Sigmoid volvulus: identifying patients requiring emergency surgery with the dark torsion knot sign Abstract Objectives To determine which clinical or CT imaging factors can help accurately identify complicated sigmoid volvulus (SV), defined as irreversible bowel ischaemia or necrosis requiring emergent surgery in patients with SV. Methods We performed a retrospective study of 51 patients admitted consecutively to the emergency department for SV. All patients attempted endoscopic detorsion as the first treatment. Clinical and contrast-enhanced CT factors were analysed. A newly described dark torsion knot sign (sudden loss of mucosal enhancement in the volvulus torsion knot) was included as a CT factor. Patients were diagnosed with complicated versus simple SV based on either surgery or follow-up endoscopic findings. Univariate and multivariate analyses were used to identify predictors of complicated SV. Results Of 51 study patients, 9 patients (17.6%) had complicated SV. Univariate analysis revealed that three clinical factors (sepsis, elevated C-reactive protein, and elevated lactic acid levels) and four CT factors (reduced bowel wall enhancement, increased bowel wall thickness, dark torsion knot sign, and diffuse omental infiltration) were significantly associated with complicated SV. Multivariate analysis identified only dark torsion knot sign (odds ratio = 104.40; p = 0.002) and sepsis (odds ratio = 16.85; p = 0.043) as independent predictive factors of complicated SV. Conclusion A newly defined CT imaging factor of dark torsion knot sign and a clinical factor of sepsis can predict complicated SV necessitating emergent surgery instead of colonoscopic detorsion as a primary treatment of choice. Key Points • A newly defined CT imaging factor of dark torsion knot sign and a clinical factor of sepsis can be helpful for predicting complicated SV necessitating emergent surgery instead of endoscopic detorsion.

Immediate and delayed hypersensitivity after intra-arterial injection of iodinated contrast media: a prospective study in patients with coronary angiography Abstract Objectives While hypersensitivity reactions (HSR) to intravenously administered iodinated contrast media (ICM) have been well studied, not much is known about HSR to intra-arterially administered ICM. Methods A prospective observational study was performed to evaluate coronary angiography (CAG)-induced ICM hypersensitivity in patients who underwent CAG using ICM including ioversol, a low-osmolar non-ionic monomer, and iodixanol, an iso-osmolar non-ionic dimer. The HSR were investigated through in-patient monitoring after CAG and telephone interview after discharge. Results A total of 714 patients were enrolled during the observation period, of whom 26 (3.6%) showed immediate HSR and 108 (15.1%) showed delayed HSR. With regard to severity, proportion of immediate HSR grades 1, 2, and 3 was 57.7%, 38.5%, and 3.8%, respectively, whereas that of delayed HSR grades 1, 2, and 3 was 85.2%, 13.9%, and 0.9%, respectively. Multivariate analysis revealed that previous intra-arterial exposure to ICM was an independent risk factor for immediate HSR (odds ratio (OR) 2.92, 95% confidence interval (CI) 1.22–6.96; p = 0.015). Iodixanol was a significant risk factor for delayed HSR (OR 1.61, 95% CI 1.07–2.43; p = 0.024) and correlated with a higher incidence of delayed HSR within 24-h post-ICM administration compared to ioversol. Conclusion The incidence rate of immediate and delayed HSR in intra-arterially administered ICM was 3.6% and 15.1%, respectively. Previous exposure to intra-arterially administered contrast media was a significant risk factor for immediate HSR. Compared to ioversol, iodixanol was associated with relatively earlier and more frequent delayed HSR. Key Points • In this prospective study, the incidence of immediate and delayed hypersensitivity in intra-arterial injection of contrast media during coronary angiography was 3.6% and 15.1%, respectively. • Delayed hypersensitivity reactions were more common but less severe than immediate hypersensitivity reactions during coronary angiography. • Previous exposure to ICM via intra-arterial route was a significant risk factor for immediate hypersensitivity to intra-arterial contrast medium.

Deteriorated functional and structural brain networks and normally appearing functional–structural coupling in diabetic kidney disease: a graph theory-based magnetic resonance imaging study Abstract Purpose This study was conducted in order to investigate the topological organization of functional and structural brain networks in diabetic kidney disease (DKD) and its potential clinical relevance. Methods Two hundred two subjects (62 DKD patients, 60 diabetes mellitus [DM] patients, and 80 healthy controls) underwent laboratory examination, neuropsychological test, and magnetic resonance imaging (MRI). Large-scale functional and structural brain networks were constructed and graph theoretical network analyses were performed. The effect of renal function on brain functional and structural networks in DKD patients was further evaluated. Correlations were performed between network properties and neuropsychological scores and clinical variables. Results Progressing deteriorated global and local network topology organizations (especially for functional network) were observed for DKD patients compared with control subjects (all p < 0.05, Bonferroni-corrected), with intermediate values for the patients with DM. DKD patients showed normally appearing functional–structural coupling compared with controls, while DM patients manifested functional–structural decoupling (p < 0.05, Bonferroni-corrected). Impaired kidney function markedly affected functional and structural network organization in DKD patients (all p < 0.05). Urea nitrogen correlated with global and local efficiency in the structural networks (r = − 0.551, p < 0.001; r = − 0.476, p < 0.001, respectively). Global and local efficiency in the structural networks and normalized characteristic path length in the functional networks were associated with information processing speed and/or psychomotor speed. Conclusion DKD patients showed enhanced functional and structural brain network disruption and normally appearing functional–structural coupling compared with DM patients, which correlated with kidney function, renal toxins, and cognitive performance. Key Points • DKD patients showed markedly disrupted functional and structural brain network efficiency measures compared with DM patients and healthy controls. • Reduced kidney function clearly deteriorated functional and structural brain networks in DKD patients. • DKD patients displayed normally appearing functional–structural coupling compared with DM patients.

Prognostic value of baseline volumetric multiparametric MR imaging in neuroendocrine liver metastases treated with transarterial chemoembolization Abstract Objectives To determine whether baseline multiparametric MR imaging can predict overall survival (OS) and hepatic progression-free survival (HPFS) in patients with neuroendocrine liver metastases (NELMs) treated with transarterial chemoembolization (TACE). Methods This retrospective study included 84 NELMs patients treated with TACE. Tumor volume and volumetric measurements of arterial enhancement (AE), venous enhancement (VE), and apparent diffusion coefficient (ADC) were performed on baseline MR imaging. A maximum of one, two, and five index lesions were selected in each patient. OS was the primary endpoint and HPFS was the secondary endpoint. Prognostic values of volumetric multiparametric MR parameters for predicting OS and HPFS considering a maximum of one, two, and five index lesions were assessed. Results Prognostic values of volumetric multiparametric MR parameters for predicting OS and HPFS were similar regardless of the maximum number of index lesions. Multivariate survival analysis showed that baseline dominant tumor volume ≥ 73 cm3, volumetric mean AE ≥ 45%, and mean VE ≥ 73% were independent prognostic factors for OS (HR 2.73; 95% CI 1.45, 5.15; HR 0.32; 95% CI 0.17, 0.63; HR 0.35; 95% CI 0.17, 0.72, respectively) and HPFS (HR 2.30, 95% CI 1.38, 3.84; HR 0.46, 95% CI 0.25, 0.84; HR 0.36, 95% CI 0.19, 0.57, respectively). OS and HPFS were similar in patients with low and high volumetric mean ADC. Conclusion Volumetric enhancement values and tumor volume of the dominant lesion on baseline MR imaging may act as prognostic factors for OS and HPFS in NELMs patients treated with TACE. Key Points • High volumetric mean AE and VE, and low tumor volume of the dominant lesion on baseline MR imaging were associated with favorable OS and HPFS in NELMs patients treated with TACE. • Evaluation of multiple lesions does not provide additional information as compared to single lesion evaluation.

Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT Abstract Purpose To develop a deep learning–based computer-aided diagnosis (CAD) system for use in the CT diagnosis of cervical lymph node metastasis (LNM) in patients with thyroid cancer. Methods A total of 995 axial CT images that included benign (n = 647) and malignant (n = 348) lymph nodes were collected from 202 patients with thyroid cancer who underwent CT for surgical planning between July 2017 and January 2018. The datasets were randomly split into training (79.0%), validation (10.5%), and test (10.5%) datasets. Eight deep convolutional neural network (CNN) models were used to classify the images into metastatic or benign lymph nodes. Pretrained networks were used on the ImageNet and the best-performing algorithm was selected. Class-specific discriminative regions were visualized with attention heatmap using a global average pooling method. Results The area under the ROC curve (AUROC) for the tested algorithms ranged from 0.909 to 0.953. The sensitivity, specificity, and accuracy of the best-performing algorithm were all 90.4%, respectively. Attention heatmap highlighted important subregions for further clinical review. Conclusion A deep learning–based CAD system could accurately classify cervical LNM in patients with thyroid cancer on preoperative CT with an AUROC of 0.953. Whether this approach has clinical utility will require evaluation in a clinical setting. Key Points • A deep learning–based CAD system could accurately classify cervical lymph node metastasis. The AUROC for the eight tested algorithms ranged from 0.909 to 0.953. • Of the eight models, the ResNet50 algorithm was the best-performing model for the validation dataset with 0.953 AUROC. The sensitivity, specificity, and accuracy of the ResNet50 model were all 90.4%, respectively, in the test dataset. • Based on its high accuracy of 90.4%, we consider that this model may be useful in a clinical setting to detect LNM on preoperative CT in patients with thyroid cancer.

Distinguishing early-stage nasopharyngeal carcinoma from benign hyperplasia using intravoxel incoherent motion diffusion-weighted MRI Abstract Objectives MRI can detect early-stage nasopharyngeal carcinoma (NPC), but the detection is more challenging in early-stage NPCs because they must be distinguished from benign hyperplasia in the nasopharynx. This study aimed to determine whether intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI) MRI could distinguish between these two entities. Methods Thirty-four subjects with early-stage NPC and 30 subjects with benign hyperplasia prospectively underwent IVIM DWI. The mean pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) and apparent diffusion coefficient (ADC) values were calculated for all subjects and compared between the 2 groups using Student’s t test. Receiver operating characteristics with the area under the curve (AUC) was used to identify the optimal threshold for all significant parameters, and the corresponding diagnostic performance was calculated. A p value of < 0.05 was considered statistically significant. Results Compared with benign hyperplasia, early-stage NPC exhibited a significantly lower D mean (0.64 ± 0.06 vs 0.87 ± 0.11 × 10−3 mm2/s), ADC0–1000 mean (0.77 ± 0.08 vs 1.00 ± 0.13 × 10−3 mm2/s), ADC300–1000 (0.63 ± 0.05 vs 0.86 ± 0.10 × 10−3 mm2/s) and a higher D* mean (32.66 ± 4.79 vs 21.96 ± 5.21 × 10−3 mm2/s) (all p < 0.001). No significant difference in the f mean was observed between the two groups (p = 0.216). The D and ADC300–1000 mean had the highest AUC of 0.985 and 0.988, respectively, and the D mean of < 0.75 × 10−3 mm2/s yielded the highest sensitivity, specificity and accuracy (100%, 93.3% and 96.9%, respectively) in distinguishing early-stage NPC from benign hyperplasia. Conclusion DWI has potential to distinguish early-stage NPC from benign hyperplasia and D and ADC300–1000 mean were the most promising parameters. Key Points • Diffusion-weighted imaging has potential to distinguish early-stage nasopharyngeal carcinoma from benign hyperplasia in the nasopharynx. • The pure diffusion coefficient, pseudo-diffusion coefficient from intravoxel incoherent motion model and apparent diffusion coefficient from conventional diffusion-weighted imaging were significant parameters for distinguishing these two entities in the nasopharynx. • The pure diffusion coefficient, followed by apparent diffusion coefficient, may be the most promising parameters to be used in screening studies to help detect early-stage nasopharyngeal carcinoma.

Image-based biomarkers for solid tumor quantification Abstract The last few decades have witnessed tremendous technological developments in image-based biomarkers for tumor quantification and characterization. Initially limited to manual one- and two-dimensional size measurements, image biomarkers have evolved to harness developments not only in image acquisition technology but also in image processing and analysis algorithms. At the same time, clinical validation remains a major challenge for the vast majority of these novel techniques, and there is still a major gap between the latest technological developments and image biomarkers used in everyday clinical practice. Currently, the imaging biomarker field is attracting increasing attention not only because of the tremendous interest in cutting-edge therapeutic developments and personalized medicine but also because of the recent progress in the application of artificial intelligence (AI) algorithms to large-scale datasets. Thus, the goal of the present article is to review the current state of the art for image biomarkers and their use for characterization and predictive quantification of solid tumors. Beginning with an overview of validated imaging biomarkers in current clinical practice, we proceed to a review of AI-based methods for tumor characterization, such as radiomics-based approaches and deep learning. Key Points • Recent years have seen tremendous technological developments in image-based biomarkers for tumor quantification and characterization. • Image-based biomarkers can be used on an ongoing basis, in a non-invasive (or mildly invasive) way, to monitor the development and progression of the disease or its response to therapy. • We review the current state of the art for image biomarkers, as well as the recent developments in artificial intelligence (AI) algorithms for image processing and analysis.

Prognostic factors of interstitial lung disease progression at sequential HRCT in anti-synthetase syndrome Abstract Objectives Interstitial lung disease (ILD) is a common extra-muscular manifestation of anti-synthetase syndrome (ASS) and the main cause of morbidity and mortality in patients with ASS. Data on prognostic factors in these patients are lacking. Methods A total of 69 patients with ILD and positivity for at least one of the following autoantibodies were included: anti-Jo-1, anti-PL7, anti-PL12, and anti-EJ. Relevant clinical characteristics were registered. According to the changes in the extent of abnormalities at the follow-up on high-resolution computed tomography (HRCT), three groups were defined: the regression, stability, and deterioration groups. Univariate analysis was performed to evaluate possible prognostic factors and multivariate analysis by logistic regression was then applied to determine the independent prognostic factors in ASS-ILD. Results The cohort comprised 69 patients positive for anti-synthetase antibodies, i.e., 30 for anti-Jo-1, 16 for anti-EJ, 13 for anti-PL7, and 10 for anti-PL12. The mean length of follow-up was 15 months. Sex, age at diagnosis, fever at presentation, and counts of CD3+CD4+ cells were significantly different among the three groups. According to the multivariate analysis, fever at presentation, lower counts of CD3+CD4+ cells, and a pattern of usual interstitial pneumonia were the three independent risk factors for poor outcomes of ASS-ILD. Conclusions At the onset of ASS, some clinical features and HRCT pattern of ILD may suggest an unfavorable outcome of lung involvement on HRCT, even with routine therapy. These factors may contribute to the high long-term mortality of ASS. Key Points • Evaluation of lung involvement on HRCT is important in the follow-up of patients with interstitial lung disease related to anti-synthetase syndrome (ASS-ILD). • The interstitial lung disease related to ASS responds to the treatment variably. • Some clinical and imaging characteristics are associated with poor prognosis in patients with ASS-ILD, including fever at diagnosis, a lower serum CD3 + /CD4 + level, and a UIP pattern.

Diagnostic performance of MRI for detecting intraplaque hemorrhage in the carotid arteries: a meta-analysis Abstract Objectives To investigate the diagnostic performance of MRI in diagnosing carotid atherosclerotic intraplaque hemorrhage (IPH) and to provide a clinical guide for MRI application. Methods We searched MEDLINE, Embase, and Cochrane library from the earliest available date of indexing through November 30, 2017. All investigators screened and selected studies comparing the use of MRI with histology. The accuracy to diagnose pathological IPH was expressed by sensitivity, specificity, negative likelihood ratios (LRs), positive LRs, and the area under summary receiver-operating characteristic (SROC) curve. We calculated the post-test probability to assess the clinical utility of MRI. Results We analyzed 696 patients from 20 articles. The sensitivity and specificity were 87% (95% CI, 81–91%) and 92% (95% CI, 87–95%), respectively. The positive and negative LRs were 10.27 (95% CI, 6.76–15.59) and 0.15 (95% CI, 0.10–0.21), respectively. The area under SROC curve was 0.95 (95% CI, 0.93–0.97). MRI was accurate in confirming or in ruling out disease over a wide range of pre-test probabilities of IPH: MRI could increase the post-test probability to > 80% in patients with a pre-test probability > 27% and could decrease the post-test probability to < 20% in patients with a pre-test probability < 64%. Conclusion Non-invasive MRI has excellent specificity and good sensitivity for diagnosing IPH. MRI is a tool for confirming or ruling out carotid atherosclerotic IPH. Key Points • Non-invasive MRI has excellent performance for diagnosing IPH, which is a component of vulnerable plaque. • The high accuracy of MRI for IPH helps clinicians analyze the prognosis of clinical events and plan personalized treatment.

T 2 mapping of the meniscus is a biomarker for early osteoarthritis Abstract Purpose To evaluate in vivo T2 mapping as quantitative, imaging-based biomarker for meniscal degeneration in humans, by studying the correlation between T2 relaxation time and degree of histological degeneration as reference standard. Methods In this prospective validation study, 13 menisci from seven patients with radiographic knee osteoarthritis (median age 67 years, three males) were included. Menisci were obtained during total knee replacement surgery. All patients underwent pre-operative magnetic resonance imaging using a 3-T MR scanner which included a T2 mapping pulse sequence with multiple echoes. Histological analysis of the collected menisci was performed using the Pauli score, involving surface integrity, cellularity, matrix organization, and staining intensity. Mean T2 relaxation times were calculated in meniscal regions of interest corresponding with the areas scored histologically, using a multi-slice multi-echo postprocessing algorithm. Correlation between T2 mapping and histology was assessed using a generalized least squares model fit by maximum likelihood. Results The mean T2 relaxation time was 22.4 ± 2.7 ms (range 18.5–27). The median histological score was 10, IQR 7–11 (range 4–13). A strong correlation between T2 relaxation time and histological score was found (rs = 0.84, CI 95% 0.64–0.93). Conclusion In vivo T2 mapping of the human meniscus correlates strongly with histological degeneration, suggesting that T2 mapping enables the detection and quantification of early compositional changes of the meniscus in knee OA. Key Points • Prospective histology-based study showed that in vivo T 2 mapping of the human meniscus correlates strongly with histological degeneration. • Meniscal T 2 mapping allows detection and quantifying of compositional changes, without need for contrast or special MRI hardware. • Meniscal T 2 mapping provides a biomarker for early OA, potentially allowing early treatment strategies and prevention of OA progression.