Choosing the right artificial intelligence solutions for your radiology department: key factors to consider

The rapid evolution of artificial intelligence (AI), particularly in deep learning, has significantly impacted radiology, introducing an array of AI solutions for interpretative tasks. This paper provides radiology departments with a practical guide for selecting and integrating AI solutions, focusing on interpretative tasks that require the active involvement of radiologists. Our approach is not to list available applications or review scientific evidence, as this information is readily available in previous studies; instead, we concentrate on the essential factors radiology departments must consider when choosing AI solutions. These factors include clinical relevance, performance and validation, implementation and integration, clinical usability, costs and return on investment, and regulations, security, and privacy. We illustrate each factor with hypothetical scenarios to provide a clearer understanding and practical relevance. Through our experience and literature review, we provide insights and a practical roadmap for radiologists to navigate the complex landscape of AI in radiology. We aim to assist in making informed decisions that enhance diagnostic precision, improve patient outcomes, and streamline workflows, thus contributing to the advancement of radiological practices and patient care.

Quantitative evaluation of Saliency-Based Explainable artificial intelligence (XAI) methods in Deep Learning-Based mammogram analysis

BACKGROUND

Explainable Artificial Intelligence (XAI) is prominent in the diagnostics of opaque deep learning (DL) models, especially in medical imaging. Saliency methods are commonly used, yet there's a lack of quantitative evidence regarding their performance.

OBJECTIVES

To quantitatively evaluate the performance of widely utilized saliency XAI methods in the task of breast cancer detection on mammograms.

METHODS

Three radiologists drew ground-truth boxes on a balanced mammogram dataset of women (n = 1496 cancer-positive and negative scans) from three centers. A modified, pre-trained DL model was employed for breast cancer detection, using MLO and CC images. Saliency XAI methods, including Gradient-weighted Class Activation Mapping (Grad-CAM), Grad-CAM++, and Eigen-CAM, were evaluated. We utilized the Pointing Game to assess these methods, determining if the maximum value of a saliency map aligned with the bounding boxes, representing the ratio of correctly identified lesions among all cancer patients, with a value ranging from 0 to 1.

RESULTS

The development sample included 2,244 women (75%), with the remaining 748 women (25%) in the testing set for unbiased XAI evaluation. The model's recall, precision, accuracy, and F1-Score in identifying cancer in the testing set were 69%, 88%, 80%, and 0.77, respectively. The Pointing Game Scores for Grad-CAM, Grad-CAM++, and Eigen-CAM were 0.41, 0.30, and 0.35 in women with cancer and marginally increased to 0.41, 0.31, and 0.36 when considering only true-positive samples.

CONCLUSIONS

While saliency-based methods provide some degree of explainability, they frequently fall short in delineating how DL models arrive at decisions in a considerable number of instances.

Robot-Assisted Minimally Invasive Multivessel Coronary Bypass Guided by Computerized Tomography

OBJECTIVE

Robot-assisted minimally invasive coronary bypass surgery is one of the least invasive approaches that offers multivessel revascularization and accelerated recovery. We investigated the benefits of computed tomography angiography (CTA) guidance in robotic coronary bypass (RCAB) by analyzing perioperative outcomes.

METHODS

Between April 2022 and April 2023, 60 consecutive patients who underwent RCAB under preoperative CTA guidance were included. The intercostal space of the minithoractomy incision was determined based on the distance from the thoracotomy site to the midsection of the left anterior descending artery (LAD) on preoperative CTA. Peripheral vascular findings on preoperative CTA guided the decision for the cannulation site. Perioperative parameters and early outcomes were evaluated.

RESULTS

The mean age of the patients was 62.3 ± 10.5 years, and 51 patients were male (85.0%). The mean number of revascularized vessels was 2.9 ± 1.1. Left thoracotomy guided by CTA measurements was performed in the fourth intercostal space in 37 patients (61.7%) and in the third intercostal space in the remaining patients. Axillary cannulation was performed in 28 (46.7%) patients because of prohibitive findings in the iliac vessels and aorta. All target coronary arteries with an indication for bypass were revascularized with CTA-guided RCAB. The left internal mammary artery (LIMA) was anastomosed to the LAD in all patients, and the LIMA was anastomosed sequentially to the diagonal artery in 17 patients (28.3%). No operative mortality or cerebrovascular event was observed. One patient underwent reoperation due to bleeding.

CONCLUSIONS

Robot-assisted minimally invasive multiple-vessel coronary bypass under preoperative CTA guidance is safe and can be performed with excellent results.

Anatomically guided self-adapting deep neural network for clinically significant prostate cancer detection on bi-parametric MRI: a multi-center study

OBJECTIVE

To evaluate the effectiveness of a self-adapting deep network, trained on large-scale bi-parametric MRI data, in detecting clinically significant prostate cancer (csPCa) in external multi-center data from men of diverse demographics; to investigate the advantages of transfer learning.

METHODS

We used two samples: (i) Publicly available multi-center and multi-vendor Prostate Imaging: Cancer AI (PI-CAI) training data, consisting of 1500 bi-parametric MRI scans, along with its unseen validation and testing samples; (ii) In-house multi-center testing and transfer learning data, comprising 1036 and 200 bi-parametric MRI scans. We trained a self-adapting 3D nnU-Net model using probabilistic prostate masks on the PI-CAI data and evaluated its performance on the hidden validation and testing samples and the in-house data with and without transfer learning. We used the area under the receiver operating characteristic (AUROC) curve to evaluate patient-level performance in detecting csPCa.

RESULTS

The PI-CAI training data had 425 scans with csPCa, while the in-house testing and fine-tuning data had 288 and 50 scans with csPCa, respectively. The nnU-Net model achieved an AUROC of 0.888 and 0.889 on the hidden validation and testing data. The model performed with an AUROC of 0.886 on the in-house testing data, with a slight decrease in performance to 0.870 using transfer learning.

CONCLUSIONS

The state-of-the-art deep learning method using prostate masks trained on large-scale bi-parametric MRI data provides high performance in detecting csPCa in internal and external testing data with different characteristics, demonstrating the robustness and generalizability of deep learning within and across datasets.

CLINICAL RELEVANCE STATEMENT

A self-adapting deep network, utilizing prostate masks and trained on large-scale bi-parametric MRI data, is effective in accurately detecting clinically significant prostate cancer across diverse datasets, highlighting the potential of deep learning methods for improving prostate cancer detection in clinical practice.

Deep learning for assessing image quality in bi-parametric prostate MRI: A feasibility study

BACKGROUND

Although systems such as Prostate Imaging Quality (PI-QUAL) have been proposed for quality assessment, visual evaluations by human readers remain somewhat inconsistent, particularly among less-experienced readers.

OBJECTIVES

To assess the feasibility of deep learning (DL) for the automated assessment of image quality in bi-parametric MRI scans and compare its performance to that of less-experienced readers.

METHODS

We used bi-parametric prostate MRI scans from the PI-CAI dataset in this study. A 3-point Likert scale, consisting of poor, moderate, and excellent, was utilized for assessing image quality. Three expert readers established the ground-truth labels for the development (500) and testing sets (100). We trained a 3D DL model on the development set using probabilistic prostate masks and an ordinal loss function. Four less-experienced readers scored the testing set for performance comparison.

RESULTS

The kappa scores between the DL model and the expert consensus for T2W images and ADC maps were 0.42 and 0.61, representing moderate and good levels of agreement. The kappa scores between the less-experienced readers and the expert consensus for T2W images and ADC maps ranged from 0.39 to 0.56 (fair to moderate) and from 0.39 to 0.62 (fair to good).

CONCLUSIONS

Deep learning (DL) can offer performance comparable to that of less-experienced readers when assessing image quality in bi-parametric prostate MRI, making it a viable option for an automated quality assessment tool. We suggest that DL models trained on more representative datasets, annotated by a larger group of experts, could yield reliable image quality assessment and potentially substitute or assist visual evaluations by human readers.

Inter-reader agreement of the prostate imaging quality (PI-QUAL) score for basic readers in prostate MRI: A multi-center study

BACKGROUND

The Prostate Imaging Quality (PI-QUAL) score is the first step toward image quality assessment in multi-parametric prostate MRI (mpMRI). Previous studies have demonstrated moderate to excellent inter-rater agreement among expert readers; however, there is a need for studies to assess the inter-reader agreement of PI-QUAL scoring in basic prostate readers.

OBJECTIVES

To assess the inter-reader agreement of the PI-QUAL score amongst basic prostate readers on multi-center prostate mpMRI.

METHODS

Five basic prostate readers from different centers assessed the PI-QUAL scores independently using T2-weighted images, diffusion-weighted imaging (DWI) including apparent diffusion coefficient (ADC) maps, and dynamic-contrast-enhanced (DCE) images on mpMRI data obtained from five different centers following Prostate Imaging-Reporting and Data System Version 2.1. The inter-reader agreements amongst radiologists for PI-QUAL were evaluated using weighted Cohen's kappa. Further, the absolute agreements in assessing the diagnostic adequacy of each mpMRI sequence were calculated.

RESULTS

A total of 355 men with a median age of 71 years (IQR, 60-78) were enrolled in the study. The pair-wise kappa scores ranged from 0.656 to 0.786 for the PI-QUAL scores, indicating good inter-reader agreements between the readers. The pair-wise absolute agreements ranged from 0.75 to 0.88 for T2W imaging, from 0.74 to 0.83 for the ADC maps, and from 0.77 to 0.86 for DCE images.

CONCLUSIONS

Basic prostate radiologists from different institutions provided good inter-reader agreements on multi-center data for the PI-QUAL scores.

Automated LVO detection and collateral scoring on CTA using a 3D self-configuring object detection network: a multi-center study

The use of deep learning (DL) techniques for automated diagnosis of large vessel occlusion (LVO) and collateral scoring on computed tomography angiography (CTA) is gaining attention. In this study, a state-of-the-art self-configuring object detection network called nnDetection was used to detect LVO and assess collateralization on CTA scans using a multi-task 3D object detection approach. The model was trained on single-phase CTA scans of 2425 patients at five centers, and its performance was evaluated on an external test set of 345 patients from another center. Ground-truth labels for the presence of LVO and collateral scores were provided by three radiologists. The nnDetection model achieved a diagnostic accuracy of 98.26% (95% CI 96.25-99.36%) in identifying LVO, correctly classifying 339 out of 345 CTA scans in the external test set. The DL-based collateral scores had a kappa of 0.80, indicating good agreement with the consensus of the radiologists. These results demonstrate that the self-configuring 3D nnDetection model can accurately detect LVO on single-phase CTA scans and provide semi-quantitative collateral scores, offering a comprehensive approach for automated stroke diagnostics in patients with LVO.

Outcome Predictors of Lesional Posterior Cortex Epilepsy Surgery

BACKGROUND

Lesional posterior cortex epilepsy (PCE) is often drug resistant and may benefit from surgical intervention. In this study, we aimed to identify potential predictive factors associated with seizure recurrence after epilepsy surgery in lesional PCE.

METHODS

We retrospectively reviewed patients with PCE who underwent surgery between 1998 and 2021. They were divided into 2 groups according to seizure outcome; the seizure-free group (group 1) and the non-seizure-free group (group 2). The relationship among clinical factors, electroencephalography (EEG) or cranial magnetic resonance imaging findings, disease, and seizure outcome was investigated.

RESULTS

A total of 60 patients, with a mean age of 27.26 ± 12.35 years (range, 9-61 years), were included in the study. There were 31 patients (51.66%) in group 1 (Engel class I) and 29 patients (48.33%) in group 2 (13 [21.66%], 10 [16.66%], and 6 [10%] patients in Engel class II, III, and IV, respectively), with a mean follow-up of 8.95 ± 6.96 years (range, 1-24 years). No difference was observed regarding age, gender, age at seizure onset, operation type, treatment gap, and presence of bilateral lesions between the groups (P > 0.05). However, bilateral findings on interictal EEG and gliosis as the underlying disease were predictors of seizure recurrence (P < 0.05).

CONCLUSIONS

More than half of the patients (including 2 with bilateral magnetic resonance imaging lesions) were seizure free at long-term follow-up. However, patients with bilateral findings on interictal EEG and gliosis were more likely to have recurrent seizures after surgery. Because lesional PCE is almost always drug resistant and has a potential for favorable outcomes, epilepsy surgery should be considered early.

The Role of Whole-Body Magnetic Resonance Imaging in Assessing Extrapulmonary Metastases in Osteosarcoma Staging and Restaging: A Pilot Study

OBJECTIVE

The aim of the study is to investigate the role of whole-body magnetic resonance imaging (MRI) in assessing extrapulmonary metastases in primary osteosarcoma staging.

METHODS

We retrospectively reviewed medical data to identify primary osteosarcoma patients with available preoperative whole-body MRI obtained in the staging or restaging. Histopathology was the reference test for assessing the diagnostic performance, if available. Otherwise, oncology board decisions were used as the reference. In addition, the benefits of whole-body MRI to F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET-CT) and bone scintigraphy were investigated.

RESULTS

In all, 36 patients with osteosarcoma (24 staging, 12 restaging) with a mean age of 16.36 ± 5.63 years (range, 9-29 years) were included in the study. The median follow-up duration was 26.61 months (interquartile range, 33.3 months). Of 36 patients, 8 had skeletal, 1 had a lymph node, and 1 had a subcutaneous metastasis. Whole-body MRI correctly identified all patients with metastatic disease but incorrectly classified a bone infarct in one patient as a skeletal metastasis, equating a scan-level sensitivity, specificity, accuracy, negative predictive value, and positive predictive value of 100%, 96.3%, 97.3%, 100%, and 90.91%. Whole-body MRI contributed to bone scintigraphy by identifying a skeletal metastasis in one patient and positron emission tomography-computed tomography by ruling out a skeletal metastasis in another.

CONCLUSIONS

Whole-body MRI could accurately identify extrapulmonary metastases in primary osteosarcoma patients for staging or restaging. In addition, it might contribute to the standard whole-body imaging methods.

Does deep learning software improve the consistency and performance of radiologists with various levels of experience in assessing bi-parametric prostate MRI?

OBJECTIVE

To investigate whether commercially available deep learning (DL) software improves the Prostate Imaging-Reporting and Data System (PI-RADS) scoring consistency on bi-parametric MRI among radiologists with various levels of experience; to assess whether the DL software improves the performance of the radiologists in identifying clinically significant prostate cancer (csPCa).

METHODS

We retrospectively enrolled consecutive men who underwent bi-parametric prostate MRI at a 3 T scanner due to suspicion of PCa. Four radiologists with 2, 3, 5, and > 20 years of experience evaluated the bi-parametric prostate MRI scans with and without the DL software. Whole-mount pathology or MRI/ultrasound fusion-guided biopsy was the reference. The area under the receiver operating curve (AUROC) was calculated for each radiologist with and without the DL software and compared using De Long's test. In addition, the inter-rater agreement was investigated using kappa statistics.

RESULTS

In all, 153 men with a mean age of 63.59 ± 7.56 years (range 53-80) were enrolled in the study. In the study sample, 45 men (29.80%) had clinically significant PCa. During the reading with the DL software, the radiologists changed their initial scores in 1/153 (0.65%), 2/153 (1.3%), 0/153 (0%), and 3/153 (1.9%) of the patients, yielding no significant increase in the AUROC (p > 0.05). Fleiss' kappa scores among the radiologists were 0.39 and 0.40 with and without the DL software (p = 0.56).

CONCLUSIONS

The commercially available DL software does not increase the consistency of the bi-parametric PI-RADS scoring or csPCa detection performance of radiologists with varying levels of experience.

The analysis of 18 F-FDG PET/MRI, electroencephalography, and semiology in patients with gray matter heterotopia: A pilot study

OBJECTIVES

To describe ¹⁸ F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (¹⁸ F-FDG PET/MRI) along with semiology and electroencephalography (EEG) in patients with gray matter heterotopia (GMH); to evaluate the concordance between ¹⁸ F-FDG PET/MRI and clinical epileptogenic zone (EZ).

MATERIALS & METHODS

GMH (subcortical heterotopia [SCH] and periventricular nodular heterotopia [PNH]) patients with epilepsy who underwent ¹⁸ F-FDG PET/MRI were retrospectively enrolled. Two radiologists evaluated brain MRI, while two nuclear medicine specialists assessed the ¹⁸ F-FDG PET. The SUVmax values of visually hypometabolic cortical areas were compared to the contralateral cortex using a SUVmax threshold value of 10%; the SUVmax values of GMH lesions were compared with that of the right precentral gyrus. The cortex or GMH with hypometabolism on ¹⁸ F-FDG PET/MRI was considered representative of the EZ. The clinical EZ was identified using EEG and semiology.

RESULTS

Thirty patients (19 PNH; 11 SCH) with a mean age of 28.46 ± 9.52 years were enrolled. The heterotopic nodules were ametabolic in 3 patients (10%), hypometabolic in 16 (33.33%), isometabolic in 13 (26.66%), and hypermetabolic in 4 (10%). ¹⁸ F-FDG PET/MRI demonstrated hypometabolism in the cortex and GMH in 22/30 (73.33%) and 16/30 (53.33%). We could identify a clinical EZ in 18 patients, and 15 out of 18 (83.33%) had concordant ¹⁸ F-FDG PET/MRI findings.

CONCLUSION

Heterotopic nodules in GMH patients show different metabolic patterns on ¹⁸ F-FDG PET/MRI, with nearly three-quarters of the patients having cortical hypometabolism. ¹⁸ F-FDG PET/ MRI findings are mostly concordant with the clinical EZ.

Revisiting imaging features of rectosigmoid vascular malformation with emphasis on multiparametric MRI: a case report

Background

Gastrointestinal vascular malformations are rare benign vascular neoplasms of the gastrointestinal tract, with the rectosigmoid region being the most frequently involved site. Patients often manifest with recurrent, intermittent rectal bleeding, which might occasionally be life-threatening.

Case presentation

A 39-year-old man with a history of hemorrhoid operations twice was presented to our gastroenterology department with blood in the stool and abdominal pain. After the colonoscopy, multiparametric MRI, and CT examinations, robotic low anterior resection was performed with the diagnosis of rectosigmoid venous malformation. The histopathological examination confirmed the diagnosis.

Conclusion

Colonoscopy is the preferred method in diagnosing rectosigmoid vascular malformation, but wrong and delayed diagnoses are common. Thus, imaging modalities might add to colonoscopy in equivocal cases.

A joint convolutional-recurrent neural network with an attention mechanism for detecting intracranial hemorrhage on noncontrast head CT

To investigate the performance of a joint convolutional neural networks-recurrent neural networks (CNN-RNN) using an attention mechanism in identifying and classifying intracranial hemorrhage (ICH) on a large multi-center dataset; to test its performance in a prospective independent sample consisting of consecutive real-world patients. All consecutive patients who underwent emergency non-contrast-enhanced head CT in five different centers were retrospectively gathered. Five neuroradiologists created the ground-truth labels. The development dataset was divided into the training and validation set. After the development phase, we integrated the deep learning model into an independent center’s PACS environment for over six months for assessing the performance in a real clinical setting. Three radiologists created the ground-truth labels of the testing set with a majority voting. A total of 55,179 head CT scans of 48,070 patients, 28,253 men (58.77%), with a mean age of 53.84 ± 17.64 years (range 18–89) were enrolled in the study. The validation sample comprised 5211 head CT scans, with 991 being annotated as ICH-positive. The model's binary accuracy, sensitivity, and specificity on the validation set were 99.41%, 99.70%, and 98.91, respectively. During the prospective implementation, the model yielded an accuracy of 96.02% on 452 head CT scans with an average prediction time of 45 ± 8 s. The joint CNN-RNN model with an attention mechanism yielded excellent diagnostic accuracy in assessing ICH and its subtypes on a large-scale sample. The model was seamlessly integrated into the radiology workflow. Though slightly decreased performance, it provided decisions on the sample of consecutive real-world patients within a minute.

Association between left ventricular strain and cardiac iron load in beta-thalassaemia major: a cardiac magnetic resonance study

OBJECTIVE

To evaluate the utility of cardiac magnetic resonance feature tracking-derived left ventricular strain in assessing cardiac dysfunction and investigate the correlation between left ventricular strain and myocardial T2* in patients with beta-thalassaemia major.

METHODS

Forty-two patients with beta-thalassaemia major, having a mean age of 22.49 ± 8.48 years, and age-matched healthy controls were enrolled in the study. The observer drew regions of interest on the interventricular septum, and T2* decay curves were calculated accordingly. The short-axis cine images were used to derive left ventricular circumferential and radial strains, and the long-axis four-chamber and two-chamber images were used to assess left ventricular longitudinal strain.

RESULTS

The mean global left ventricular strains were lower in beta-thalassaemia major patients than the controls (p < 0.05). Left ventricular strains of beta-thalassaemia major patients with cardiac T2* values of > 20 ms were also significantly reduced compared with the controls (p < 0.05); there was no difference between the mean left ventricular ejection fractions of the two groups (p = 0.84). Cardiac T2* showed a weak correlation with left ventricular ejection fraction (r = 0.33, p = 0.03), while the left ventricular circumferential strain showed a good positive correlation with cardiac T2* (r = 0.6, p < 0.0001).

CONCLUSION

Compared with healthy controls, patients with beta-thalassaemia major, including those with myocardial T2* values of >20 ms, showed reduced global left ventricular strains. Left ventricular circumferential strain was positively correlated with myocardial T2*. Left ventricular strain analysis using cardiac magnetic resonance feature tracking may have utility in beta-thalassaemia major assessment.Key FindingsPatients with beta-thalassaemia major, including those with myocardial T2* values of >20 ms, had reduced global left ventricular strains.Cardiac T2* showed a weak correlation with left ventricular ejection fraction, while the left ventricular circumferential strain showed a good positive correlation with cardiac T2*.ImportanceLeft ventricular strain using cardiac magnetic resonance feature tracking might be used as an adjunct in assessing cardiac functions in beta-thalassaemia major.

The Association between the Extent of Late Gadolinium Enhancement and Diastolic Dysfunction in Hypertrophic Cardiomyopathy

Background Diastolic dysfunction in hypertrophic cardiomyopathy (HCM) patients is a frequent, yet poorly understood phenomenon.

Purpose The purpose of this study is to assess the relationship between the myocardial fibrosis and diastolic dysfunction in patients with HCM.

Materials and Methods We retrospectively investigated the impact of the myocardial fibrosis, as assessed by the extent of late gadolinium enhancement (LGE-%) on cardiac magnetic resonance imaging (CMRI), on diastolic dysfunction in 110 patients with HCM. The diastolic dysfunction was evaluated by the left atrial (LA) volume index measured on CMRI and lateral septal E/E′ ratio calculated on echocardiography.

Results : There was a moderate correlation between the LGE-% and LA volume ( r = 0.59, p < 0.0001). The logistic regression model of LGE-%, mitral regurgitation, and total left ventricular mass that investigated the independent predictors of LA volume identified LGE-% as the only independent parameter associated with the LA volume index ( β = 0.30, p = 0.003). No correlation was observed between the LGE-% and E/E′( r = 0.24, p = 0.009).

Conclusions Myocardial fibrosis in HCM patients is associated with a chronic diastolic burden as represented by increased LA volume. However, the fibrosis does not influence the E/E′ ratio, which is a well-known parameter of ventricular relaxation, restoring forces, and filling pressure.

Diagnostic Accuracy of Ultrasound for the Evaluation of Lateral Compartment Lymph Nodes in Papillary Thyroid Carcinoma

AIMS

To evaluate the diagnostic accuracy of ultrasound (US) assessing the lateral compartment lymph node metastasis in patients with primary papillary thyroid carcinoma (PTC), and to demonstrate the incidence and patterns of the lateral lymph node metastasis.

METHODS

We retrospectively reviewed 198 patients with primary PTC who underwent thyroidectomy in addition to modified lateral neck dissections (MLND) involving level II to level V due to clinically positive lateral neck disease. A skilled and experienced single operator performed all US examinations. Surgical pathology results were accepted as the reference method and sensitivity, specificity, and diagnostic accuracy of US in detecting metastatic lymph nodes established using level-by-level analysis.

RESULTS

In the study cohort, 10.1% of the patients had lateral compartment lymph node metastases without any central compartment involvement. For the lateral compartment, 48.5% had level II, 74.7% had level III, 64.6% had level IV, and 29.3% of the patients had level V metastasis. None of the patients had isolated level V metastasis. The sensitivity, specificity, and diagnostic accuracy of US in identifying lateral lymph compartment metastasis ranged from 87% to 91.4%, 92% to 98.6% 92.4% to 96%, respectively. However, the sensitivity (74.7%) and diagnostic accuracy (76.2%) of US significantly decreased for the central compartment while specificity (90%) remained similar.

CONCLUSION

US performed by a skilled operator has an excellent diagnostic accuracy for the evaluation of lateral cervical lymph nodes in primary PTC; thus, might enable precise tailoring of the management strategies. Moreover, the high incidence of level V involvement favors MLND over selective approaches.

Inter-vendor performance of deep learning in segmenting acute ischemic lesions on diffusion-weighted imaging: a multicenter study

There is little evidence on the applicability of deep learning (DL) in the segmentation of acute ischemic lesions on diffusion-weighted imaging (DWI) between magnetic resonance imaging (MRI) scanners of different manufacturers. We retrospectively included DWI data of patients with acute ischemic lesions from six centers. Dataset A (n = 2986) and B (n = 3951) included data from Siemens and GE MRI scanners, respectively. The datasets were split into the training (80%), validation (10%), and internal test (10%) sets, and six neuroradiologists created ground-truth masks. Models A and B were the proposed neural networks trained on datasets A and B. The models subsequently fine-tuned across the datasets using their validation data. Another radiologist performed the segmentation on the test sets for comparisons. The median Dice scores of models A and B were 0.858 and 0.857 for the internal tests, which were non-inferior to the radiologist’s performance, but demonstrated lower performance than the radiologist on the external tests. Fine-tuned models A and B achieved median Dice scores of 0.832 and 0.846, which were non-inferior to the radiologist's performance on the external tests. The present work shows that the inter-vendor operability of deep learning for the segmentation of ischemic lesions on DWI might be enhanced via transfer learning; thereby, their clinical applicability and generalizability could be improved.

The visibility of prostate cancer concerning underlying histopathological variances: A single-center multiparametric magnetic resonance imaging study

PURPOSE

To investigate whether prostate cancer (PCa) lesions regarding histopathological composition exhibit different morphological features on multiparametric prostate MRI (mpMRI).

METHODS

We investigated men with PCa with available mpMRI and whole-mount specimens between June 2015 to December 2020.The acquisition protocol consistent with the Prostate Imaging Reporting and Data System (PI-RADS). Two observers evaluated the images following the PI-RADS v2.1. guideline before biopsy and radical prostatectomy. The discrepancies were resolved in a joint meeting. A genitourinary pathologist reviewed the whole-digitalized mount specimens, and the lesions with Gleason score of 7 and above (3 + 4 and above), and/or cancers with a maximum diameter of 6 mm and more, and/or extraprostatic extension were accepted as clinically significant PCa. The PI-RADS scores and the diameter of the clinically significant PCa on mpMRI concerning histopathological components (i.e., cribriform component, intraductal pattern, or without cribriform component or intraductal pattern) were investigated. The clinically significant PCa foci with PI-RADS score <3 was accepted as an invisible lesion on mpMRI.

RESULTS

In all, 58 men with a total of 112 clinically significant PCa foci, were enrolled in the study. The intraductal pattern, cribriform pattern, or none of these patterns were observed in 28/112 (25 %), 43/112 (38.05 %), and 41/112 (36.60 %) tumor foci. Six out of 28 (21.42 %), 17/43 (39.53 %), and 18/41 (42.8 %) foci with an intraductal pattern, cribriform component, or without any of them, respectively, were invisible on mpMRI (P = 0.111).

CONCLUSION

Though it was not reached a statistical significance, clinically significant PCa with the cribriform component and without any intraductal or cribriform component are more likely to manifests mpMRI invisible foci than the intraductal pattern. Further multi-center studies are warranted to precisely elucidate mpMRI features of PCa regarding histopathological composition.

Diagnostic value of left atrial strain in pediatric hypertrophic cardiomyopathy with normal maximum left atrial volume index: preliminary cardiac magnetic resonance study

BACKGROUND

The maximum left atrial volume index is the most widely used metric for assessing the left atrium in hypertrophic cardiomyopathy; however, it may be normal in the early phases of the disease.

OBJECTIVE

To assess whether pediatric hypertrophic cardiomyopathy patients with normal maximum left atrial volume index have impaired atrial functions on cardiac magnetic resonance imaging (MRI).

MATERIALS AND METHOD

A total of 26 pediatric hypertrophic cardiomyopathy patients and 24 age-matched children, as controls, were enrolled in the study. The left atrial reservoir, conduit and booster strain were calculated from two orthogonal planes and the left atrial volumes were calculated using the biplanar method. The extent of left ventricular late gadolinium enhancement (LGE-%) was calculated using the thresholding method. The left ventricular early diastolic longitudinal strain rate was calculated to assess diastolic dysfunction.

RESULTS

The maximum left atrial volume index of the children with hypertrophic cardiomyopathy and the controls were not significantly different (P>0.05). Most of the left atrial functional indices were worse in children with hypertrophic cardiomyopathy (P<0.05), yet no difference was observed between the left atrial booster strains of the two groups (P>0.05). The left atrial conduit strain showed moderate to good negative correlations with left ventricular LGE-% and diastolic dysfunction.

CONCLUSION

Left atrial conduit and reservoir strains are impaired in pediatric hypertrophic cardiomyopathy patients with normal maximum left atrial volumetric indices. Most left atrial strain parameters are closely linked to left ventricular LGE-% and diastolic dysfunction. Left atrial strain analysis may reveal subtle functional changes in the atrium before the increase in the maximum volume index.

Epicardial adipose tissue volume predicts long term major adverse cardiovascular events in patients with Type 2 diabetes

OBJECTIVE

Epicardial adipose tissue (EAT) is a metabolically active visceral fat depot that plays an important role in coronary atherosclerosis. In this study, our aim was to investigate the relationship between long-term major adverse cardiovascular events (MACEs) and EAT volume detected by coronary computed tomography angiography (CCTA) in patients with Type 2 diabetes mellitus (T2-DM) without previous coronary events.

METHODS

A total of 127 patients with diabetes who underwent CCTA between 2012 and 2014 were enrolled retrospectively. The study population was divided into 2 groups according to whether they experienced or did not experience MACE, which was defined as cardiac death, non-fatal myocardial infarction or unstable angina requiring hospitalization, coronary revascularizations (percutaneous coronary intervention or coronary artery bypass grafting surgery), heart failure, peripheral arterial disease, or ischemic stroke. In both groups, EAT volumes were measured by CCTA.

RESULTS

During 60±7 months follow-up period, 22 participants experienced MACEs. Data were evaluated with univariate and multivariate analyses and receiver operating characteristic (ROC) analysis. Age, male sex, coronary artery disease, hemoglobin A1c, glucose, creatinine, C- reactive protein, and cholesterol levels were found to be associated with MACE. EAT volume (odds ratio [OR]: 1.027; 95% confidence interval [CI]: 1.010‒1.044, p=0.002) and low-density lipoprotein (OR: 1.015; 95% CI: 1.000‒1.030, p=0.050) were found to be independent predictors for MACE. ROC analysis indicated that EAT volumes >123.2 mL had a 72.7% sensitivity and a 77.1% specificity for predicting long-term MACE in patients with T2-DM (area under the curve: 0.820; 95% CI: 0.733-0.908).

CONCLUSION

EAT volume is an independent predictor of long-term MACE in patients with T2-DM without previous coronary events. EAT volume may be used additionally in risk stratification for MACE besides the well-known vascular risk factors in patients with T2-DM.

Whole-body MRI for preventive health screening: Management strategies and clinical implications

PURPOSE

To document the diagnostic yields of whole-body MRI (WB-MRI) screening for asymptomatic individuals by using a classification system that categorizes the findings by clinical relevance and provides a flowchart for further investigations, and to determine the influence of WB-MRI findings on clinical decision-making.

METHODS

In this institutional review board-approved study, a retrospective review of individuals who underwent WB-MRI between 2009 and 2020 was conducted, and asymptomatic participants who underwent non-contrast-enhanced comprehensive WB-MRI for screening were enrolled. Participants were classified into four categories based on WB-MRI findings, and those with relevant findings (i.e., categories 3 and 4) were referred for further diagnostic workup. The participants' medical records were investigated, and interviews were conducted to reveal false-negative findings and identify the number of WB-MRI-triggered treatments.

RESULTS

We included 576 participants (377 [65.4 %] men, 199 [34.6 %] women; mean age, 48.40 ± 10.82 years), of which 266 (46.2 %) and 310 (53.8 %) underwent WB-MRI with 1.5 T and 3.0 T magnets, respectively. Approximately one-third of the participants showed clinically relevant findings, and 65 (11.2 %) received a treatment triggered by WB-MRI. Notably, 15 (2.6 %) and 28 (4.8 %) participants had cancers and intracranial aneurysms, respectively. Of the 576 participants, 16 (2.8 %) had false-negative findings, among which five had cancers.

CONCLUSION

WB-MRI yields numerous important findings that trigger therapeutic interventions in a large sample of asymptomatic adults. However, considering its inherent limitations, WB-MRI might be inadequate for detecting malignancies such as colon, thyroid, and breast cancers; thus, it may serve as a complementary screening method for health-conscious individuals.

Patients with ACL graft deficiency showed a higher frequency of knee osteoarthritis compared with patients with intact ACL graft in the medium term

AIM

To evaluate whether patients with anterior cruciate ligament (ACL) graft tear who do not undergo revision reconstruction surgery are more likely to exhibit osteoarthritic features than patients with intact ACL graft using MRI.

MATERIALS AND METHODS

We retrospectively evaluated our hospital medical archive for identifying all consecutive patients with ACL graft failure who underwent MRI between January 2015 and January 2019. An equal number of patients with intact ACL graft was selected for the control group. An observer with 6 years of musculoskeletal radiology experience evaluated the baseline and last available follow-up MRIs of the patients for bone marrow lesions (BMLs), cartilage defects, osteophytes, anterior tibial translation, and effusion-synovitis.

RESULTS

A total of 130 patients, 118 males (90.8%), and 12 females (9.2%), with the mean age of 29.22 ± 9.3 years, were enrolled in the study. Of 130 patients, 65 had a deficient ACL graft, and 65 had an intact ACL graft. The time from the index injury to the last follow-up MRI was 45 months (IQR, 19) for the study cohort. On the follow-up MRIs, patients with ACL graft deficiency showed more prominent degenerative features compared with the patients with intact ACL graft characterized as follows: higher grades of medial meniscal tears (P = 0.06); higher grades of BMLs in the anteromedial (P = 0.014) and posteromedial (P = 0.006) femur, higher grades of cartilage defects in the medial patella (p = 0.0P); higher grades of osteophytes in the anteromedial (P = 0.018) and central medial femur (p = 0.048), central medial tibia (P = 0.048), and medial patella (P = 0.07); and more frequent anterior tibial translation (P = 0.022).

CONCLUSION

Patients with ACL graft deficiency present with more prominent degenerative features, particularly on the medial side, suggestive of osteoarthritis compared with patients with intact ACL grafts in the medium-term follow-up.

The influence of cardiac motion on radiomics features: radiomics features of non-enhanced CMR cine images greatly vary through the cardiac cycle

OBJECTIVES

The cardiac cycle might impair the reproducibility of radiomics features of cardiac magnetic resonance (CMR) cine images, yet this issue has not been addressed in the previous research. We aim to evaluate whether radiomics features of CMR cine images vary during the cardiac cycle and investigate the reproducibility of radiomics features of CMR cine images.

METHODS

This retrospective study enrolled 59 healthy adults who underwent CMR examination. Two observers segmented the myocardium on a 4D stack of three consecutive mid-ventricular short-axis cine images covering the cardiac cycle. A total of 352 radiomics features were extracted. The coefficient of variation and intraclass correlation coefficient were used to assess the feature variability through the cycle and inter-observer reproducibility, respectively.

RESULTS

Approximately 55% of radiomics features showed large variability through the cardiac cycle. The original features showed more variability than the Laplacian of Gaussian-filtered features (73.8% vs. 48%). The features of 4D stack cine images had a higher proportion of reproducible features (92.0%, 87.7%, and 76.1%) compared with the end-diastolic (77.8%, 62.2%, and 41.7%) and the end-systolic images (81.5%, 74.1%, and 58.8%) for intraclass correlation cut-off values of ³0.80, > 0.85, and > 0.90, respectively.

CONCLUSIONS

Radiomics features of CMR cine images greatly vary during the cardiac cycle. The radiomics features of 4D stack of cine images are more robust compared with end-diastolic and end-systolic cine images in terms of reproducibility. The impact of the cardiac cycle on the reproducibility of the features should be considered when employing CMR cine images radiomics.

KEY POINTS

• There is limited evidence on the impact of cardiac motion on radiomics features of CMR cine images and the reproducibility of the radiomics features of CMR cine images. • Radiomics features of non-enhanced CMR cine images greatly vary during the cardiac cycle, and the number of "reproducible" features shows significant variations according to the cardiac phases. • The impact of cardiac cycle on the reproducibility of the radiomics features should be considered when employing CMR cine images radiomics.

Does measurement of the jugular foramen diameter on MRI help to differentiate transverse sinus thrombosis from unilateral transverse sinus hypoplasia?

BACKGROUND AND PURPOSE

The transverse sinus (TS) is a frequent location of cerebral venous thrombosis. However, unilateral TS hypoplasia is a frequent variation and radiological imaging pitfall in the diagnosis because it may mimic unilateral TS thrombosis. The purpose of this study is to find a cutoff value for bilateral jugular foramen (JF) diameter ratios on magnetic resonance imaging (MRI) for differentiating TS thrombosis from TS hypoplasia.

MATERIALS AND METHODS

We retrospectively reviewed magnetic resonance venography results for 174 patients with reduced unilateral TS caliber resulting from either unilateral thrombosis (80 patients) or unilateral hypoplasia (94 patients). We calculated the ratio by proportioning the diameter of the JF ipsilateral to the TS with caliber reduction to the diameter of the contralateral JF. The Mann-Whitney U test was used to compare the ratios between thrombosis and hypoplasia groups, and the cutoff value was calculated by receiver-operating characteristic curve analysis.

RESULTS

The ratio of bilateral JF diameters was lower in patients with hypoplasia than those with thrombosis (P < .01). The cutoff value to determine the diagnosis of TS hypoplasia with maximum accuracy was 0.638, with a sensitivity of 91.3% and specificity of 64.9%.

CONCLUSION

In equivocal cases, calculating the cutoff value by proportioning the diameter of JF ipsilateral to the TS with caliber reduction to the contralateral JF seems to be an efficient, quick, and straightforward method and valuable aid to differentiate TS thrombosis from TS hypoplasia.

Late gadolinium enhancement on CMRI in patients with LV noncompaction: An overestimated phenomenon?

BACKGROUND AND PURPOSE

Subendocardial fibrosis is recognized finding in left ventricular noncompaction (LVNC); however, the evidence regarding the patterns and the frequency of late gadolinium enhancement (LGE) on cardiac magnetic resonance imaging (CMRI) is controversial. The present study sought to assess the frequency and patterns of LGE in LVNC.

MATERIALS AND METHODS

Patients with a diagnosis of LVNC based on the echocardiographic CMRI criteria were enrolled in this retrospective study. The myocardial noncompacted-to-compacted ratio (NC/C) was perpendicularly measured on short-axis cine images. Two observers jointly assessed the presence of LGE on short-axis LGE images. The long-axis four-chamber and long-axis two-chamber images were used to confirm the presence of LGE if needed.

RESULTS

A total of 42 patients, 20 females (47.7%) and 22 were males (52.3%), were included in the study. The median age of the patients was 32.4 years (range 18-63). LGE was identified in 2 out of 42 patients (4.7%) with LVNC. LGE was identified in the interventricular septum involving the subendocardial layer and noncompacted lateral myocardial wall involving the trabeculae at mid-ventricular and basal levels.

CONCLUSION

LGE is uncommon in patients with LVNC. We highlight that the diagnosis of LVNC in patients with atypical LGE patterns, such as epicardial or transmural enhancement, should be reappraised and the other cardiac diseases should be discarded before establishing the final diagnosis.

Diagnostic Capabilities of MRI Versus 18F FDG PET-CT in Postoperative Patients with Thyroglobulin Positive, 131I-negative Local Recurrent or Metastatic Thyroid Cancer

BACKGROUND

The detection of recurrence or metastasis might be challenging in patients, who underwent total thyroidectomy and radioactive iodine therapy for Differentiated Thyroid Carcinoma (DTC), with increased serum Thyroglobulin (Tg) levels and negative 131I whole body scan (131I-WBS) results.

AIMS

The purpose of this study was to compare the ability of Magnetic Resonance Imaging (MRI) and 18F-fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (18F FDG PET-CT) to detect recurrence or cervical and upper mediastinal metastases in postoperative DTC patients who had negative 131I-WBS despite elevated serum Tg levels.

STUDY DESIGN

This study has a retrospective study design.

METHODS

We evaluated cervical and upper mediastinal MRI and 18F FDG PET-CT of 32 postoperative patients with DTC (26 patients with papillary thyroid carcinoma and 6 patients with follicular thyroid carcinoma).

RESULTS

We evaluated 44 lesions in 32 patients. For all lesions, the Positive Predictive Value, (PPV) Negative Predictive Value (NPV), sensitivity, specificity, and accuracy of MRI were 81.4%, 76.4%, 84.6%, 72.2%, and 79.5% respectively. The PPV, NPV, sensitivity, specificity, and accuracy of 18F FDG PET-CT were 100.0%, 85.7%, 88.4%, 100.0%, and 93.1%, respectively.

CONCLUSION

Although we could not replace 18F FDG PET-CT, MRI might be used as an adjunct to 18F FDG PET-CT for the evaluation of recurrent or cervical and upper mediastinal metastatic thyroid cancers; however, MRI is inadequate for the detection of metastases in small lymph nodes.

The diagnostic value of quantitative texture analysis of conventional MRI sequences using artificial neural networks in grading gliomas

AIM

To explore the value of quantitative texture analysis of conventional magnetic resonance imaging (MRI) sequences using artificial neural networks (ANN) for the differentiation of high-grade gliomas (HGG) and low-grade gliomas (LGG).

MATERIALS AND METHODS

A total of 181 patients, 97 with HGG (53.5%) and 84 with LGG (46.5%) with brain MRI having T2-weighted (W) fluid attenuation inversion recovery (FLAIR), and contrast-enhanced T1W images were enrolled in the present study. Histogram parameters and high-order texture features were extracted using manually placed regions of interest (ROIs) on T2W-FLAIR and contrast-enhanced T1W images covering the whole volume of the tumours. The reproducibility of the features was assessed by interobserver reliability analyses. The cohort was divided into training (n=121) and test partitions (n=60). The training set was used for attribute selection and model development, and the test set was used to evaluate the diagnostic performance of the pre-trained ANNs in discriminating HGG and LGG.

RESULTS

In the test cohort, the ANN models using texture data of T2W-FLAIR and contrast-enhanced T1W images achieved an area under the receiver operating characteristic curve (AUC) of 0.87 and 0.86, respectively. The combined ANN model with selected texture features achieved the highest diagnostic accuracy equating 88.3% with an AUC of 0.92.

CONCLUSIONS

Quantitative texture analysis of T2W-FLAIR and contrast-enhanced T1W enhanced by ANN can accurately discriminate HGG from LGG and might be of clinical value in tailoring the management strategies in patients with gliomas.

Machine learning-based quantitative texture analysis of conventional MRI combined with ADC maps for assessment of IDH1 mutation in high-grade gliomas

PURPOSE

To assess the performance of texture analysis of conventional magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) maps in predicting IDH1 status in high-grade gliomas (HGG).

MATERIALS AND METHODS

A total of 142 patients with HGG were included in the study. IDH1 mutation was present in 48 of 142 HGG (33.8%). Patients were randomly divided into the training cohort (n = 96) and the validation cohort (n = 46). Texture features were extracted via regions of interest on axial T2WI FLAIR, post-contrast T1WI, and ADC maps covering the whole volume of the tumors. The training cohort was used to train the random forest classifier, and the diagnostic performance of the pre-trained model was tested on the validation cohort.

RESULTS

The random forest model of conventional MRI sequences and ADC images achieved diagnostic accuracy of 82.2% and 80.4% in predicting IDH1 status in the validation cohorts, respectively. The combined model of T2WI FLAIR, post-contrast T1WI, and ADC images exhibited the highest diagnostic accuracy equating 86.94% in the validation cohort.

CONCLUSION

Texture analysis of conventional MRI sequences enhanced by ML analysis can accurately predict the IDH1 status of HGG. Adding textural analysis of ADC maps to conventional MRI results in incremental diagnostic performance.

Assessment of ventricular tachyarrhythmia in patients with hypertrophic cardiomyopathy with machine learning-based texture analysis of late gadolinium enhancement cardiac MRI

OBJECTIVE

To assess the diagnostic value of machine learning-based texture feature analysis of late gadolinium enhancement images on cardiac magnetic resonance imaging (MRI) for assessing the presence of ventricular tachyarrhythmia (VT) in patients with hypertrophic cardiomyopathy.

MATERIALS AND METHODS

This retrospective study included 64 patients with hypertrophic cardiomyopathy who underwent cardiac MRI and 24-hour Holter monitoring within 1 year before cardiac MRI. There were 42 men and 22 women with a mean age of 48.13±13.06 (SD) years (range: 20-70 years). Quantitative textural features were extracted via manually placed regions of interest in areas with high and intermediate signal intensity on late gadolinium-chelate enhanced images. Feature selection and dimension reduction were performed. The diagnostic performances of machine learning classifiers including support vector machines, Naive Bayes, k-nearest-neighbors, and random forest for predicting the presence of VT were assessed using the results of 24-hour Holter monitoring as the reference test. All machine learning models were assessed with and without the application of the synthetic minority over-sampling technique (SMOTE).

RESULTS

Of the 64 patients with hypertrophic cardiomyopathy, 21/64 (32.8%) had VT. Of eight machine learning models investigated, k-nearest-neighbors with SMOTE exhibited the best diagnostic accuracy for the presence or absence of VT. k-nearest-neighbors with SMOTE correctly identified 40/42 (95.2%) VT-positive patients and 40/43 (93.0%) VT-negative patients, yielding 95.2% sensitivity (95% CI: 82.5%-99.1%), 93.0% specificity (95% CI: 79.8%-98.1%) and 94.1% accuracy (95% CI: 88.8%-98%).

CONCLUSION

Machine learning-based texture analysis of late gadolinium-chelate enhancement-positive areas is a promising tool for the classification of hypertrophic cardiomyopathy patients with and without VT.

Is there any association between jugular venous reflux and nonpulsatile subjective tinnitus? A preliminary study of four-dimensional magnetic resonance angiography

Objective

To demonstrate whether there is an association between jugular venous reflux and nonpulsatile subjective tinnitus (NST) using real-time four-dimensional magnetic resonance imaging (MRI) angiography.

Materials and Methods

Patients with unilateral NST who underwent contrast-enhanced MRI with a special protocol were included in the study. Thick slab dynamic maximum intensity projection images were obtained including interleaved stochastic trajectories (TWIST)-MRI examination. All patients were requested to perform Valsalva maneuver during the sequence. Jugular venous reflux grading was performed as follows: absence of reflux or if reflux does not reach the base of the skull: grade 0; if reflux reaches the jugular bulb, but no intracranial contrast is observed: grade 1; and if reflux extends into the intracranial cortical veins and/or the cavernous sinus above the jugular bulb: Grade 2.

Results

A total number of 30 patients, 23 male and 7 female, were included in the study. Jugular venous reflux was not identified (Grade 0) in 20 patients. Grade 1 reflux was determined in 7 cases and Grade 2 reflux was observed in 3 cases. Notably, only patients with Grade 2 reflux described worsening of their tinnitus symptoms during the examination and their daily activities as well.

Conclusions

NST might also be associated with hemodynamic problems of the venous system and the MRI protocol starting with TWIST accompanied with Valsalva maneuver is not well-known, yet seems to be a feasible and beneficial method to detect potential jugular venous reflux in NST patients.

Prediction of recurrence in non-muscle invasive bladder cancer patients. Do patient characteristics matter?

PURPOSE

To evaluate patients, diagnosed with non-muscle invasive bladder cancer, according to patient specific parameters including hemoglobin level, estimated glomerular filtration rate (eGFR), body mass index (BMI) and cigarette smoking and to identify if any of these parameters matters in terms of recurrence prediction.

METHODS

231 patients who have undergone transurethral resection of the bladder (TURB) between January 2015 and January 2018 and diagnosed with non-muscle invasive bladder cancer (NMIBC) were included. Patient demographic characteristics including age, sex, BMI and cigarette smoking were assessed. Hemoglobin, creatinine and eGFR values were recorded. Follow-up was performed according to the European Association of Urology (EAU) guidelines' recommendations. Recurrence and progression during follow-up were recorded.

RESULTS

231 patients were included in the study. Median patient BMI, Hb levels, and eGFR values were 26.51 kg/m2 (IQR 5.48), 14,2 g/dL (IQR 2.50), and 83.25 ml/min/1.73m2 (IQR 27.83), respectively. Among all patients, 105 (45%) were ex-smokers and 78 (33%) were current smokers, 41 had anemia (17.7%), 37 (16%) patients were obese; 104 (45%) had mildly impaired renal function and 34 (14.7%) had impaired renal function. During follow-up, 67 (29%) patients had disease recurrence and 21 (9.1%) had disease progression (9.1%). Univariate and multivariate analyses revealed significant relationship between recurrence and obesity, impaired renal function and cigarette smoking.

CONCLUSIONS

Recurrence is a commonly encountered unfortunate consequence of NMIBC, and obesity, renal failure, history of smoking and anemia seem to increase the rate of recurrence among bladder cancer patients.

Shear Wave Elastography of the Lumbar Multifidus Muscle in Patients With Unilateral Lumbar Disk Herniation

OBJECTIVES

To assess lumbar multifidus muscle stiffness in patients with unilateral lumbar disk herniation (LDH) causing nerve root compression using shear wave elastography (SWE).

METHODS

Thirty-three patients with unilateral subarticular LDH (L3-L4, L4-L5, and L5-S1) causing nerve root compression, diagnosed by magnetic resonance imaging, were enrolled in the study. Exclusion criteria were bilateral or multilevel LDH confirmed on magnetic resonance imaging, bilateral leg symptoms, and patients with a history of any spinal operation, malignancy, trauma, infection, spondylolisthesis, severe lateral recess stenosis, spinal canal stenosis, and substantial comorbidities. Two observers separately evaluated the multifidus muscle using SWE. Shear wave elastographic examinations of the muscle were performed slightly below the herniation using the spinous process of the vertebra as a landmark. The stiffness of the muscle between affected and normal sides was compared. Moreover, the correlation between the stiffness and duration of the symptoms and the correlation between the stiffness and severity of the nerve compression were also calculated.

RESULTS

The mean stiffness values of the multifidus muscle on the affected side (mean ± SD: observer 1, 14.08 ± 3.57 kPa; observer 2, 13.70 ± 4.05 kPa) were significantly lower compared to the contralateral side (observer 1, 18.81 ± 3.95 kPa; observer 2, 18.28 ± 4.12 kPa; P < .001). The muscle stiffness had a moderate negative correlation with the duration of the symptoms and the severity of the nerve compression (observer 1, r = -0.535; observer 2, r = -0.458; P < .001).

CONCLUSIONS

The multifidus muscle on the ipsilateral side of the LDH showed reduced stiffness values, and stiffness values were negatively correlated with the disease duration and severity of the nerve compression. Further studies might reveal the potential role of SWE of the multifidus muscle in determining clinical outcomes and assessing effectiveness treatment in patients with LDH.

Evaluation of lumbar multifidus muscle in patients with lumbar disc herniation: are complex quantitative MRI measurements needed?

Objective

To assess the composition of lumbar multifidus muscle, in patients with unilateral lumbar disc herniation causing nerve compression, using quantitative and qualitative magnetic resonance imaging (MRI) measurement methods.

Methods

Two radiologists retrospectively measured MRI signal intensity of the multifidus muscle, as high intensity represents more fat, and visually graded the fat content using a 5-point grading system in patients with unilateral subarticular lumbar disc herniation. Findings from the herniated and contralateral sides were compared. The association between fat content and severity of nerve compression and symptom duration were also evaluated.

Results

Ninety patients (aged 24–70 years) were included. Signal intensity of the affected multifidus muscle was significantly higher versus the contralateral muscle for quantitative measurements and qualitative scoring for both investigators. Significant correlations were observed between the severity of nerve compression and symptom duration and the degree of fat content in the affected multifidus muscle.

Conclusions

Higher fat composition was observed in the multifidus muscle ipsilateral to the lumbar disc herniation versus the contralateral side. Straightforward visual grading of muscle composition regarding fat infiltration appeared to be as useful as quantitative measurement.

Prognostic value of ADC measurements in predicting overall survival in patients undergoing 90Y radioembolization for colorectal cancer liver metastases

AIM

To assess the ability of diffusion-weighted imaging (DWI) in predicting the overall survival in patients who underwent Yttrium 90 radioembolization (⁹⁰Y-RE) for colorectal liver metastases (CLM) with other well-established clinical and imaging parameters by comparing the pre- and post-treatment apparent diffusion coefficient (ADC) values of the lesions.

METHODS

A total of 81 metastatic lesions of 27 consecutive patients who underwent DWI before and after the ⁹⁰Y-RE session were enrolled in the study. ADC values were calculated from the entire (ADC_e) and peripheral (ADC_p) tumor on pre- and post-treatment DWI, and any relative increase in ADC >0% accepted as a functional imaging response. The impact of functional imaging response in addition to other well-known parameters including Response Evaluation Criteria in Solid Tumors (RECIST), hepatic tumor burden, Eastern Cooperative Oncology Group performance status (ECOG-PS) and the presence of extrahepatic metastases in predicting overall survival (OS) was assessed using Kaplan-Meier curves and Cox-regression analyses.

RESULTS

The median OS of the patients was 10 months (range, 6-20 months) while the median OS of the responders being significantly longer than the non-responders for ADC_e and ADC_p (median 11 vs 7 months, P = 0.003; median 12 vs. 7 months, P < 0.0001, respectively). The RECIST score was also significantly affected the OS (progressive or stable disease median 8 months vs. partial response 15 indent months, P = 0.019). The other parameters including hepatic tumor burden, gender, ECOG score, the involvement of the liver lobes, and the presence of extrahepatic metastases were not associated with the OS. In multivariate analysis, only ADC_p remained as an independent predictor of OS (P = 0.003, HR = 19.878).

CONCLUSION

Any increase in relative ADC_p or ADC_e values after Y90-RE treatment was associated with longer OS in CLM patients, and DWI seems to be valuable imaging biomarker in predicting OS in CLM patients during the early post-interventional period after ⁹⁰Y-RE.

Apparent diffusion coefficient characteristics of parenchymal neuro-Behçet's disease

AIM

To evaluate apparent diffusion coefficient (ADC) characteristic of parenchymal neuro-Behçet's disease (NBD).

METHODS

We retrospectively reviewed cranial magnetic resonance imaging (MRI) examinations of NBD patients with acute or chronic parenchymal lesions. ADC measurements of the lesions and contralateral normal brain parenchyma were performed by a consensus of two radiologists. To compare the ADC value of the chronic and acute lesions, relative ADC values (rADC) were calculated. The ratio of the lesions' ADC to contralateral normal brain parenchyma ADC yielded a rADC value of the lesions. Contrast enhancement patterns and the locations of the lesions were also noted.

RESULTS

A total of 24 NBD patients with 45 parenchymal lesions, 25 acute, and 20 chronic, were enrolled in the study. A significant difference was observed between the mean ADC value of the acute lesions (1074.48 ± 138.31 m/s) and the mean ADC value of the contralateral normal brain parenchyma (841.20 ± 142.96 m/s; P < 0.0001). A significant difference was observed between the mean ADC value of the chronic lesions (1069.95 ± 143.95 m/s) and the mean ADC value of the contralateral normal brain parenchyma (793.90 ± 96.71 m/s; P < 0.0001). No significant difference was observed between the mean rADC (1.35 ± 0.20) and the mean rADC value of the chronic lesions (1.29 ± 0.15; P = 0.22).

CONCLUSIONS

ADC measurements might provide substantial information about the histopathological aspect of parenchymal NBD lesions.

Shear Wave Elastography in the Evaluation of the Kidneys in Pediatric Patients with Unilateral Vesicoureteral Reflux

OBJECTIVES

To evaluate the ability of shear wave elastography (SWE) to detect renal parenchymal scar formation in patients with vesicoureteral reflux.

METHODS

We prospectively evaluated 49 patients with unilateral grade 2 or higher-degree VUR. All patients underwent dimercaptosuccinic acid (DMSA) scintigraphy for evaluation of the renal parenchymal scar. After the DMSA scan, 2 radiologists, who were blinded to clinical data and each other's measurements, evaluated the kidneys of the patients using SWE. The kidneys were divided into 3 parts: upper pole, middle region, and lower pole, and 3 regions of interest were placed to each part. Shear wave velocity (SWV) values were calculated using meters per second as a unit and recorded for each region. Afterward, SWV values were compared to DMSA results.

RESULTS

There was no significant difference between the observers' mean SWV values of kidneys with VUR without scar formation (mean ± SD, 2.11 ± 0.06 and 2.09 ± 0.05 m/s) and the contralateral normal kidney SVW values (2.11 ± 0.06 and 2.10 ± 0.05 m/s; P = .936 and .724, respectively). We observed a significant difference between the mean SWV values of the kidneys with VUR accompanied by scar formation (2.28 ± 0.10 and 2.27 ± 0.11 m/s) and the mean SWV values of the contralateral normal kidneys (2.09 ± 0.05 and 2.10 ± 0.04 m/s; P < .001 for both observers).

CONCLUSIONS

Shear wave elastography could detect scar tissue in kidneys; however, the variability of the stiffness due to the kidney's complex structure, and variations in blood perfusion and the glomerular filtration rate of the kidney might limit the use of SWE in current clinical diagnostic algorithms for VUR.

Diagnostic values of edema-sensitive T2-weighted imaging, TSE T1-weighted early contrast-enhanced imaging, late gadolinium enhancement, and the Lake Louise criteria in assessing acute myocarditis: A single-center cardiac magnetic resonance study

OBJECTIVE

The aim of this study was to evaluate the diagnostic accuracy of the Lake Louise consensus criteria using cardiac magnetic resonance (CMR) imaging assessment of edema, hyperemia, and late gadolinium enhancement (LGE) in the diagnostic determination of acute myocarditis.

METHODS

A total of 44 patients with acute myocarditis and 24 healthy controls were included in this retrospective study. The presence of edema was defined as a myocardial mean signal intensity >1.9 times that of the skeletal muscle in the same slice on T2-weighted short tau inversion-recovery sequences. Hyperemia was defined as an early gadolinium enhancement ratio (EGEr) ≥4 calculated using the contrast-enhancement of the myocardium and skeletal muscle on TSE T1-weighted sequences, and LGE was assessed by visual examination. The reference methods used to determine the presence of myocarditis were based on the European Society of Cardiology Working Group on Myocardial and Pericardial Diseases guidelines for clinical and biochemical findings.

RESULTS

The diagnostic accuracy of edema, hyperemia, LGE, and the Lake Louise criteria (at least 2 of 3 components) was 75.7%, 64.2%, 88.5%, and 84.2%, respectively. Among the 3 components of the Lake Louise criteria, edema had the highest specificity (100%), and LGE had the highest sensitivity (86%). The use of LGE and/or edema as a criterion for acute myocarditis revealed the highest diagnostic accuracy (92.8%) among the CMR sequences and combinations of components examined.

CONCLUSION

LGE and/or edema as a sole criterion for the diagnosis of acute myocarditis demonstrated better diagnostic accuracy than the Lake Louise criteria. The use of EGEr did not improve the performance of CMR-based diagnosis. Alternatives to the use of EGEr are recommended for the diagnosis of acute myocarditis.

Assessment of the common carotid artery wall stiffness by Shear Wave Elastography in Behcet's disease

AIM

To evaluate endothelial dysfunction and subclinical atherosclerosis in Behcet's disease (BD) by measuring the common carotid artery (CCA) wall stiffness and carotid intima-media thickness (CIMT).

MATERIALS AND METHODS

We prospectively evaluated CIMT and the CCA wall stiffness of 34 BD patients and 28 age/sex-matched controls. CIMT measurements were performed from the posterior wall of the carotid artery approximately 10 mm proximal to the initiation of the carotid bulb using B-mode ultrasound. The stiffness of the CCA was measured from the superficial wall of the CCA using shear wave elastography (SWE). SWE measurements were recorded as shear wave velocity (SWV) using m/s as a unit.

RESULTS

The mean right (0.5±0.11 mm) and left (0.5±0.14 mm) CIMT of the patients were significantly higher compared to the mean right (0.41±0.07 mm) and left (0.41±0.11 mm) CIMT of the healthy controls (p=0.001 and p= 0.003 respectively). The mean right (3.72±0.94 m/s) and left (3.57±0.72 m/s) CCA wall stiffness of the patients were significantly higher compared to the mean right (2.42±0.49 m/s) and left (2.56±0.49 m/s) CCA wall stiffness of the controls (p<0.001 for both).

CONCLUSIONS

SWE seems to be a promising modality to evaluate endothelial dysfunction in BD by interpreting the arterial stiffness, and SWE might be an important adjunct to clinical and laboratory findings, and imaging modalities to assess cardiovascular risk in BD. Moreover, SWE evaluation of the arterial stiffness might assist us to understand pathophysiological aspects of BD.

Evaluation of parenchymal thyroid diseases with multiparametric ultrasonography

Aim:

Differential diagnosis of parenchymal thyroid diseases by gray-scale ultrasound is quite difficult for a radiologist as the findings are very similar to each other. In this study we aimed to assess some quantitative spectral Doppler parameters, resistivity index (RI), acceleration time (AT), and quantitative elastography [shear wave velocity (SWV)] together to show their reliability for differential diagnosis of parenchymal thyroid diseases.

Materials and Methods:

We retrospectively reviewed findings of 227 patients (179 females, 48 males) that underwent spectral Doppler ultrasound and acoustic radiation force impulse between October 2013 and March 2016. Ages of the patients were between 18 and 74 years (39.52 ± 12.67). Based on clinical and laboratory findings, patients were divided into five groups (N: Normal, EH: Early Hashimoto, H: Late Hashimoto, M: Nodular Thyroid Disease, HM: Hashimoto + Nodular Thyroid Disease). Detailed statistical analyses were done on parameters such as age, gender, volume information, and RI, AT (ms), SWV (m/s).

Results:

No significant effect of gender or volume on the differentiation of disease pattern (Chi-square test: P = 0.306, Kruskal-Wallis test: P = 0.290) was found in this study. RI (0.41 ± 0.06) and SWV values (1.19 ± 0.18 m/s) were the lowest. AT values (>55 ms) were the highest in EH group (area under the curve: 0.913). Existence of H decreased RI and SWV values, while it extended AT in a different thyroid disease.

Conclusion:

Thyroid parenchymal diseases could be classified and differentiated from each other by measuring RI, AT, and SWV values quantitatively. So, in suspicious cases, these parameters could be a reliable asset for differential diagnosis.

Apparent Diffusion Coefficient Measurement in Mediastinal Lymphadenopathies: Differentiation between Benign and Malignant Lesions

Objectives:

We aimed to prospectively assess the diagnostic value of apparent diffusion coefficient (ADC) measurement in the differentiation of benign and malignant mediastinal lymphadenopathies.

Materials and Methods:

The study included 63 consecutive patients (28 women, 35 men; mean age 59.3 years) with 125 mediastinal lymphadenopathies. Echoplanar diffusion-weighted magnetic resonance imaging of the mediastinum was performed with b-factors of 0 and 600 mm²/s before mediastinoscopy and mediastinotomy, and ADC values were measured. The ADC values were compared with the histological results, and statistical analysis was done. P < 0.05 was considered statistically significant.

Results:

The mean ADC value of malignant mediastinal lymphadenopathy (1.030 ± 0.245 × 10⁻³ mm²/s) was significantly lower (P < 0.05) when compared to benign lymphadenopathies (1.571 ± 0.559 × 10⁻³ mm²/s). For differentiating malignant from benign mediastinal lymphadenopathy, the best result was obtained when an ADC value of 1.334 × 10⁻³ mm²/s was used as a threshold value; area under the curve 0.848, accuracy 78.4%, sensitivity 66%, specificity of 86%, positive predictive value 76.7%, and negative predictive value of 79.2%. Interobserver agreement was excellent for ADC measurements.

Conclusions:

ADC measurements could be considered an important supportive method in differentiating benign from malignant mediastinal lymphadenopathies.

Bilateral Cystic Adrenal Neuroblastoma with Cystic Liver metastasis

Bilateral congenital cystic adrenal neuroblastoma (NB) with cystic liver metastasis is a very rare condition and only few cases have been reported in the literature. Herein we report a case of a congenital bilateral cystic adrenal NB with cystic liver metastasis and briefly discuss characteristic imaging features of cystic NB.

Elastography in Distinguishing Benign from Malignant Thyroid Nodules

AIM

The aim of this study is to test the diagnostic success of strain elastography in distinguishing benign from malignant thyroid nodules.

MATERIALS AND METHODS

The size, echogenicity, and halo integrity of 293 thyroid nodules and the presence of microcalcification in these nodules were evaluated on gray-scale examination. Doppler characteristics and elastography patterns were also evaluated and recorded. Nodules were classified in four categories (patterns 1-4) based on elastographic examination.

RESULTS

According to the cytopathological findings, 222 nodules were benign, and 71 nodules were malignant. The risk of a nodule to be malignant was 3.8 times increased by hypoechogenicity, 7.7 times increased by the presence of microcalcification, and 11.5 times increased by the absence of halo. On Doppler patterns, the presence of central vascularity increased the malignancy risk of a nodule by 5.8 times. According to the receiver operating characteristic analysis, patterns 3 and 4 were malignant, and patterns 1 and 2 were benign. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of elastography were 100%, 80.2%, 61.7%, 100%, and 85%, respectively.

CONCLUSION

Strain elastography can be used as a noninvasive method in distinguishing benign from malignant thyroid nodules and in identifying the patients who would undergo surgery.