including post-contrast T1-weighted images (postT1WI) and post-contrast FLAIR images (postFLAIR). Two radiologists evaluated the presence of otomastoid effusion and inner ear contrast-enhancement on MRI. A CART decision tree model was constructed using MRI features to differentiate AIED/AID from COM and control groups, and diagnostic performance was analyzed. High-intensity bilateral effusion (61.1%) and inner ear enhancement (postFLAIR, 93.8%; postT1WI, 61.1%) were the most common findings in the AIED/AID group. We constructed two CART decision tree models; the first used effusion amount as the first partitioning node and postT1WI-inner ear enhancement as the second node, whereas the second comprised two partitioning nodes with the degree of postFLAIR-enhancement of the inner ear. The first and second models enabled distinction of AIED/AID from COM with high specificity (100% and 94.3%, respectively). The amount of effusion and the degree of inner ear enhancement on MRI may facilitate the distinction between AIED/AID and COM with SNHL using decision tree models, thereby contributing to early diagnosis and intervention.

To train an automatic brain tumor segmentation model, a large amount of data is required. In this paper, we proposed a strategy to overcome the limited amount of clinically collected magnetic resonance image (MRI) data regarding meningiomas by pre-training a model using a larger public dataset of MRIs of gliomas and augmenting our meningioma training set with normal brain MRIs. Pre-operative MRIs of 91 meningioma patients (171 MRIs) and 10 non-meningioma patients (normal brains) were collected between 2016 and 2019. Three-dimensional (3D) U-Net was used as the base architecture. The model was pre-trained with BraTS 2019 data, then fine-tuned with our datasets consisting of 154 meningioma MRIs and 10 normal brain MRIs. To increase the utility of the normal brain MRIs, a novel balanced Dice loss (BDL) function was used instead of the conventional soft Dice loss function. The model performance was evaluated using the Dice scores across the remaining 17 meningioma MRIs. The segmentation performance of the model was sequentially improved via the pre-training and inclusion of normal brain images. The Dice scores improved from 0.72 to 0.76 when the model was pre-trained. The inclusion of normal brain MRIs to fine-tune the model improved the Dice score; it increased to 0.79. When employing BDL as the loss function, the Dice score reached 0.84. The proposed learning strategy for U-net showed potential for use in segmenting meningioma lesions.

BackgroundAlthough accurate treatment response assessment for brain metastases (BMs) is crucial, it is highly labor intensive. This retrospective study aimed to develop a computer-aided detection (CAD) system for automated BM detection and treatment response evaluation using deep learning.MethodsWe included 214 consecutive MRI examinations of 147 patients with BM obtained between January 2015 and August 2016. These were divided into the training (174 MR images from 127 patients) and test datasets according to temporal separation (temporal test set #1; 40 MR images from 20 patients). For external validation, 24 patients with BM and 11 patients without BM from other institutions were included (geographic test set). In addition, we included 12 MRIs from BM patients obtained between August 2017 and March 2020 (temporal test set #2). Detection sensitivity, dice similarity coefficient (DSC) for segmentation, and agreements in one-dimensional and volumetric Response Assessment in Neuro-Oncology Brain Metastases (RANO-BM) criteria between CAD and radiologists were assessed.ResultsIn the temporal test set #1, the sensitivity was 75.1% (95% confidence interval [CI]: 69.6%, 79.9%), mean DSC was 0.69 ± 0.22, and false-positive (FP) rate per scan was 0.8 for BM ≥ 5 mm. Agreements in the RANO-BM criteria were moderate (κ, 0.52) and substantial (κ, 0.68) for one-dimensional and volumetric, respectively. In the geographic test set, sensitivity was 87.7% (95% CI: 77.2%, 94.5%), mean DSC was 0.68 ± 0.20, and FP rate per scan was 1.9 for BM ≥ 5 mm. In the temporal test set #2, sensitivity was 94.7% (95% CI: 74.0%, 99.9%), mean DSC was 0.82 ± 0.20, and FP per scan was 0.5 (6/12) for BM ≥ 5 mm.ConclusionsOur CAD showed potential for automated treatment response assessment of BM ≥ 5 mm.

Purpose Although endovascular treatment is currently thought to only be suitable for patients who have pial arterial filling scores >3 as determined by multiphase computed tomography angiography (mpCTA), a cut-off score of 3 was determined by a study, including patients within 12 hours after symptom onset. We aimed to investigate whether a cut-off score of 3 for endovascular treatment within 6 hours of symptom onset is an appropriate predictor of good functional outcome at 3 months. Materials and Methods From April 2015 to January 2016, acute ischemic stroke patients treated with mechanical thrombectomy within 6 hours of symptom onset were enrolled into this study. Pial arterial filling scores were semi-quantitatively assessed using mpCTA, and clinical and radiological parameters were compared between patients with favorable and unfavorable outcomes. Multivariate logistic regression analysis was then performed to investigate the independent association between clinical outcome and pial collateral score, with the predictive power of the latter assessed using C-statistics. Results Of the 38 patients enrolled, 20 (52.6%) had a favorable outcome and 18 had an unfavorable outcome, with the latter group showing a lower mean pial arterial filling score (3.6±0.8 vs. 2.4±1.2, P=0.002). After adjusting for variables with a P-value of 2 vs. ≤2. Conclusion A pial arterial filling cut-off score of 2 as determined by mpCTA appears to be more suitable for predicting clinical outcomes following endovascular treatment within 6 hours of symptom onset than the cut-off of 3 that had been previously suggested.

Vanishing white matter (VWM) disease is an autosomal recessive disorder that affects the central nervous system of a patient, and is caused by the development of pathogenic mutations in any of the EIF2B1-5 genes. Any dysfunction of the EIF2B1-5 gene encoded eIF2B causes stress-provoked episodic rapid neurological deterioration in the patient, followed by a chronic progressive disease course. We present the case of a patient with an infantile-onset VWM with the pre-described specific clinical course, subsequent neurological aggravation induced by each viral infection, and the noted consequent progression into a comatose state. Although the initial brain magnetic resonance imaging did not reveal specific pathognomonic signs of VWM to distinguish it from other types of demyelinating leukodystrophy, the next-generation sequencing studies identified heterozygous missense variants in EIF2B3, including a novel variant in exon 7 (C706G), as well as a 0.008% frequency reported variant in exon 2 (T89C). Hence, the characteristic of unbiased genomic sequencing can clinically affect patient care and decisionmaking, especially in terms of the consideration of genetic disorders such as leukoencephalopathy in pediatric patients.

Background and Purpose: This systematic review and meta-analysis aimed to evaluate the pooled proportion of image findings of acute to subacute craniocervical arterial dissection (AD) direct signs on magnetic resonance vessel wall imaging (MR-VWI) and to identify factors responsible for the heterogeneity across the included studies.Methods: A systematic literature search in the Ovid-MEDLINE and EMBASE databases was performed for studies published on the relevant topic before April 14, 2020. Pooled sensitivity and specificity values and their 95% confidence intervals (CIs) were calculated using bivariate random-effects modeling. Meta-regression analyses were also performed to determine factors influencing heterogeneity.Results: Eleven articles with data for 209 patients with acute to subacute craniocervical AD who underwent MR-VWI were included in this systematic review and meta-analysis. The most common findings on MR-VWI were wall hematoma (84%; 95% CI, 71%−92%), abnormal enhancement (72%; 95% CI, 49%−88%), aneurysmal dilatation (71%, 95% CI, 53%−84%), and intimal flap or double lumen signs (49%; 95% CI, 29%−71%). Among the potential covariates of heterogeneity, the presence of contrast-enhanced T1-weighted imaging (CE-T1WI) within the MR-VWI sequence combination significantly affected the pooled proportion of the intimal flap or double lumen signs.Conclusion: Wall hematoma and intimal flap or double lumen signs were the most common and least common direct sign image findings, respectively, on MR-VWI in patients with acute to subacute craniocervical AD. Furthermore, the absence of CE-T1WI in MR-VWI protocol was the cause of heterogeneity for the detection of the intimal flap or double lumen signs. This data may help improve MR-VWI interpretation and enhance the understanding of the radiologic diagnosis of craniocervical AD.

ObjectivesTo determine the optimal utility of the open mouth maneuver and Metal Artifact Reduction for the Orthopedic Implants (O-MAR) technique for CT of the oral cavity and oropharynx.MethodsBetween July 2017 and May 2019, 59 subjects who underwent both conventional and open mouth head and neck CT scans were included in this retrospective study. All images were reconstructed using the O-MAR algorithm. With conventional CT with/without the O-MAR (CTc_O/CTc) and open mouth CT with/without O-MAR (CTo_O/CTo), one reader measured the noise level in multiple anatomic regions of the oral cavity and oropharynx. Visual scores for the streak artifact and overall subjective image quality were assessed by two independent readers.ResultsFor the mobile tongue, retromolar trigone, and palatine tonsil, the mean noise was significantly lower, and the mean visual scores were significantly higher, with CTo than with CTc or CTc_O (all, P < 0.001). The mean visual scores were higher with CTo_O than with CTo for the mobile tongue and palatine tonsil (all, P < 0.001). Contrarily, for the mouth floor and tongue base, the mean noise was significantly higher with CTo_O than with CTc or CTc_O, and the mean visual scores were significantly higher with CTc than with CTo or CTo_O (all, P < 0.001).ConclusionsThe open mouth maneuver and O-MAR technique can have different influences on the CT image quality according to the anatomical subsites of the oral cavity and oropharynx.

Granulomatosis with polyangiitis (GPA) can involve the skull base or the Eustachian tubes. GPA is diagnosed on the basis of clinical manifestations and serological tests, although it is challenging to discriminate GPA from infectious processes driving skull base osteomyelitis (SBO) and malignant processes such as nasopharyngeal carcinoma (NPC). Moreover, current serological tests have a low sensitivity and cannot distinguish GPA from these other conditions. We hypothesized that certain MRI characteristics would differ significantly among conditions and aimed to evaluate whether the features could differentiate between GPA, SBO, and NPC involving the skull base. We retrospectively evaluated the MRI findings of patients with GPA, SBO, and NPC. We performed univariable logistic regression analyses to identify the predictive variables for differentiating between conditions and evaluated their diagnostic values. We showed, for the first time, that certain MRI findings significantly differed between patients with GPA and those with SBO or NPC, including the lesion morphology and extent, the apparent diffusion coefficient (ADC) values, the contrast enhancement patterns, the presence or absence of necrosis, and retropharyngeal lymphadenopathy. In conclusion, utilizing certain MRI features can improve the diagnostic performance of MRI by differentiating GPA with skull base involvement from other conditions with similar radiologic findings, including SBO and NPC, facilitating treatment plans and, thus, improving patient outcomes.

Objectives: The aim of this study was to delineate the clinical and laboratory features suggestive of intralabyrinthine schwannoma (ILS).Methods: We compared the clinical features of 16 patients with ILS, who had been diagnosed at the Seoul National University Bundang Hospital from 2003 to 2018, with those of 18 patients with symptomatic unilateral intracanalicular schwannoma and randomly selected 20 patients with definite or probable unilateral Meniere's disease (MD).Results: Patients with ILS presented with either recurrent spontaneous dizziness/vertigo combined with auditory symptoms (n = 8), isolated auditory symptoms without dizziness/vertigo (n = 7), or recurrent spontaneous dizziness/vertigo without auditory symptoms (n = 1). Most patients reported no improvement (n = 11) or worsening (n = 1) of the symptoms despite medical treatments including intratympanic (n = 5) or intravenous steroids (n = 2). Conventional brain MRIs failed to detect ILS in about a half of the patients (7/16, 44%). However, ILS showed a filling defect on 3-dimensional (3D) heavily T2-weighted MRIs (n = 12), and nodular enhancement on 3D contrast-enhanced T1 (n = 15) or FLAIR MRIs (n = 13) targeted for the inner ear. Compared to MD or intracanalicular schwannoma, ILS showed mostly abnormal head-impulse tests (HITs, p = 0.001). In contrast, the incidence of canal paresis did not differ among the groups (p = 0.513).Conclusion: ILS may mimic MD by presenting recurrent dizziness/vertigo and auditory symptoms. ILS should be suspected in patients with recurrent audiovestibulopathy especially when (1) the duration of the dizziness is not typical for MD, (2) the patients do not respond to medical treatments, or (3) HITs are abnormal.

Accurate image interpretation of Waters’ and Caldwell view radiographs used for sinusitis screening is challenging. Therefore, we developed a deep learning algorithm for diagnosing frontal, ethmoid, and maxillary sinusitis on both Waters’ and Caldwell views. The datasets were selected for the training and validation set (n = 1403, sinusitis% = 34.3%) and the test set (n = 132, sinusitis% = 29.5%) by temporal separation. The algorithm can simultaneously detect and classify each paranasal sinus using both Waters’ and Caldwell views without manual cropping. Single- and multi-view models were compared. Our proposed algorithm satisfactorily diagnosed frontal, ethmoid, and maxillary sinusitis on both Waters’ and Caldwell views (area under the curve (AUC), 0.71 (95% confidence interval, 0.62–0.80), 0.78 (0.72–0.85), and 0.88 (0.84–0.92), respectively). The one-sided DeLong’s test was used to compare the AUCs, and the Obuchowski–Rockette model was used to pool the AUCs of the radiologists. The algorithm yielded a higher AUC than radiologists for ethmoid and maxillary sinusitis (p = 0.012 and 0.013, respectively). The multi-view model also exhibited a higher AUC than the single Waters’ view model for maxillary sinusitis (p = 0.038). Therefore, our algorithm showed diagnostic performances comparable to radiologists and enhanced the value of radiography as a first-line imaging modality in assessing multiple sinusitis.

Purpose Parallel imaging mitigates susceptibility artifacts that can adversely affect diffusion tensor tractography (DTT) of the pons depending on the reduction (R) factor. We aimed to find the optimal R factor for DTT of the pons that would allow us to visualize the largest possible number of pyramidal tract fibers. Materials and Methods Diffusion tensor imaging was performed on 10 healthy subjects at 3 Tesla based on single-shot echo-planar imaging using the following parameters: b value, 1000 s/mm2; gradient direction, 15; voxel size, 2 × 2 × 2 mm3; and R factors, 1, 2, 3, 4, and 5. DTT of the right and left pyramidal tracts in the pons was conducted in all subjects. Signal-to-noise ratio (SNR), image distortion, and the number of fibers in the tracts were compared across R factors. Results SNR, image distortion, and fiber number were significantly different according to R factor. Maximal SNR was achieved with an R factor of 2. Image distortion was minimal with an R factor of 5. The number of visible fibers was greatest with an R factor of 3. Conclusion R factor 3 is optimal for DTT of the pontine pyramidal tract. A balanced consideration of SNR and image distortion, which do not have the same dependence on the R factor, is necessary for DTT of the pons.

Background and Purpose Recent advances in intra-arterial techniques and thrombectomy devices lead to high rate of recanalization. However, little is known regarding the effect of the evolvement of endovascular revascularization therapy (ERT) in acute basilar artery occlusion (BAO). We compared the outcome of endovascular mechanical thrombectomy (EMT) versus intra-arterial fibrinolysis (IAF)-based ERT in patients with acute BAO. Methods After retrospectively reviewed a registry of consecutive patients with acute ischemic stroke who underwent ERT from September 2003 to February 2015, 57 patients with acute BAO within 12 hours from stroke onset were enrolled. They were categorized as an IAF group (n=24) and EMT group (n=33) according to the primary technical option. We compared the procedural and clinical outcomes between the groups. Results The time from groin puncture to recanalization was significantly shorter in the EMT group than in the IAF group (48.5 [25.3 to 87.8] vs. 92 [44 to 179] minutes; P=0.02) The rate of complete recanalization was significantly higher in the EMT group than in the IAF group (87.9% vs 41.7%; P

The duplicated origin of vertebral artery (VA) is a very rare condition. It could be easily misdiagnosed as an arterial dissection on selective catheter angiography, especially in a patient with acute cerebellar infarction of unknown etiology. We report a patient with an acute cerebellar infarction and duplicated origin of the left VA, which was found during the selective catheter angiography.

Background and Purpose Quantitative magnetic resonance angiography (Q-MRA) enables direct measurement of volume flow rate (VFR) of intracranial arteries. We aimed to evaluate the collateral flows in internal carotid artery (ICA) occlusion with primary collateral pathway via circle of Willis using Q-MRA, and to compare them between patients who recently developed ipsilateral symptomatic ischemia and those who did not. Methods Between 2012 and 2014, 505 patients underwent Q-MRA in our institution. Among these, 33 patients who had unilateral ICA occlusion with primary collateral pathway were identified, and grouped into asymptomatic patients, stable patients with chronic infarction, and symptomatic patients with acute/subacute infarction. Mean VFR (mVFR) in intracranial arteries was measured and compared between the patients’ groups. Kruskal-Wallis test was used for statistical analysis. Results Six patients were asymptomatic, fifteen with chronic infarction were stable, and twelve with acute/subacute infarction were symptomatic. The mVFR of ipsilateral middle cerebral artery in symptomatic patients was significantly lower than those in stable or asymptomatic patients (73.7±45.6 mL/min vs. 119.9±36.1 mL/min vs. 121.8±42.0 mL/min; P = 0.04). Total sum of the mVFR of ipsilateral anterior, middle, and posterior cerebral arteries was significantly lower in symptomatic patients than those in other groups (229.3 ± 51.3 mL/min vs. 282.0±68.6 mL/min vs. 314.0±44.4 mL/min; P = 0.02). Conclusions Q-MRA could be helpful to demonstrate the difference in the degree of primary collateral flow in ICA occlusion between the patients with recent symptomatic ischemia and those without.

To assess the effect of computer-aided detection (CAD) of brain metastasis (BM) on radiologists' diagnostic performance in interpreting three-dimensional brain magnetic resonance (MR) imaging using follow-up imaging and consensus as the reference standard.The institutional review board approved this retrospective study. The study cohort consisted of 110 consecutive patients with BM and 30 patients without BM. The training data set included MR images of 80 patients with 450 BM nodules. The test set included MR images of 30 patients with 134 BM nodules and 30 patients without BM. We developed a CAD system for BM detection using template-matching and K-means clustering algorithms for candidate detection and an artificial neural network for false-positive reduction. Four reviewers (two neuroradiologists and two radiology residents) interpreted the test set images before and after the use of CAD in a sequential manner. The sensitivity, false positive (FP) per case, and reading time were analyzed. A jackknife free-response receiver operating characteristic (JAFROC) method was used to determine the improvement in the diagnostic accuracy.The sensitivity of CAD was 87.3% with an FP per case of 302.4. CAD significantly improved the diagnostic performance of the four reviewers with a figure-of-merit (FOM) of 0.874 (without CAD) vs. 0.898 (with CAD) according to JAFROC analysis (p < 0.01). Statistically significant improvement was noted only for less-experienced reviewers (FOM without vs. with CAD, 0.834 vs. 0.877, p < 0.01). The additional time required to review the CAD results was approximately 72 sec (40% of the total review time).CAD as a second reader helps radiologists improve their diagnostic performance in the detection of BM on MR imaging, particularly for less-experienced reviewers.