Deep learning-based multimodal segmentation of oropharyngeal squamous cell carcinoma on CT and MRI using self-configuring nnU-Net.

PURPOSE: To evaluate deep learning-based segmentation models for oropharyngeal squamous cell carcinoma (OPSCC) using CT and MRI with nnU-Net. METHODS: This single-center retrospective study included 91 patients with OPSCC. The patients were grouped into the development (n = 56), test 1 (n = 13), and test 2 (n = 22) cohorts. In the development cohort, OPSCC was manually segmented on CT, MR, and co-registered CT-MR images, which served as the ground truth. The multimodal and multichannel input images were then trained using a self-configuring nnU-Net. For evaluation metrics, dice similarity coefficient (DSC) and mean Hausdorff distance (HD) were calculated for test cohorts. Pearson's correlation and Bland-Altman analyses were performed between ground truth and prediction volumes. Intraclass correlation coefficients (ICCs) of radiomic features were calculated for reproducibility assessment. RESULTS: All models achieved robust segmentation performances with DSC of 0.64 ± 0.33 (CT), 0.67 ± 0.27 (MR), and 0.65 ± 0.29 (CT-MR) in test cohort 1 and 0.57 ± 0.31 (CT), 0.77 ± 0.08 (MR), and 0.73 ± 0.18 (CT-MR) in test cohort 2. No significant differences were found in DSC among the models. HD of CT-MR (1.57 ± 1.06 mm) and MR models (1.36 ± 0.61 mm) were significantly lower than that of the CT model (3.48 ± 5.0 mm) (p = 0.037 and p = 0.014, respectively). The correlation coefficients between the ground truth and prediction volumes for CT, MR, and CT-MR models were 0.88, 0.93, and 0.9, respectively. MR models demonstrated excellent mean ICCs of radiomic features (0.91-0.93). CONCLUSION: The self-configuring nnU-Net demonstrated reliable and accurate segmentation of OPSCC on CT and MRI. The multimodal CT-MR model showed promising results for the simultaneous segmentation on CT and MRI. CLINICAL RELEVANCE STATEMENT: Deep learning-based automatic detection and segmentation of oropharyngeal squamous cell carcinoma on pre-treatment CT and MRI would facilitate radiologic response assessment and radiotherapy planning. KEY POINTS: • The nnU-Net framework produced a reliable and accurate segmentation of OPSCC on CT and MRI. • MR and CT-MR models showed higher DSC and lower Hausdorff distance than the CT model. • Correlation coefficients between the ground truth and predicted segmentation volumes were high in all the three models.

MR-self Noise2Noise: self-supervised deep learning-based image quality improvement of submillimeter resolution 3D MR images.

OBJECTIVES: The study aimed to develop a deep neural network (DNN)-based noise reduction and image quality improvement by only using routine clinical scans and evaluate its performance in 3D high-resolution MRI. METHODS: This retrospective study included T1-weighted magnetization-prepared rapid gradient-echo (MP-RAGE) images from 185 clinical scans: 135 for DNN training, 11 for DNN validation, 20 for qualitative evaluation, and 19 for quantitative evaluation. Additionally, 18 vessel wall imaging (VWI) data were included to evaluate generalization. In each scan of the DNN training set, two noise-independent images were generated from the k-space data, resulting in an input-label pair. 2.5D U-net architecture was utilized for the DNN model. Qualitative evaluation between conventional MP-RAGE and DNN-based MP-RAGE was performed by two radiologists in image quality, fine structure delineation, and lesion conspicuity. Quantitative evaluation was performed with full sampled data as a reference by measuring quantitative error metrics and volumetry at 7 different simulated noise levels. DNN application on VWI was evaluated by two radiologists in image quality. RESULTS: Our DNN-based MP-RAGE outperformed conventional MP-RAGE in all image quality parameters (average scores = 3.7 vs. 4.9, p < 0.001). In the quantitative evaluation, DNN showed better error metrics (p < 0.001) and comparable (p > 0.09) or better (p < 0.02) volumetry results than conventional MP-RAGE. DNN application to VWI also revealed improved image quality (3.5 vs. 4.6, p < 0.001). CONCLUSION: The proposed DNN model successfully denoises 3D MR image and improves its image quality by using routine clinical scans only. KEY POINTS: • Our deep learning framework successfully improved conventional 3D high-resolution MRI in all image quality parameters, fine structure delineation, and lesion conspicuity. • Compared to conventional MRI, the proposed deep neural network-based MRI revealed better quantitative error metrics and comparable or better volumetry results. • Deep neural network application to 3D MRI whose pulse sequences and parameters were different from the training data showed improvement in image quality, revealing the potential to generalize on various clinical MRI.

Identification of the intraparotid facial nerve on MRI: a systematic review and meta-analysis.

OBJECTIVES: Accurate preoperative localization of the intraparotid facial nerve (IFN) on MRI could reduce intraoperative injury. This study aimed to assess the detection rate of the IFN and its branches on MRI. METHODS: PubMed-MEDLINE and Embase databases were searched for articles published up to October 2019. The inclusion criteria were (a) adults, (b) MRI-based identification of IFN by radiologists, (c) original articles, and (d) detailed results to assess the proportion of visible IFN. Two radiologists reviewed the original articles. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to determine the quality of the selected studies. The DerSimonian-Laird random effects model was utilized to calculate the pooled estimates. Between-studies heterogeneity was evaluated using the chi-squared statistic test and Higgins' inconsistency index (I2). A subgroup meta-regression was performed to explore the factors causing study heterogeneity. RESULTS: Nine original articles with 209 subjects were included. MRI reported a high pooled detection rate of 99.8% (95% CI, 98.4-100%) for the main trunk of the IFN. The pooled rates for the temporofacial and cervicofacial branches were 90.4% (95% CI, 84.1-96.7%) and 96.3% (95% CI, 96.1-99.5%), respectively. Heterogeneity was detected only in the temporofacial branch (I2 = 83%) as a result of both slice thickness and the use of steady-state sequences with diffusion-weighted imaging (DWI) implementation. CONCLUSIONS: MRI showed an overall high detection rate of the IFN and its branches. Furthermore, an increased identification was observed in studies that used a slice thickness of < 1 mm and steady-state sequences with DWI implementation. KEY POINTS: • MRI showed an overall high detection rate of the intraparotid facial nerve and its branches. • Higher detection rate was observed in studies that used a slice thickness of < 1 mm and steady-state sequences with diffusion-weighted imaging.

Radiomics may increase the prognostic value for survival in glioblastoma patients when combined with conventional clinical and genetic prognostic models.

OBJECTIVES: To evaluate the additional prognostic value of multiparametric MR-based radiomics in patients with glioblastoma when combined with conventional clinical and genetic prognostic factors. METHODS: In this single-center study, patients diagnosed with glioblastoma between October 2007 and December 2019 were retrospectively screened and grouped into training and test sets with a 7:3 distribution. Segmentations of glioblastoma using multiparametric MRI were performed automatically via a convolutional-neural network. Prognostic factors in the clinical model included age, sex, type of surgery/post-operative treatment, and tumor location; those in the genetic model included statuses of isocitrate dehydrogenase-1 mutation and O-6-methylguanine-DNA-methyltransferase promoter methylation. Univariate and multivariate Cox proportional hazards analyses were performed for overall survival (OS) and progression-free survival (PFS). Integrated time-dependent area under the curve (iAUC) for survival was calculated and compared between prognostic models via the bootstrapping method (performances were validated with prediction error curves). RESULTS: Overall, 120 patients were included (training set, 85; test set, 35). The mean OS and PFS were 25.5 and 18.6 months, respectively. The prognostic performances of multivariate models improved when radiomics was added to the clinical model (iAUC: OS, 0.62 to 0.73; PFS, 0.58 to 0.66), genetic model (iAUC: OS, 0.59 to 0.67; PFS, 0.59 to 0.65), and combined model (iAUC: OS, 0.65 to 0.73; PFS, 0.62 to 0.67). In the test set, the combined model (clinical, genetic, and radiomics) demonstrated robust validation for risk prediction of OS and PFS. CONCLUSIONS: Radiomics increased the prognostic value when combined with conventional clinical and genetic prognostic models for OS and PFS in glioblastoma patients. KEY POINTS: • CNN-based automatic segmentation of glioblastoma on multiparametric MRI was useful in extracting radiomic features. • Patients with glioblastoma with high-risk radiomics scores had poor overall survival (hazards ratio 8.33, p < 0.001) and progression-free survival (hazards ratio 3.76, p < 0.001). • MR-based radiomics improved the survival prediction when combined with clinical and genetic factors (overall and progression-free survival iAUC from 0.65 to 0.73 and 0.62 to 0.67, respectively; both p < 0.001).

MRI-visible dilated perivascular spaces in healthy young adults: A twin heritability study.

We investigated the narrow-sense heritability of MRI-visible dilated perivascular spaces (dPVS) in healthy young adult twins and nontwin siblings (138 monozygotic, 79 dizygotic twin pairs, and 133 nontwin sibling pairs; 28.7 ± 3.6 years) from the Human Connectome Project. dPVS volumes within basal ganglia (BGdPVS) and white matter (WMdPVS) were automatically calculated on three-dimensional T2-weighted MRI. In univariate analysis, heritability estimates of BGdPVS and WMdPVS after age and sex adjustment were 65.8% and 90.2%. In bivariate analysis, both BGdPVS and WMdPVS showed low to moderate genetic correlations (.30-.43) but high shared heritabilities (71.8-99.9%) with corresponding regional volumes, intracranial volumes, and other regional dPVS volumes. Older age was significantly associated with larger dPVS volume in both regions even after adjusting for clinical and volumetric variables, while blood pressure was not associated with dPVS volume although there was weak genetic correlation. dPVS volume, particularly WMdPVS, was highly heritable in healthy young adults, adding evidence of a substantial genetic contribution in dPVS development and differential effect by location. Age affects dPVS volume even in young adults, while blood pressure might have limited role in dPVS development in its normal range.

MRI and Quantitative Magnetic Susceptibility Maps of the Brain after Serial Administration of Gadobutrol: A Longitudinal Follow-up Study.

Background The relationship between administration of macrocyclic gadolinium-based contrast agents and T1-weighted signal intensity (SI) change of the globus pallidus (GP) and dentate nucleus (DN) is, to the knowledge of the authors, not known. Purpose To determine if quantitative susceptibility mapping (QSM) can detect changes in magnetic susceptibility of the GP and DN after serial administration of macrocyclic gadobutrol in patients with primary brain tumors. Materials and Methods Patients diagnosed with primary brain tumors from August 2014 to February 2019 were eligible for this single-center retrospective study. Among 501 consecutive adult patients who were given at least one administration of gadobutrol, those who were previously administered an unknown or linear gadolinium-based contrast agent were excluded. Brain MRI scans with three-dimensional gradient-recalled-echo image phase data for QSM processing were reviewed. Regions of interest were drawn on the GP and DN on the basis of semiautomatic thresholding. Univariable generalized estimation equations were used to determine the associations between MRI measures (SI on T1-weighted images and magnetic susceptibility on QSM) and number of gadobutrol doses. Potential confounding factors were adjusted for in multivariable generalized estimating equation. Results Ninety patients (mean age, 51 years ± 17 [standard deviation]; 51 men) with 199 MRI scans were analyzed. In models adjusted for repeated observations between injections, the number of injections of gadobutrol was associated with the magnetic susceptibility of the GP (1.4 × 10-3 ppm/number of gadobutrol injections; P = .01) and DN (8.1 × 10-4 ppm/number of gadobutrol injections; P = .03). After adjustment for confounders, the number of gadobutrol injections remained an independent predictor of increased magnetic susceptibility in the GP (1.3 × 10-3 ppm/number of gadobutrol injections; 95% confidence interval: 0.39 × 10-3, -2.4 × 10-3; P = .006). There were no associations between number of gadobutrol injections and SI or magnetic susceptibility in the DN. Conclusion The magnetic susceptibility of the globus pallidus increased after serial administration of gadobutrol. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Wang and Prince in this issue.

Dual-energy CT for differentiating acute intracranial hemorrhage from contrast staining or calcification: a meta-analysis.

PURPOSE: This study aimed to comprehensively evaluate the diagnostic performance of dual-energy CT (DECT) for differentiating acute intracranial hemorrhage (ICH) from contrast staining or small calcifications via a systematic review and meta-analysis. METHODS: The PubMed-MEDLINE, EMBASE, and Cochrane Library databases were searched up to November 10, 2019. Original studies (prospective or retrospective cohort studies) with the primary aim of detecting ICH using DECT were selected. The diagnostic performance of DECT was assessed using bivariate and hierarchical summary receiver operating characteristic models. Quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies-2, while between-study heterogeneity was assessed using Higgins' inconsistency index (I2). To explore heterogeneity, subgroup meta-regression analyses were performed. Deeks' funnel plot asymmetry test was used for assessing publication bias. RESULTS: Nine studies comprising 402 patients with 453 lesions were included for data synthesis. The overall pooled sensitivity and specificity of DECT for ICH detection were 96% (95% CI, 77-99%) and 98% (95 CI, 93%-100%), respectively. Substantial and moderate between-study heterogeneities were observed for sensitivity (I2 = 90.3%) and specificity (I2 = 57.9%), respectively. In meta-regression analysis, type of cohort affected heterogeneity-studies including only stroke patients showed lower sensitivity (43.5% vs. 94.2%) but higher specificity (98.7% vs. 92.6%) than those with mixed etiologies (P < 0.001). Deeks' funnel plot asymmetry test revealed publication bias (P = 0.020). CONCLUSION: DECT demonstrated excellent diagnostic performance in terms of differentiating acute ICH from contrast staining and small calcifications. However, publication bias suggests the possibility of overestimated diagnostic performance, warranting large-scale, prospective cohort studies.

CT-based quantitative evaluation of the efficacy after radiofrequency ablation in patients with benign thyroid nodules.

OBJECTIVE: The purpose of this study was to evaluate the usefulness of CT for quantitative assessment of the neck structures after RFA in patients with benign thyroid nodules. MATERIALS AND METHODS: This single-center, retrospective cohort study included 38 patients with benign thyroid nodules who had received RFA and had available pre- and post-treatment CT images. Changes in the tracheal anteroposterior (AP)/transverse diameter ratio, cross-sectional tracheal area, midline deviation of the trachea, and anterior neck angle after RFA were quantitatively measured using CT. Volume reduction rates (VRRs) for the thyroid gland and nodules were measured using CT and US, respectively, and the intraclass correlation coefficient (ICC) was calculated. The paired Wilcoxon signed-rank test was used to compare pre- and post-treatment CT-based measurements, and univariate linear regression analysis was performed to determine the association of VRR with the mean delivered radiofrequency energy, number of RFA sessions, and initial thyroid volume. RESULTS: After RFA, the tracheal AP/transverse diameter ratio and midline deviation were significantly decreased while the tracheal area and anterior neck angle were significantly increased (all, p < 0.001). The thyroid volume reduction was also significant (VRR, 42.1% ± 21.1%, p < 0.001), with moderate consistency between the CT-based thyroid VRR and US-based nodule VRR (ICC = 0.68, 95% confidence interval = 0.38-0.83, p < 0.001). The mean delivered radiofrequency energy (p = 0.565), number of RFA sessions (p = 0.209), and initial thyroid volume (p = 0.363) showed no significant association with VRR. CONCLUSION: CT-based quantitative assessments may be useful for evaluating improvements in the neck structures after RFA for benign thyroid nodules.

Comparison of efficacy and complications between radiofrequency ablation and repeat surgery in the treatment of locally recurrent thyroid cancers: a single-center propensity score matching study.

PURPOSE: To compare the efficacy and complication rates of radiofrequency ablation (RFA) and repeat surgery in the treatment of locally recurrent thyroid cancers. MATERIALS AND METHODS: A total of 221 patients with locally recurrent thyroid cancers who underwent either RFA (n = 96) or repeat surgery (n = 125) between March 2008 and March 2017 were retrospectively enrolled (range of follow-up, 1-10 years). Each cohort consisted of 70 patients after propensity score adjustment. Patients with more than three recurrent lesions were excluded. The primary and secondary end points were recurrence-free survival and complication rates, respectively. Recurrence-free survival curves were compared via the log-rank test. The complications-voice changes, hypocalcemia, and immediate procedural complications-were compared between the groups. In addition, pretreatment serum thyroglobulin (Tg) levels and those at the last follow-up were also compared between the two groups to examine therapeutic efficacy. RESULTS: After propensity score matching, both groups showed no significant differences in baseline characteristics. The recurrence-free survival rates were comparable between the RFA and surgery groups (p = .2). There were no significant differences in mean serum Tg levels and their mean decrease after treatment between the groups (p = .891 and p = .963, respectively). Immediate procedural complications and voice changes also showed no significant between-group differences (p = .316, p = .084, respectively). Hypocalcemia occurred only in the repeat surgery group (n = 18). Overall complications were significantly more frequent in the repeat surgery group (RFA, n = 7; surgery, n = 27; p < .001). CONCLUSION: RFA may be an effective and safe alternative to repeat surgery in the treatment of a small number of locally recurrent thyroid cancers.

Improving Diagnostic Performance of MRI for Temporal Lobe Epilepsy With Deep Learning-Based Image Reconstruction in Patients With Suspected Focal Epilepsy.

OBJECTIVE: To evaluate the diagnostic performance and image quality of 1.5-mm slice thickness MRI with deep learning-based image reconstruction (1.5-mm MRI + DLR) compared to routine 3-mm slice thickness MRI (routine MRI) and 1.5-mm slice thickness MRI without DLR (1.5-mm MRI without DLR) for evaluating temporal lobe epilepsy (TLE). MATERIALS AND METHODS: This retrospective study included 117 MR image sets comprising 1.5-mm MRI + DLR, 1.5-mm MRI without DLR, and routine MRI from 117 consecutive patients (mean age, 41 years; 61 female; 34 patients with TLE and 83 without TLE). Two neuroradiologists evaluated the presence of hippocampal or temporal lobe lesions, volume loss, signal abnormalities, loss of internal structure of the hippocampus, and lesion conspicuity in the temporal lobe. Reference standards for TLE were independently constructed by neurologists using clinical and radiological findings. Subjective image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were analyzed. Performance in diagnosing TLE, lesion findings, and image quality were compared among the three protocols. RESULTS: The pooled sensitivity of 1.5-mm MRI + DLR (91.2%) for diagnosing TLE was higher than that of routine MRI (72.1%, P < 0.001). In the subgroup analysis, 1.5-mm MRI + DLR showed higher sensitivity for hippocampal lesions than routine MRI (92.7% vs. 75.0%, P = 0.001), with improved depiction of hippocampal T2 high signal intensity change (P = 0.016) and loss of internal structure (P < 0.001). However, the pooled specificity of 1.5-mm MRI + DLR (76.5%) was lower than that of routine MRI (89.2%, P = 0.004). Compared with 1.5-mm MRI without DLR, 1.5-mm MRI + DLR resulted in significantly improved pooled accuracy (91.2% vs. 73.1%, P = 0.010), image quality, SNR, and CNR (all, P < 0.001). CONCLUSION: The use of 1.5-mm MRI + DLR enhanced the performance of MRI in diagnosing TLE, particularly in hippocampal evaluation, because of improved depiction of hippocampal abnormalities and enhanced image quality.

Development and Validation of Deep Learning-Based Automated Detection of Cervical Lymphadenopathy in Patients with Lymphoma for Treatment Response Assessment: A Bi-institutional Feasibility Study.

The purpose is to train and evaluate a deep learning (DL) model for the accurate detection and segmentation of abnormal cervical lymph nodes (LN) on head and neck contrast-enhanced CT scans in patients diagnosed with lymphoma and evaluate the clinical utility of the DL model in response assessment. This retrospective study included patients who underwent CT for abnormal cervical LN and lymphoma assessment between January 2021 and July 2022. Patients were grouped into the development (n = 76), internal test 1 (n = 27), internal test 2 (n = 87), and external test (n = 26) cohorts. A 3D SegResNet model was used to train the CT images. The volume change rates of cervical LN across longitudinal CT scans were compared among patients with different treatment outcomes (stable, response, and progression). Dice similarity coefficient (DSC) and the Bland-Altman plot were used to assess the model's segmentation performance and reliability, respectively. No significant differences in baseline clinical characteristics were found across cohorts (age, P = 0.55; sex, P = 0.13; diagnoses, P = 0.06). The mean DSC was 0.39 ± 0.2 with a precision and recall of 60.9% and 57.0%, respectively. Most LN volumes were within the limits of agreement on the Bland-Altman plot. The volume change rates among the three groups differed significantly (progression (n = 74), 342.2%; response (n = 8), - 79.2%; stable (n = 5), - 8.1%; all P < 0.01). Our proposed DL segmentation model showed modest performance in quantifying the cervical LN burden on CT in patients with lymphoma. Longitudinal changes in cervical LN volume, as predicted by the DL model, were useful for treatment response assessment.

Correlation between radiologic depth of invasion and pathologic depth of invasion in oral cavity squamous cell carcinoma: A systematic review and meta-analysis.

OBJECTIVES: To comprehensively assess the correlation between radiologic depth of invasion (rDOI) and pathologic depth of invasion (pDOI) in oral cavity squamous cell carcinoma (OSCC) by meta-analysis. MATERIALS AND METHODS: PubMed and Embase databases were searched to find pertinent articles reporting rDOI of OSCC. Studies evaluating the correlations and mean differences (MDs) between rDOI and pDOI were included. The rDOI was measured based on ultrasound (US), computed tomography (CT), or magnetic resonance imaging (MRI). The correlation coefficients and MDs between rDOI and pDOI were meta-analytically pooled. Between-study heterogeneity was assessed using Higgins' inconsistency index (I2). Subgroup analysis was performed based on imaging modality. RESULTS: Twenty-three studies with 1787 patients were included. The pooled correlation coefficient and MD were 0.86 (95 % confidence interval [CI], 0.82-0.90; I2 = 66.9 %) and 1.84 mm (95 % CI, 1.02-2.65 mm; I2 = 88.2 %), respectively. In subgroup analysis, MRI showed the largest MD (n = 12, 2.61 mm), followed by US (n = 2, -0.41 mm) and CT (n = 2, 0.12 mm). US showed the highest correlation coefficient (n = 3, 0.91), followed by MRI (n = 12, 0.85) and CT (n = 3, 0.82). CONCLUSION: rDOI measured by US, CT, and MRI demonstrated excellent correlations with pDOI.

Pretreatment MR-based radiomics in patients with glioblastoma: A systematic review and meta-analysis of prognostic endpoints.

PURPOSE: Recent studies have shown promise of MR-based radiomics in predicting the survival of patients with untreated glioblastoma. This study aimed to comprehensively collate evidence to assess the prognostic value of radiomics in glioblastoma. METHODS: PubMed-MEDLINE, Embase, and Web of Science were searched to find original articles investigating the prognostic value of MR-based radiomics in glioblastoma published up to July 14, 2023. Concordance indexes (C-indexes) and Cox proportional hazards ratios (HRs) of overall survival (OS) and progression-free survival (PFS) were pooled via random-effects modeling. For studies aimed at classifying long-term and short-term PFS, a hierarchical regression model was used to calculate pooled sensitivity and specificity. Between-study heterogeneity was assessed using the Higgin inconsistency index (I2). Subgroup regression analysis was performed to find potential factors contributing to heterogeneity. Publication bias was assessed via funnel plots and the Egger test. RESULTS: Among 1371 abstracts, 18 and 17 studies were included for qualitative and quantitative data synthesis, respectively. Respective pooled C-indexes and HRs for OS were 0.65 (95 % confidence interval [CI], 0.58-0.72) and 2.88 (95 % CI, 2.28-3.64), whereas those for PFS were 0.61 (95 % CI, 0.55-0.66) and 2.78 (95 % CI, 1.91-4.03). Among 4 studies that predicted short-term PFS, the pooled sensitivity and specificity were 0.77 (95 % CI, 0.58-0.89) and 0.60 (95 % CI, 0.45-0.73), respectively. There was a substantial between-study heterogeneity among studies with the survival endpoint of OS C-index (n = 9, I2 = 83.8 %). Publication bias was not observed overall. CONCLUSION: Pretreatment MR-based radiomics provided modest prognostic value in both OS and PFS in patients with glioblastoma.

Ultrasound LI-RADS Visualization Scores on Surveillance Ultrasound for Hepatocellular Carcinoma: A Systematic Review With Meta-analysis.

We performed a systematic review and meta-analysis to determine the proportions of each surveillance ultrasound (US) visualization score for hepatocellular carcinoma based on the US Liver Imaging Reporting and Data System (LI-RADS) and to identify the factors associated with visualization score C. Original publications reporting US LI-RADS visualization scores were identified in MEDLINE and EMBASE from January 1, 2017, to November 25, 2022. The meta-analytic pooled proportion of each visualization score based on US examination was calculated using the DerSimonian‒Laird random-effects model. Subgroup meta-regression analyses were performed to explore study heterogeneity. US LI-RADS visualization scores were reported from a total of 25,698 US examinations across 12 studies. The pooled proportions of visualization scores A, B and C were 56.7% (95% confidence interval [CI]: 38.6-73.2%, I2 = 99.2%), 30.3% (95% CI: 21.5-40.7%, I2 = 98.8%) and 6.9% (95% CI: 3.9-11.7%, I2 = 97.7%), respectively. Significantly higher proportions of visualization score C were found in studies that exclusively enrolled cirrhosis patients and a study in which the disease etiology was non-alcoholic fatty liver disease (NAFLD) (p < 0.05). In addition, the pooled proportion of visualization score C was higher in studies with a mean or median body mass index >25 kg/m2 (10.7%, 95% CI: 4.3-24.3%). In conclusion, a substantial proportion of surveillance US examinations exhibited moderate to severe limitations on visualization. There was a tendency toward higher proportions of US LI-RADS visualization score C in patients with cirrhosis, NAFLD and obesity.

Glioma grading using multiparametric MRI: head-to-head comparison among dynamic susceptibility contrast, dynamic contrast-enhancement, diffusion-weighted images, and MR spectroscopy.

PURPOSE: To assess the diagnostic accuracy of dynamic susceptibility contrast, dynamic contrast-enhancement, MR spectroscopy (MRS), and diffusion-weighted imaging for differentiating high-grade (HGGs) from low-grade gliomas (LGGs). METHODS: Seventy-two patients (16 LGGs, 56 HGGs) with pathologically confirmed gliomas were retrospectively included. From three-dimensionally segmented tumor, histogram analyses of relative cerebral blood volume (rCBV), volume transfer constant (Ktrans), and apparent diffusion coefficient (ADC) were performed. Choline-to-creatinine ratio (Cho/Cr) was calculated using MRS. Logistic regression analyses were performed to differentiate HGGs (grade ≥ 3) from LGGs (grade ≤ 2). Areas under the receiver operating characteristics curves (AUC) were plotted. Subgroup analysis was performed between IDH-wildtype glioblastomas and IDH-mutant astrocytomas. Pairwise Spearman's correlation coefficients (ρ) were computed. RESULTS: HGGs had higher 95th percentile rCBV, Ktrans and Cho/Cr (P < 0.01) than LGGs. AUC of 95th percentiles of rCBV and Ktrans were 0.79 (95% CI, 0.67-0.91) and 0.74 (95% CI, 0.59-0.88), respectively. AUC of 5th percentile of ADC was 0.63 (95% CI, 0.48-0.79), and that of Cho/Cr was 0.67 (95% CI, 0.52-0.81). IDH-wildtype glioblastomas and IDH-mutant astrocytomas showed significantly different 95th percentile rCBV (P = 0.04) and Ktrans (P < 0.01), with Ktrans showing the highest AUC (0.73, 95% CI 0.57-0.89) in IDH status prediction. Moderate correlations were observed between 95th percentile rCBV and Ktrans (ρ = 0.47), Cho/Cr (ρ = 0.40), and 5th percentile ADC (ρ = -0.36) (all P < 0.01). CONCLUSIONS: The 95th percentile rCBV may be most helpful in discriminating HGGs from LGGs. The 95th percentile Ktrans may aid predicting IDH status of diffuse gliomas.

Diagnosis of nasal bone fractures on plain radiographs via convolutional neural networks.

This study aimed to assess the performance of deep learning (DL) algorithms in the diagnosis of nasal bone fractures on radiographs and compare it with that of experienced radiologists. In this retrospective study, 6713 patients whose nasal radiographs were examined for suspected nasal bone fractures between January 2009 and October 2020 were assessed. Our dataset was randomly split into training (n = 4325), validation (n = 481), and internal test (n = 1250) sets; a separate external dataset (n = 102) was used. The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of the DL algorithm and the two radiologists were compared. The AUCs of the DL algorithm for the internal and external test sets were 0.85 (95% CI, 0.83-0.86) and 0.86 (95% CI, 0.78-0.93), respectively, and those of the two radiologists for the external test set were 0.80 (95% CI, 0.73-0.87) and 0.75 (95% CI, 0.68-0.82). The DL algorithm therefore significantly exceeded radiologist 2 (P = 0.021) but did not significantly differ from radiologist 1 (P = 0.142). The sensitivity and specificity of the DL algorithm were 83.1% (95% CI, 71.2-93.2%) and 83.7% (95% CI, 69.8-93.0%), respectively. Our DL algorithm performs comparably to experienced radiologists in diagnosing nasal bone fractures on radiographs.

Clinical Implications of Focal Mineral Deposition in the Globus Pallidus on CT and Quantitative Susceptibility Mapping of MRI.

OBJECTIVE: To assess focal mineral deposition in the globus pallidus (GP) by CT and quantitative susceptibility mapping (QSM) of MRI scans and evaluate its clinical significance, particularly cerebrovascular degeneration. MATERIALS AND METHODS: This study included 105 patients (66.1 ± 13.7 years; 40 male and 65 female) who underwent both CT and MRI with available QSM data between January 2017 and December 2019. The presence of focal mineral deposition in the GP on QSM (GPQSM) and CT (GPCT) was assessed visually using a three-point scale. Cerebrovascular risk factors and small vessel disease (SVD) imaging markers were also assessed. The clinical and radiological findings were compared between the different grades of GPQSM and GPCT. The relationship between GP grades and cerebrovascular risk factors and SVD imaging markers was assessed using univariable and multivariable linear regression analyses. RESULTS: GPCT and GPQSM were significantly associated (p < 0.001) but were not identical. Higher GPCT and GPQSM grades showed smaller gray matter (p = 0.030 and p = 0.025, respectively) and white matter (p = 0.013 and p = 0.019, respectively) volumes, as well as larger GP volumes (p < 0.001 for both). Among SVD markers, white matter hyperintensity was significantly associated with GPCT (p = 0.006) and brain atrophy was significantly associated with GPQSM (p = 0.032) in at univariable analysis. In multivariable analysis, the normalized volume of the GP was independently positively associated with GPCT (p < 0.001) and GPQSM (p = 0.002), while the normalized volume of the GM was independently negatively associated with GPCT (p = 0.040) and GPQSM (p = 0.035). CONCLUSION: Focal mineral deposition in the GP on CT and QSM might be a potential imaging marker of cerebral vascular degeneration. Both were associated with increased GP volume.

Image Quality of High-Resolution 3-Dimensional Neck MRI Using CAIPIRINHA-VIBE and GRASP-VIBE: An Intraindividual Comparative Study.

OBJECTIVES: Acquiring high-quality magnetic resonance imaging (MRI) of the head and neck region is often challenging due to motion and susceptibility artifacts. This study aimed to compare image quality of 2 high-resolution three-dimensional (3D) MRI sequences of the neck, controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE), and golden-angle radial sparse parallel imaging (GRASP)-VIBE. MATERIALS AND METHODS: One hundred seventy-three patients indicated for contrast-enhanced neck MRI examination were scanned using 3 T scanners and both CAIPIRINHA-VIBE and GRASP-VIBE with nearly isotropic 3D acquisitions (<1 mm in-plane resolution with analogous acquisition times). Patients' MRI scans were independently rated by 2 radiologists using a 5-grade Likert scale for overall image quality, artifact level, mucosal and lesion conspicuity, and fat suppression degree at separate anatomical regions. Interobserver agreement was calculated using the Cohen κ coefficient. The quality ratings of both sequences were compared using the Mann-Whitney U test. Nonuniformity and contrast-to-noise ratio values were measured in all subjects. Separate MRI scans were performed twice for each sequence in a phantom and healthy volunteer without contrast injection to calculate the signal-to-noise ratio (SNR). RESULTS: The scores of overall image quality, overall artifact level, motion artifact level, and conspicuity of the nasopharynx, oropharynx, oral cavity, hypopharynx, and larynx were all significantly higher in GRASP-VIBE than in CAIPIRINHA-VIBE (all P 's < 0.001). Moderate to substantial interobserver agreement was observed in overall image quality (GRASP-VIBE κ = 0.43; CAIPIRINHA-VIBE κ = 0.59) and motion artifact level (GRASP-VIBE κ = 0.51; CAIPIRINHA-VIBE κ = 0.65). Lesion conspicuity was significantly higher in GRASP-VIBE than in CAIPIRINHA-VIBE ( P = 0.005). The degree of fat suppression was weaker in the lower neck regions in GRASP-VIBE (3.90 ± 0.72) than in CAIPIRINHA-VIBE (4.97 ± 0.21) ( P < 0.001). The contrast-to-noise ratio at hypopharyngeal level was significantly higher in GRASP-VIBE (6.28 ± 4.77) than in CAIPIRINHA-VIBE (3.14 ± 9.95) ( P < 0.001). In the phantom study, the SNR of GRASP-VIBE was 12 times greater than that of CAIPIRINHA-VIBE. The in vivo SNR of the volunteer MRI scan was 13.6 in CAIPIRINHA-VIBE and 20.7 in GRASP-VIBE. CONCLUSIONS: Both sequences rendered excellent images for head and neck MRI scans. GRASP-VIBE provided better image quality, as well as mucosal and lesion conspicuities, with less motion artifacts, whereas CAIPIRINHA-VIBE provided better fat suppression in the lower neck regions.

Magnetic Resonance Imaging-Based Radiomics for the Prediction of Progression-Free Survival in Patients with Nasopharyngeal Carcinoma: A Systematic Review and Meta-Analysis.

Advanced non-metastatic nasopharyngeal carcinoma (NPC) has variable treatment outcomes. However, there are no prognostic biomarkers for identifying high-risk patients with NPC. The aim of this systematic review and meta-analysis was to comprehensively assess the prognostic value of magnetic resonance imaging (MRI)-based radiomics for untreated NPC. The PubMed-Medline and EMBASE databases were searched for relevant articles published up to 12 August 2021. The Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) checklist was used to determine the qualities of the selected studies. Random-effects modeling was used to calculate the pooled estimates of Harrell's concordance index (C-index) for progression-free survival (PFS). Between-study heterogeneity was evaluated using Higgins' inconsistency index (I2). Among the studies reported in the 57 articles screened, 10 with 3458 patients were eligible for qualitative and quantitative data syntheses. The mean adherence rate to the TRIPOD checklist was 68.6 ± 7.1%. The pooled estimate of the C-index was 0.762 (95% confidence interval, 0.687-0.837). Substantial between-study heterogeneity was observed (I2 = 89.2%). Overall, MRI-based radiomics shows good prognostic performance in predicting the PFS of patients with untreated NPC. However, more consistent and robust study protocols are necessary to validate the prognostic role of radiomics for NPC.