MR imaging findings of massive perivillous fibrin deposition of the placenta: A case report

Massive perivillous fibrin deposition (MPFD) of the placenta is characterized by the obliteration of the villous trophoblast with extensive deposition of fibrinoid material in the intervillous space. Here, we describe the MRI findings of a case of MPFD. The placenta demonstrates linear and geographical hypointensity on T2-weighted imaging, which is suggested to mainly reflect fibrin deposition. This finding should be noted, particularly in patients with miscarriage in their past history.

MR imaging findings of primary ovarian carcinoid: A novel finding of T1 hyperintense solid tissue

Ovarian carcinoid is a rare well-differentiated neuroendocrine tumor resembling those arising in the gastrointestinal tract. We present a case of ovarian carcinoid with magnetic resonance imaging (MRI) findings. A 50-year-old woman with genital bleeding and severe constipation was referred to our hospital. On MR imaging, a left ovarian tumor showed iso to high signal intensity on T1-weighted images (T1WI), relatively low signal intensity on T2WI, and slightly high signal intensity on diffusion-weighted images. Additionally, the tumor demonstrated early and delayed strong contrast enhancement on dynamic contrast-enhanced images. The tumor was pathologically diagnosed with ovarian strumal carcinoid. High signal intensity on T1WI should be recognized as the MRI findings in ovarian carcinoids.

Clinical Utility of Diffusion-Weighted Imaging in Gynecological Imaging: Revisited

ABSTRACT

Diffusion-weighted imaging (DWI) is an increasingly valuable sequence in daily clinical practice, providing both functional and morphological information. The use of DWI can help quantify diffusion using the apparent diffusion coefficient, which reflects the physiological features of the tissue and tumor microcirculation. This knowledge is crucial for understanding and interpreting gynecological imaging. This article reviews the clinical utility of DWI for gynecological imaging, highlighting its ability to aid in the detection of endometrial and cervical cancers, as well as tumor extension and metastasis. In addition, DWI can easily detect the solid components of ovarian cancer (including dissemination), assist in the diagnosis of adnexal torsion, and potentially show bone marrow status. Apparent diffusion coefficient measurement is useful for differentiating between endometrial lesions, uterine leiomyomas, and sarcomas, and may provide important information for predicting the prognosis of gynecological cancers.

Magnetic resonance imaging findings of endosalpingiosis: a case report

Endosalpingiosis is characterized by the presence of glands lined by benign tubal-type epithelium outside the fallopian tube. It is usually an incidental finding and rarely occurs as a tumor-like mass lesion. Here, we describe the magnetic resonance imaging findings of endosalpingiosis that presented as a paraovarian multicystic lesion. It exhibited iso to low intensity on T1-weighted images and inhomogeneous high intensity on T2-weighted images. The septa presented relatively iso to slight high intensity on T2-weighted images and strong contrast enhancement on dynamic contrast-enhanced imaging. Endosalpingiosis should be considered as a differential diagnosis in cases of paraovarian multicystic lesions along the uterine serosa.

CT and MR imaging findings of bilateral ovarian metastasis from renal cell carcinoma: a case report

Secondary ovarian involvement by renal cell carcinoma rarely occurs. Here, we describe the computed tomography and magnetic resonance imaging findings of bilateral ovarian metastases from renal cell carcinoma that demonstrated heterogeneous strong contrast enhancing tumors with flow voids around and within the tumors. In addition, the apparent diffusion coefficients of the malignant tumors were high. These findings were similar to those of renal cell carcinomas at primary and other metastatic sites.

Adaptive statistical iterative reconstruction for computed tomography of the spine

INTRODUCTION

The utility of evaluating a sagittal view of CT of the spine is well-known. In many clinical cases, the sagittal view includes noise generated from surrounding objects and may degrade the image quality. Iterative reconstruction (IR) techniques are useful for noise reduction; however, they can reduce spatial resolution. The aim of this study was to evaluate the effectiveness of the adaptive statistical iterative reconstruction (ASiR) for generating sagittal CT images of the spine when compared to filtered back projection (FBP).

METHODS

The image quality of clinical images from 25 patients were subjectively assessed. Three radiologists rated spatial resolution, image noise, and overall image quality using a five-point scale. For objective assessment, z-direction modulation transfer function (z-MTF) was measured using a custom-made phantom. Additionally, z-axis noise power spectrum (z-NPS) was measured using a water phantom. An improved adaptive statistical iterative reconstruction algorithm called ASiR-V was used in this study. Blending levels were 50%, and 100% (ASiR-V50, ASiR-V100, respectively).

RESULTS

For subjective assessments, images using ASiR-V100 were determined to have the best overall image quality, despite having received the worst score in the assessment of spatial resolution. For objective assessments, the image using ASiR-V50 and ASiR-V100 curves were slightly degraded in terms of low contrast z-MTF when compared to FBP.

CONCLUSION

ASiR-V was effective to improve the image quality when compared with FBP when reviewing sagittal reformats of the spine.

IMPLICATIONS FOR PRACTICE

This study suggests that high resolution is not the only thing that is key when reviewing sagittal CT spinal reformats. Such images should be provided as part of routine CT spine protocols, where available.

Investigation of myocardial extracellular volume fraction in heart failure patients using iodine map with rapid-kV switching dual-energy CT: Segmental comparison with MRI T1 mapping

PURPOSE

To measure myocardial extracellular volume fraction (ECV) for each region or segment using iodine density image (IDI) with single-source dual-energy computed tomography (DECT) and compare the results with an MRI T1 mapping approach.

MATERIALS AND METHODS

For this prospective study, 79 consecutive heart failure patients referred for MRI were included and 23 patients (14 men, 63 ± 14 years) who underwent both MRI and late contrast enhancement DECT following coronary CT angiography were evaluated. CT-ECV was computed from IDI using late acquisition projection data. MR-ECV was computed from native and post-contrast T1 maps using non-rigid image registration for segments with evaluable image quality from 3.0-T MRI. Regional CT-ECV and MR-ECV were measured based on 16-segment models. CT-ECV and MR-ECV were compared using Pearson correlations. Agreement among methods was assessed using Bland-Altman comparisons.

RESULTS

In the 368 segments, although all segments were evaluable on IDI, 37 segments were rated as non-evaluable on T1 maps. Overall, 331 segments were analyzed. Mean CT-ECV and MR-ECV were 31.6 ± 9.1 and 33.2 ± 9.1, respectively. Strong correlations were seen between CT-ECV and MR-ECV for each region, as follows: all segments, r = 0.837; septal, r = 0.871; mid-septal, r = 0.895; anterior, r = 0.869; inferior, r = 0.793; and lateral, 0.864 (all p < 0.001). Differences between CT-ECV and MR-ECV were as follows: all segments, 1.13 ± 4.98; septal, -1.51 ± 4.37; mid-septal, -1.85 ± 4.22; anterior, 2.54 ± 4.89; inferior, 1.2 ± 5.78; and lateral, 2.65 ± 3.98.

CONCLUSION

ECV using DECT and from cardiac MRI showed a strong correlation on regional and segmental evaluations. DECT is useful for characterizing myocardial ECV changes as well as MRI.

Detection and Classification of Myocardial Delayed Enhancement Patterns on MR Images with Deep Neural Networks: A Feasibility Study

PURPOSE

To evaluate whether deep neural networks trained on a similar number of images to that required during physician training in the American College of Cardiology Core Cardiovascular Training Statement can acquire the capability to detect and classify myocardial delayed enhancement (MDE) patterns.

MATERIALS AND METHODS

The authors retrospectively evaluated 1995 MDE images for training and validation of a deep neural network. Images were from 200 consecutive patients who underwent cardiovascular MRI and were obtained from the institutional database. Experienced cardiac MR image readers classified the images as showing the following MDE patterns: no pattern, epicardial enhancement, subendocardial enhancement, midwall enhancement, focal enhancement, transmural enhancement, and nondiagnostic. Data were divided into training and validation datasets by using a fourfold cross-validation method. Three untrained deep neural network architectures using the convolutional neural network (CNN) technique were trained with the training dataset images. The detection and classification accuracies of the trained CNNs were calculated with validation data.

RESULTS

The 1995 MDE images were classified by human readers as follows: no pattern, 926; epicardial enhancement, 91; subendocardial enhancement, 458; midwall enhancement, 118; focal enhancement, 141; transmural enhancement, 190; and nondiagnostic, 71. GoogLeNet, AlexNet, and ResNet-152 CNNs demonstrated accuracies of 79.5% (1592 of 1995 images), 78.9% (1574 of 1995 images), and 82.1% (1637 of 1995 images), respectively.

CONCLUSION

Deep learning with CNNs using a limited amount of training data, less than that required during physician training, achieved high diagnostic performance in the detection of MDE on MR images.© RSNA, 2019Supplemental material is available for this article.

Usefulness of Preoperative 18F-FDG PET/CT for Patients with Thymic Epithelial Tumors

Background

The purpose of this study was to investigate the relationship between preoperative FDG-PET parameters and the World Health Organization (WHO) classification or Masaoka staging system of thymic epithelial tumors.

Methods

We retrospectively reviewed 32 patients with histologically proven thymic epithelial tumors who underwent FDG-PET/CT before surgical resection. FDG-PET parameters, including the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolytic activity (TLG), were measured. These PET parameters were compared in the Masaoka staging system and WHO classification. A receiver operating characteristics (ROC) analysis was performed to identify the cut-off values of PET parameters for the accurate differentiation of early and advanced stages in the Masaoka staging system.

Results

There were 17 low-risk thymomas (1 type A, 9 type AB, and 7 type B1), 8 high-risk thymomas (4 type B2 and 4 type B3), and 7 thymic carcinomas (7 squamous cell carcinoma). Their Masaoka stages were as follows: 24 in the early stage (stages I and II) and 8 in the advanced stage (stage III). Regarding the WHO classification, only SUVmax showed a significant difference (P < 0.05). In the Masaoka stage, all PET parameters were significantly higher in the advanced stage than in the early stage (P < 0.05). In the ROC analysis to predict the early and advanced stages in thymic epithelial tumors, the area under the curve was the highest for TLG among the PET parameters examined and the cut-off value of TLG for discriminating the early from advanced stage with maximal sensitivity and specificity was 30.735.

Conclusion

Although volumetric PET parameters, such as MTV and TLG, did not correlate with the WHO classification, a significant correlation was observed between SUVmax and the WHO classification. In the Masaoka staging system, volumetric PET parameters may achieve more precise staging than SUVmax.

Myocardial Delayed Enhancement CT for the Evaluation of Heart Failure: Comparison to MRI

Purpose To assess the diagnostic performance of dual-energy CT with myocardial delayed enhancement (MDE) in the detection and classification of myocardial scar in patients with heart failure, with late gadolinium enhancement (LGE) MRI as the standard of reference. Materials and Methods MDE CT and LGE MRI were performed in 44 patients with heart failure (30 men; mean patient age, 66 years ± 14) between 2013 and 2016, and images were retrospectively analyzed. The presence and patterns of MDE on iodine-density and virtual monochromatic (VM) images were assessed by two independent readers. Contrast-to-noise ratio (CNR) and percentage signal intensity increase relative to normal myocardium were measured. Diagnostic performance and area under the receiver operating characteristic curve for MDE CT and kappa values for reader agreement were determined. Results Thirty-five of the 44 patients (80%) demonstrated a focal area of LGE, with a nonischemic pattern in 22 of the 44 patients (50%) and an ischemic pattern in 13 (30%). Iodine-density images demonstrated the highest CNR and percentage signal intensity increase on CT images (P < .05), resulting in the highest diagnostic performance in the detection of any MDE CT abnormality (92% sensitivity [195 of 213 segments] and 98% specificity [481 of 491 segments]). The areas under the receiver operating characteristic curve for iodine-density images and 40-keV VM images in the detection of MDE were 0.97 and 0.95, respectively (P < .001). Kappa values for reader agreement were 0.82 for iodine-density images and 0.72 for 40-keV VM images. Conclusion Myocardial delayed enhancement CT enables accurate detection and localization of scar in patients with heart failure when compared with late gadolinium enhancement MRI, the reference standard.