Cardiac Magnetic Resonance-Derived Indexed Volumes and Volume Ratios of the Cardiac Chambers Discriminating Group 2 Pulmonary Hypertension From Other World Health Organization Groups.

OBJECTIVE: The aims of the study were to assess the performance of cardiac magnetic resonance (CMR)-derived cardiac chamber volumes and volume ratios to identify group 2 pulmonary hypertension (PH) patients and to determine their cutoff values with the highest sensitivity and specificity. METHODS: One hundred six patients underwent CMR, 2 months after the diagnosis of PH by right heart catheterization. We classified patients with pulmonary capillary wedge pressure of greater than 15 mm Hg as group 2 PH. Cardiac chamber volumes indexed to the body surface area and volume ratios were correlated to the type of PH. Their sensitivity and specificity to detect group 2 PH were examined at various cutoff points. RESULTS: The most appropriate cutoff values to designate group 2 PH patients with high sensitivity and specificity were as follows: left atrium volume index of 54.72 mL/m2 or greater, right ventricle volume/left atrium volume of 2.07 or less, and right atrium volume/left atrium volume of 1.61 or less. CONCLUSIONS: Cardiac magnetic resonance-derived cardiac chamber volume indices and volume ratios can determine group 2 PH diagnosis with high sensitivity and specificity.

Novel MRI-Based CAD System for Early Detection of Thyroid Cancer Using Multi-Input CNN.

Early detection of thyroid nodules can greatly contribute to the prediction of cancer burdening and the steering of personalized management. We propose a novel multimodal MRI-based computer-aided diagnosis (CAD) system that differentiates malignant from benign thyroid nodules. The proposed CAD is based on a novel convolutional neural network (CNN)-based texture learning architecture. The main contribution of our system is three-fold. Firstly, our system is the first of its kind to combine T2-weighted MRI and apparent diffusion coefficient (ADC) maps using a CNN to model thyroid cancer. Secondly, it learns independent texture features for each input, giving it more advanced capabilities to simultaneously extract complex texture patterns from both modalities. Finally, the proposed system uses multiple channels for each input to combine multiple scans collected into the deep learning process using different values of the configurable diffusion gradient coefficient. Accordingly, the proposed system would enable the learning of more advanced radiomics with an additional advantage of visualizing the texture patterns after learning. We evaluated the proposed system using data collected from a cohort of 49 patients with pathologically proven thyroid nodules. The accuracy of the proposed system has also been compared against recent CNN models as well as multiple machine learning (ML) frameworks that use hand-crafted features. Our system achieved the highest performance among all compared methods with a diagnostic accuracy of 0.87, specificity of 0.97, and sensitivity of 0.69. The results suggest that texture features extracted using deep learning can contribute to the protocols of cancer diagnosis and treatment and can lead to the advancement of precision medicine.

A Comprehensive Computer-Assisted Diagnosis System for Early Assessment of Renal Cancer Tumors.

Renal cell carcinoma (RCC) is the most common and a highly aggressive type of malignant renal tumor. In this manuscript, we aim to identify and integrate the optimal discriminating morphological, textural, and functional features that best describe the malignancy status of a given renal tumor. The integrated discriminating features may lead to the development of a novel comprehensive renal cancer computer-assisted diagnosis (RC-CAD) system with the ability to discriminate between benign and malignant renal tumors and specify the malignancy subtypes for optimal medical management. Informed consent was obtained from a total of 140 biopsy-proven patients to participate in the study (male = 72 and female = 68, age range = 15 to 87 years). There were 70 patients who had RCC (40 clear cell RCC (ccRCC), 30 nonclear cell RCC (nccRCC)), while the other 70 had benign angiomyolipoma tumors. Contrast-enhanced computed tomography (CE-CT) images were acquired, and renal tumors were segmented for all patients to allow the extraction of discriminating imaging features. The RC-CAD system incorporates the following major steps: (i) applying a new parametric spherical harmonic technique to estimate the morphological features, (ii) modeling a novel angular invariant gray-level co-occurrence matrix to estimate the textural features, and (iii) constructing wash-in/wash-out slopes to estimate the functional features by quantifying enhancement variations across different CE-CT phases. These features were subsequently combined and processed using a two-stage multilayer perceptron artificial neural network (MLP-ANN) classifier to classify the renal tumor as benign or malignant and identify the malignancy subtype as well. Using the combined features and a leave-one-subject-out cross-validation approach, the developed RC-CAD system achieved a sensitivity of 95.3%±2.0%, a specificity of 99.9%±0.4%, and Dice similarity coefficient of 0.98±0.01 in differentiating malignant from benign tumors, as well as an overall accuracy of 89.6%±5.0% in discriminating ccRCC from nccRCC. The diagnostic abilities of the developed RC-CAD system were further validated using a randomly stratified 10-fold cross-validation approach. The obtained results using the proposed MLP-ANN classification model outperformed other machine learning classifiers (e.g., support vector machine, random forests, relational functional gradient boosting, etc.). Hence, integrating morphological, textural, and functional features enhances the diagnostic performance, making the proposal a reliable noninvasive diagnostic tool for renal tumors.

Peripheral Nerve Sheath Tumors of Head and Neck: Imaging-Based Review of World Health Organization Classification.

We aim to review the imaging appearance of peripheral nerve sheath tumors (PNSTs) of head and neck according to updated fourth edition of World Health Organization classification. Peripheral nerve sheath tumor can be sporadic or associated with neurofibromatosis type 1, neurofibromatosis type 2, and schwannomatosis. Schwannoma is the most common benign PNST that can be intracranial or extracranial and appears heterogeneous reflecting its histologic composition. Melanotic schwannoma is a different entity with high prediction of malignancy; it shows hypointense signal on T2-weighted image. Neurofibroma can present by localized, plexiform, or diffuse lesion. It usually appears homogeneous or shows a characteristic target sign. Perineurioma can be intraneural seen with the nerve fiber or extraneural appearing as a mass. Solitary circumscribed neuroma and neurothekeoma commonly present as dermal lesions. Nerve sheath myxoma may exhibit high signal on T1 weighted image. Benign triton tumors can be central, aggressive lesion, or peripheral nonaggressive lesion. Granular cell tumor shows hypointense signal on T2 weighted image. Neuroglial heterotopia most commonly occurs in the nasal cavity. Ectopic meningioma arises from ectopic arachnoid cells in the neck. In hybrid PNST, combined histological features of benign PNST occur in the same lesion. Malignant PNSTs are rare with an aggressive pattern. Computed tomography and magnetic resonance imaging are complementary studies to determine the location and extent of the tumor. Advanced magnetic resonance sequences, namely, diffusion-weighted imaging and dynamic contrast enhancement, can help in differentiation of benign from malignant PNST.

Neck Imaging Reporting and Data System: What Does Radiologist Want to Know?

The aim of this work was to review Neck Imaging Reporting and Data System (NI-RADS) that was designed for reporting and surveillance of head and neck cancer after therapy and their subsequent management. The categories of NI-RADS can be designated as belonging in 1 of the 4 categories: negative; low suspicion; high suspicion; and definite recurrence. Lexicon of NI-RADS-1 shows nonmass-like distortion of soft tissues, NI-RADS-2 lesions divided into mucosal (2A) versus deep (2B) abnormalities, NI-RADS-3 primary site can either be a submucosal or deep lesion, and NI-RADS-4 is a biopsy-proven residual or recurrent disease. The NI-RADS Lexicon of radiology reporting categories linked to management protocols and surveillance for these patients. Neck Imaging Reporting and Data System is to provide guidance for next-imaging decisions either a follow-up period, biopsy, or surgery.

Imaging of Neuronal and Mixed Glioneuronal Tumors.

Neuronal and mixed glioneuronal tumors represent a group of neoplasms with varying degrees of neural and glial elements. Their age of presentation varies, but they are most commonly seen in children and young adults. With the exception of anaplastic ganglioglioma and other atypical variants, most lesions are low grade; however, they can have significant morbidity because of seizures, mass effect, or difficult to treat hydrocephalus. Although many tumors show overlapping clinical and imaging features, some have relatively distinctive imaging characteristics that may aid in narrowing the differential diagnosis. In this review, we discuss relevant clinical and pathologic characteristics of these tumors and provide an overview of conventional and advanced imaging features that provide clues as to the diagnosis.

Liver Imaging Reporting and Data System Version 2018: What Radiologists Need to Know.

In this article, we aim to review Liver Imaging Reporting and Data System version 18 (LI-RADS v2018). Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy. Liver Imaging Reporting and Data System developed for standardizing interpreting, reporting, and data collection of HCC describes 5 major features for accurate HCC diagnosis and several ancillary features, some favoring HCC in particular or malignancy in general and others favoring benignity. Untreated hepatic lesions LI-RADS affords 8 unique categories based on imaging appearance on computed tomography and magnetic resonance imaging, which indicate the possibility of HCC or malignancy with or without tumor in vein. Furthermore, LI-RADS defines 4 treatment response categories for treated HCCs after different locoregional therapy. These continuous recent updates on LI-RADS improve the communication between the radiologists and the clinicians for better management and patient outcome.

Interobserver Agreement of Magnetic Resonance Imaging of Liver Imaging Reporting and Data System Version 2018.

AIM: This study aimed to assess the interobserver agreement of magnetic resonance (MR) imaging of Liver Imaging Reporting and Data System version 2018 (LI-RADS v2018). SUBJECTS AND METHODS: Retrospective analysis was done for 119 consecutive patients (77 male and 42 female) at risk of hepatocellular carcinoma who underwent dynamic contrast MR imaging. Image analysis was done by 2 independent and blinded readers for arterial phase hyperenhancement, washout appearance, enhancing capsule appearance, and size. Hepatic lesions were classified into 7 groups according to LI-RADS v2018. RESULTS: There was excellent interobserver agreement of both reviewers for LR version 4 (κ = 0.887, P = 0.001) with 90.76% agreement. There was excellent interobserver agreement for nonrim arterial phase hyperenhancement (κ = 0.948; 95% confidence interval [CI], 0.89-0.99; P = 0.001), washout appearance (κ = 0.949; 95% CI, 0.89-1.0; P = 0.001); and enhancing capsule (κ = 0.848; 95% CI, 0.73-0.97; P = 0.001) and excellent reliability of size (interclass correlation, 0.99; P = 0.001). There was excellent interobserver agreement for LR-1 (κ = 1.00, P = 0.001), LR-2 (κ = 0.94, P = 0.001), LR-5 (κ = 0.839, P = 0.001), LR-M (κ = 1.00, P = 0.001), and LR-TIV (κ = 1.00; 95% CI, 1.0-1.0; P = 0.001), and good agreement for LR-3 (κ = 0.61, P = 0.001) and LR-4 (κ = 0.61, P = 0.001). CONCLUSION: MR imaging of LI-RADS v2018 is a reliable imaging modality and reporting system that may be used for standard interpretation of hepatic focal lesions.

Assessment of Tamoxifen-Related Endometrial Changes in Premenopausal Female Patients With Diffusion-Weighted Magnetic Resonance Imaging.

PURPOSE: To evaluate tamoxifen-related endometrial changes in premenopausal female patients with diffusion-weighted magnetic resonance imaging (DWI). METHODS: This prospective study was performed on 71 premenopausal female patients (mean age, 41 years) who were receiving tamoxifen therapy. All patients underwent magnetic resonance imaging with DWI of the pelvis and hysteroscopic-guided endometrial biopsy. The apparent diffusion coefficient (ADC) values of the endometrial plate were calculated and correlated with pathological results. RESULTS: The mean ADCs of tamoxifen-related benign endometrial lesions (1.35 ± 0.19 and 1.32 ± 0.13 × 10 mm/s) were significantly higher (P = 0.001) than those of normal endometrial plate (0.95 ± 0.11 and 0.93 ± 0.11 × 10 mm/s) by both reviewers, respectively. The cutoff ADC values used to differentiate tamoxifen-related benign endometrial lesions from normal endometrium were 1.07 and 1.02 × 10 mm/s with areas under the curve of 0.94 and 0.93 and accuracy of 94.4 and 95.8 by both reviewers, respectively. The mean ADC values of endometrial polyp (EP) (1.44 ± 0.19 and 1.42 ± 0.22 × 10 mm/s) were significantly higher (P = 0.001) than those of endometrial hyperplasia (EH) (1.25 ± 0.19 and 1.23 ± 0.19 × 10 mm/s) by both reviewers, respectively. The cutoff ADC values used to differentiate EP from EH were 1.38 × 10 and 1.36 × 10 mm/s with areas under the curve of 0.81 and 0.77 and accuracy of 80% and 70% by both reviewers, respectively. There was an insignificant difference in ADC value between typical and atypical EH. The ADC values of endometrial cancer (0.80 and 0.78 × 10 mm/s) were lower than those of tamoxifen-related benign endometrial lesions. The final diagnosis was normal endometrium (n = 36), benign endometrial lesions either EH (n = 17), or EP (n = 16), and endometrial cancer in only 2 patients. CONCLUSIONS: We concluded that DWI helps in detection and characterization of different tamoxifen-related endometrial changes in the premenopausal female patients.

Imaging Findings of Klippel-Trenaunay Syndrome.

We aim to review the imaging findings of Klippel-Trenaunay syndrome. This disorder characterized clinically by a triad of capillary malformations manifesting as a port-wine stain, venous varicosities typically along the lateral aspect of the lower extremities, and bone and/or soft tissue hypertrophy. Imaging of extremities shows unilateral venous varicosities, persistent embryonic veins, anomalous of the superficial and deep venous system, low-flow venolymphatic malformations, and bony and soft tissue hypertrophy. Other findings include neurospinal as cavernoma, aneurysm, and hemimegalencephaly, pulmonary as pulmonary thromboembolism and pulmonary hypertension and visceral as gastrointestinal and genitourinary vascular anomalies. Imaging may detect associated lesions and differentiate from simulating lesions.

Odontogenic Tumors: Imaging-Based Review of the Fourth Edition of World Health Organization Classification.

The fourth edition of World Health Organization (2017) classified odontogenic tumors according to the tissue of origin. Epithelial odontogenic tumors include ameloblastomas, calcifying epithelial odontogenic tumors, adenomatoid odontogenic tumors, and squamous odontogenic tumors. Mixed epithelial and mesenchymal odontogenic tumors include odontomas, ameloblastic fibromas, dentigenic ghost cell odontogenic tumors, and primordial odontogenic tumors. Mesenchymal odontogenic tumors include cementoblastomas, cement-ossifying fibromas, odontogenic fibromas, and odontogenic myxomas. Malignant odontogenic tumors are either carcinomas or sarcomas. The imaging appearance of odontogenic tumors varies according to its category. Computed tomography and magnetic resonance imaging play an important role in localization, characterization, and extension of odontogenic tumors to the teeth and surrounding tissue.

Apparent Diffusion Coefficient of the Placenta and Fetal Organs in Intrauterine Growth Restriction.

PURPOSE: This study aimed to assess apparent diffusion coefficient (ADC) of the placenta and fetal organs in intrauterine growth restriction (IUGR). MATERIALS AND METHODS: A prospective study of 30 consecutive pregnant women (aged 21-38 years with mean age of 31.5 years and a mean gestational week of 35 ± 2.3) with IUGR and 15 age-matched pregnant women was conducted. All patients and controls underwent diffusion-weighted magnetic resonance imaging. The ADCs of the placenta and fetal brain, kidney, and lung were calculated and correlated with neonates needing intensive care unit (ICU) admission. RESULTS: There was a significant difference in ADC of the placenta and fetal brain, lung, and kidney (P = 0.001, 0.001, 0.04, and 0.04, respectively) between the patients and the controls. The cutoff ADCs of the placenta and fetal brain, lung, and kidney used to detect IUGR were 1.45, 1.15, 1.80, and 1.40 × 10 mm/s, respectively, with areas under the curve (AUCs) of 0.865, 0.858, 0.812, and 0.650, respectively, and accuracy values of 75%, 72.5%, 72.5%, and 70%, respectively. Combined ADC of the placenta and fetal organs used to detect IUGR revealed an AUC of 1.00 and an accuracy of 100%. There was a significant difference in ADC of the placenta and fetal brain, lung, and kidney between neonates needing admission and those not needing ICU admission (P = 0.001, 0.001, 0.002, and 0.002, respectively). The cutoff ADCs of the placenta and fetal brain, lung, and kidney used to define neonates needing ICU were 1.35, 1.25, 1.95, and 1.15 × 10 mm/s with AUCs of 0.955, 0.880, 0.884, and 0.793, respectively, and accuracy values of 86.7%, 46.7%, 76.7%, and 70%, respectively. Combined placental and fetal brain ADC used to define neonates needing ICU revealed an AUC of 0.968 and an accuracy of 93.3%. CONCLUSION: Combined ADC of the placenta and fetal organs can detect IUGR, and combined ADC of the placenta and fetal brain can define fetuses needing ICU.

Imaging of Pulmonary Atresia With Ventricular Septal Defect.

The aim of this article was to review computed tomography angiography and magnetic resonance angiography of pulmonary atresia with ventricular septal defect. This disorder is a rare complex congenital heart disease. Preoperative imaging of pulmonary atresia with ventricular septal defect with computed tomography angiography and magnetic resonance angiography is important for complete anatomical delineation and planning for treatment. Preoperative imaging used for assessment of the main pulmonary artery (its size, valve, and confluence), aortopulmonary collaterals (its origin, insertion, course, and size), presence of patent ductus arteriosus, other sources of collaterals as bronchial and coronary arteries, and pattern of pulmonary arborization. Imaging can detect associated aortic, pulmonary venous and coronary anomalies, and other congenital heart disease. Postoperative imaging after unifocalization and stent is for assessment of patency, stenosis, and occlusion of stent or perivascular lesions as seroma.

Assessment of Liver and Spleen in Children With Gaucher Disease Type 1 With Chemical Shift Imaging.

PURPOSE: The aim of this study was to assess of liver and spleen in children with Gaucher disease type 1 with chemical shift imaging. METHODS: Retrospective analysis was conducted on 36 untreated children with Gaucher disease type 1 and 15 age- and sex-matched control children who underwent chemical shift imaging of the abdomen. The hepatic and splenic fat fraction was calculated. The Pediatric Gaucher Severity Scoring System, hematologic parameters, and enzyme assay of the disease were calculated and correlated with hepatic and splenic fat fraction. RESULTS: The mean hepatic fat fraction in Gaucher disease was 14.1 ± 3.1 (95% confidence interval [CI], 12.9-15.2) was significantly higher (P = 0.001) than that of control subjects 5.2 ± 0.9 (95% CI, 4.7-5.7). The mean splenic fat fraction in Gaucher disease was 11.2 ± 2.9 (95% CI, 11.2 ± 2.9), and that of control was 4.5 ± 0.9 (95% CI, 4.02-5.2). The thresholds of hepatic and splenic fat fraction used to differentiate patients from control subjects were 0.47 and 0.39 with areas under the curve of 0.947 and 0.999, respectively. The hepatic and splenic fat fraction is correlated with the Pediatric Gaucher Severity Scoring System (r = -0.523, -0.602), hemoglobin concentration (r = -0.491, -0.505), platelet count (r = -0.593, -0.24), ß-glucosidase (r = 0.519, 0.549), and chitotriosidase (r = -0.03, 0.267), respectively. CONCLUSIONS: Hepatic and splenic fat fraction is a promising quantitative imaging parameter for detection and quantification of hepatic and splenic infiltration in children with Gaucher disease and correlated with clinical scoring, hematologic parameters, and enzyme assay of the disease.

Diffusion Tensor Imaging of the Lateral Rectus Muscle in Duane Retraction Syndrome.

AIM: This study aimed to assess metrics of diffusion tensor imaging in evaluating microstructural abnormalities of the lateral rectus muscle in Duane retraction syndrome (DRS). PATIENT AND METHODS: A prospective study was conducted on 27 patients with DRS and 16 age- and sex-matched controls who underwent diffusion tensor imaging of orbit and forced duction test (FDT). Fractional anisotropy (FA) and mean diffusivity (MD) of the lateral rectus were calculated by 2 observers. RESULTS: Fractional anisotropy of the lateral rectus in patients (0.62 ± 0.07 and 0.59 ± 0.06) was significantly higher (P = 0.001) than that in controls (0.49 ± 0.06 and 0.51 ± 0.06). Selection values of 0.53 and 0.52 as cutoff points of FA of the lateral rectus to differentiate patients from controls revealed areas under the curve of 0.92 and 0.86 and accuracy values of 84.8% and 80.4% by both observers, respectively. Mean diffusivity of the lateral rectus by both observers in patients (1.19 ± 0.13 and 1.23 ± 0.19 × 10 mm/s) was significantly lower (P = 0.001) than that in controls (1.54 ± 0.18 and 1.49 ± 0.16 × 10 mm/s). Selection values of 1.35 and 1.40 × 10 mm/s as cutoff points of MD of the lateral rectus to differentiate patients from the control groups revealed areas under the curve of 0.93 and 0.85 and accuracy values of 91.3% and 80.4% by both observers, respectively. Interobserver agreement for MD and FA of the lateral rectus by both observers were excellent (r = 0.870 and, 0.959). Diffusion tensor imaging metrics of the lateral rectus muscle did not differ significantly between patients with unilateral and bilateral disease (P = 0.05) and patients with DRS type I and type III (P = 0.05). Diffusion tensor imaging metrics of the lateral rectus muscle differed significantly between FDT grades I and II versus grades III and IV, and these metrics were well correlated with the degree of FDT. CONCLUSION: Diffusion tensor imaging metrics are valuable noninvasive tools in evaluating the microstructural abnormalities of the lateral rectus in DRS and are well correlated with degree of FDT.

Clinical Applications of Arterial Spin Labeling in Brain Tumors.

The aim of this review was to review the basic background, technique, and clinical applications of arterial spin labeling in brain tumors. Arterial spin labeling is used for differentiation of brain tumors from nonneoplastic lesions such as infarction and infection. It has a role in the grading of gliomas and in the differentiation of gliomas from lymphomas and metastasis. It is used for detection of the best biopsy site and prediction of treatment response. Arterial spin labeling is used for the assessment of extra-axial tumors and pediatric tumors. Last, it has a role in the differentiation of tumor recurrence from postradiation changes and in monitoring patients after therapy.

Computed Tomography Angiography and Magnetic Resonance Angiography of Congenital Anomalies of Pulmonary Veins.

We aimed to review computed tomography and magnetic resonance angiography of congenital anomalies of pulmonary veins. Total anomalous pulmonary venous return shows all pulmonary veins drain abnormally in another site rather than left atrium. Imaging can detect anomalous veins either supracardiac, infracardiac, or mixed. Partial anomalous pulmonary venous return shows some pulmonary vein have abnormal drainage that well delineated with computed tomography angiography. Scimitar syndrome is a type of partial anomalous pulmonary venous return where the pulmonary veins of the right lung drain infracardiac and is associated with right lung hypoplasia and dextrocardia. Pseudoscimitar show anomalous vein that takes a tortuous course and drains into the left atrium producing a false-positive scimitar sign. Cor triatriatum shows septum divide left atrium with proximal chamber receives blood flow from the pulmonary veins. Levoatriocardinal vein is an anomalous connection between the left atrium and anomalous vein from systemic venous system that is embryo logically derived from the cardinal veins. Computed tomography angiography can detect pulmonary vein stenosis, atresia, hypoplasia, and varix. Imaging is important for intimal diagnosis and detects the anomalous vessels and its connection, presence of stenosis, and associated other congenital cardiac anomalies. Also, it is a great role in assessment of patients after surgery.

Assessment of Mass Effect Sign at High-Resolution Computed Tomography in Prediction of Cholesteatoma.

OBJECTIVE: The aim of this study was to assess the accuracy of mass effect sign in the diagnosis of cholesteatoma at high-resolution computed tomography (HRCT). METHODS: This prospective study included 32 ears in 24 patients with chronic otitis media who underwent HRCT of the temporal bone. Otoscopic and operative notes were recorded. Image analysis was done both qualitatively and quantitatively. In the qualitative analysis, mass effect was evaluated visually by comparing both ears together in 4 certain anatomical sites. Ossicular erosions, erosion of tegmen tympani, erosion of tympanic segment of facial nerve canal, and the presence of lobulated nondependent opacity were also evaluated. In the quantitative analysis, we calculated the difference between the distances of the described anatomical sites in both ears. RESULTS: Qualitative analysis of mass effect sign showed 97.1% accuracy in detecting cholesteatoma. Ossicular erosions showed 69.2% accuracy in the diagnosis of cholesteatoma. In the quantitative analysis, we found that the cutoff point of 0.45 mm in the difference of aditus measure between both ears showed 85.3% accuracy in differentiating cholesteatoma from otitis media. The cutoff point of 0.75 mm in the differences in supratubal measure showed 86.1% accuracy. The cutoff point of 0.45 mm in the medial to incus measure showed 100% accuracy. CONCLUSION: High-resolution computed tomography is highly valuable for the detection of mass effect sign, which has great importance in diagnosing cholesteatoma.

Arterial spin labeling perfusion-weighted MR imaging: correlation of tumor blood flow with pathological degree of tumor differentiation, clinical stage and nodal metastasis of head and neck squamous cell carcinoma.

PURPOSE: The prognostic parameters of head and neck squamous cell carcinoma (HNSCC) include the pathological degree of tumor differentiation, clinical staging, and presence of metastatic cervical lymph nodes. To correlate tumor blood flow (TBF) acquired from arterial spin labeling (ASL) perfusion-weighted MR imaging with pathological degree of tumor differentiation, clinical stage, and nodal metastasis of HNSCC. MATERIALS AND METHODS: Retrospective analysis of 43 patients (31 male, 12 female with a mean age of 65 years) with HNSCC that underwent ASL of head and neck and TBF of HNSCC was calculated. Tumor staging and metastatic lymph nodes were determined. The stages of HNSCC were stage 1 (n = 7), stage II (n = 12), stage III (n = 11) and stage IV (n = 13). Metastatic cervical lymph nodes were seen in 24 patients. The degree of tumor differentiation was determined through pathological examination. RESULTS: The mean TBF of poorly and undifferentiated HNSCC (157.4 ± 6.7 mL/100 g/min) was significantly different (P = 0.001) than that of well-to-moderately differentiated (142.5 ± 5.7 mL/100 g/min) HNSCC. The cut-off TBF used to differentiate well-moderately differentiated from poorly and undifferentiated HNSCC was 152 mL/100 g/min with an area under the curve of 0.658 and accuracy of 88.4%. The mean TBF of stages I, II (146.10 ± 9.1 mL/100 g/min) was significantly different (P = 0.014) than that of stages III, IV (153.33 ± 9.3 mL/100 g/min) HNSCC. The cut-off TBF used to differentiate stages I, II from stages III and IV was 148 mL/100 g/min with an area under the curve of 0.701 and accuracy of 69.8%. The TBF was higher in patients with metastatic cervical lymph nodes. The cut-off TBF suspect metastatic node was 147 mL/100 g/min with an area under the curve of 0.671 and accuracy of 67.4%. CONCLUSION: TBF is a non-invasive imaging parameter that well correlated with pathological degree of tumor differentiation, clinical stage of tumor and nodal metastasis of HNSCC.

Inter-observer agreement of the Coronary Artery Disease Reporting and Data System (CAD-RADSTM) in patients with stable chest pain.

PURPOSE: To assess inter-observer variability of the Coronary Artery Disease - Reporting and Data System (CAD-RADS) for classifying the degree of coronary artery stenosis in patients with stable chest pain. MATERIAL AND METHODS: A prospective study was conducted upon 96 patients with coronary artery disease, who underwent coronary computed tomography angiography (CTA). The images were classified using the CAD-RAD system according to the degree of stenosis, the presence of a modifier: graft (G), stent (S), vulnerable plaque (V), or non-diagnostic (n) and the associated coronary anomalies, and non-coronary cardiac and extra-cardiac findings. Image analysis was performed by two reviewers. Inter-observer agreement was assessed. RESULTS: There was excellent inter-observer agreement for CAD-RADS (k = 0.862), at 88.5%. There was excellent agreement for CAD-RADS 0 (k = 1.0), CAD-RADS 1 (k = 0.92), CAD-RADS 3 (k = 0.808), CAD-RADS 4 (k = 0.826), and CAD-RADS 5 (k = 0.833) and good agreement for CAD-RADS 2 (k = 0.76). There was excellent agreement for modifier G (k = 1.0) and modifier S (k = 1.0), good agreement for modifier N (k = 0.79), and moderate agreement for modifier V (k = 0.59). There was excellent agreement for associated coronary artery anomalies (k = 0.845), non-coronary cardiac findings (k = 0.857), and extra-cardiac findings (k = 0.81). CONCLUSIONS: There is inter-observer agreement of CAD-RADS in categorising the degree of coronary arteries stenosis, and the modifier of the system and associated cardiac and extra-cardiac findings.