[F]FB(ePEG12)12-exendin-4 noninvasive imaging of insulinoma negative for insulin immunostaining on specimen from endoscopic ultrasonography-guided fine needle aspiration: a case report with review of literature.

Insulinomas are the most common functional pancreatic neuroendocrine neoplasm; when treatment is delayed, they induce hyperinsulinemic hypoglycemia, which is life-threatening. As surgical resection is the only curative treatment for insulinoma, preoperative localization is crucial; however, localization based on conventional imaging modalities such as computed tomography (CT) and magnetic resonance imaging is often inconclusive. Somatostatin receptor-targeted imaging is another option for detecting pancreatic neuroendocrine neoplasms but has low sensitivity and is not specific for insulinoma.

Thin-slice 2D MR Imaging of the Shoulder Joint Using Denoising Deep Learning Reconstruction Provides Higher Image Quality Than 3D MR Imaging.

Purpose: This study was conducted to evaluate whether thin-slice 2D fat-saturated proton density-weighted images of the shoulder joint in three imaging planes combined with parallel imaging, partial Fourier technique, and denoising approach with deep learning-based reconstruction (dDLR) are more useful than 3D fat-saturated proton density multi-planar voxel images.

Methods: Eighteen patients who underwent MRI of the shoulder joint at 3T were enrolled. The denoising effect of dDLR in 2D was evaluated using coefficient of variation (CV).

Thin-slice reverse encoding distortion correction DWI facilitates visualization of non-functioning pituitary neuroendocrine tumor (PitNET)/pituitary adenoma and surrounding normal structures.

Background: To evaluate the clinical usefulness of thin-slice echo-planar imaging (EPI)-based diffusion-weighted imaging (DWI) with an on-console distortion correction technique, termed reverse encoding distortion correction DWI (RDC-DWI), in patients with non-functioning pituitary neuroendocrine tumor (PitNET)/pituitary adenoma.

Methods: Patients with non-functioning PitNET/pituitary adenoma who underwent 3-T RDC-DWI between December 2021 and September 2022 were retrospectively enrolled. Image quality was compared among RDC-DWI, DWI with correction for distortion induced by B inhomogeneity alone (B-corrected-DWI), and original EPI-based DWI with anterior-posterior phase-encoding direction (AP-DWI).

Multiparametric Approach to Breast Cancer With Emphasis on Magnetic Resonance Imaging in the Era of Personalized Breast Cancer Treatment.

A multiparametric approach to breast cancer imaging offers the advantage of integrating the diverse contributions of various parameters. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the most important MRI sequence for breast imaging. The vascularity and permeability of lesions can be estimated through the use of semiquantitative and quantitative parameters.

Evaluating Reproducibility of the ADC and Distortion in Diffusion-weighted Imaging (DWI) with Reverse Encoding Distortion Correction (RDC).

Purpose: To compare image distortion and reproducibility of quantitative values between reverse encoding distortion correction (RDC) diffusion-weighted imaging (DWI) and conventional DWI techniques in a phantom study and in healthy volunteers.

Methods: This prospective study was conducted with the approval of our institutional review board. Written informed consent was obtained from each participant.

F-labeled PEGylated exendin-4 imaging noninvasively differentiates insulinoma from an accessory spleen: the first case report of [18F]FB(ePEG12)12-exendin-4 positron emission tomography/computed tomography for insulinoma.

Background: Insulinomas are the most common functioning pancreatic neuroendocrine neoplasms, and these tumors induce hypoglycemia due to hyperinsulinemia. Hypoglycemia caused by insulinomas can cause seizures, coma or death due to the delayed diagnosis. The only curative treatment is surgical resection.

Prognostic value of pretreatment FDG PET/CT in uterine cervical cancer according to two major histologic types: squamous cell carcinoma and adenocarcinoma.

Objectives: The aim of this study was to assess the prognostic value of pretreatment Positron emission tomography / computed tomography using F-fluorodeoxyglucose (FDG-PET/CT) in cervical cancer according to two major histologic types.

Methods: Eighty-three squamous cell carcinoma (SCC) patients and 35 adenocarcinoma (AC) patients who underwent pretreatment FDG-PET/CT were retrospectively analyzed. Maximum standardized uptake value (SUV), mean standardized uptake value (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumor were calculated.

Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance.

Purpose: Neuromelanin-sensitive MRI (NM-MRI) has proven useful for diagnosing Parkinson's disease (PD) by showing reduced signals in the substantia nigra (SN) and locus coeruleus (LC), but requires a long scan time. The aim of this study was to assess the image quality and diagnostic performance of NM-MRI with a shortened scan time using a denoising approach with deep learning-based reconstruction (dDLR).

Materials And Methods: We enrolled 22 healthy volunteers, 22 non-PD patients and 22 patients with PD who underwent NM-MRI, and performed manual ROI-based analysis.

Evaluation of breast lesions based on modified BI-RADS using high-resolution readout-segmented diffusion-weighted echo-planar imaging and T2/T1-weighted image.

Purpose: To evaluate the diagnostic performance of a non-contrast magnetic resonance imaging (MRI) protocol combining high-resolution diffusion-weighted images (HR-DWI) using readout-segmented echo planar imaging, T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI), using our modified Breast Imaging-Reporting and Data System (modified BI-RADS).

Methods: Two experienced radiologists, blinded to the final pathological diagnosis, categorized a total of 108 breast lesions (61 malignant and 47 benign) acquired with the above protocol using the modified BI-RADS with a diagnostic decision tree. The decision tree included subcategories of category 4, as in mammography (categories 2, 3, 4A, 4B, 4C, and 5).

Multiparametric imaging of breast cancer: An update of current applications.

Imaging plays an indispensable role in the diagnosis and treatment of breast cancer. Several new imaging tools are currently being developed for clinical use to improve diagnostic performance and tumor response evaluation. Abbreviated magnetic resonance imaging (MRI) allows shortening scanning time without penalizing diagnostic performances.

Super-resolution application of generative adversarial network on brain time-of-flight MR angiography: image quality and diagnostic utility evaluation.

Objectives: To develop a generative adversarial network (GAN) model to improve image resolution of brain time-of-flight MR angiography (TOF-MRA) and to evaluate the image quality and diagnostic utility of the reconstructed images.

Methods: We included 180 patients who underwent 1-min low-resolution (LR) and 4-min high-resolution (routine) brain TOF-MRA scans. We used 50 patients' datasets for training, 12 for quantitative image quality evaluation, and the rest for diagnostic validation.

Visual Evaluation of Ultrafast MRI in the Assessment of Residual Breast Cancer after Neoadjuvant Systemic Therapy: A Preliminary Study Association with Subtype.

The purpose of this study was to investigate the diagnostic performance of ultrafast DCE (UF-DCE) MRI after the completion of neoadjuvant systemic therapy (NST) in breast cancer. In this study, MR examinations of 55 post-NST breast cancers were retrospectively analyzed. Residual tumor sizes were measured in the 20th phase of UF-DCE MRI, early and delayed phases of conventional DCE MRI, and high spatial-resolution CE MRI (UF, early, delayed, and HR, respectively).

Diagnostic advantage of thin slice 2D MRI and multiplanar reconstruction of the knee joint using deep learning based denoising approach.

The purpose of this study is to evaluate whether thin-slice high-resolution 2D fat-suppressed proton density-weighted image of the knee joint using denoising approach with deep learning-based reconstruction (dDLR) with MPR is more useful than 3D FS-PD multi planar voxel image. Twelve patients who underwent MRI of the knee at 3T and 13 knees were enrolled. Denoising effect was quantitatively evaluated by comparing the coefficient of variation (CV) before and after dDLR.

Evaluation of pathological complete response after neoadjuvant systemic treatment of invasive breast cancer using diffusion-weighted imaging compared with dynamic contrast-enhanced based kinetic analysis.

Purpose: This study compared the performance of diffusion-weighted imaging (DWI) to dynamic contrast-enhanced (DCE)-MRI for diagnosing pathological complete response (pCR) before surgery.

Method: Overall, 133 lesions from 133 patients who underwent pre-surgical MRI evaluation after neoadjuvant systemic treatment were included. Two readers blinded to the pathological diagnosis evaluated the images.

Application of a Flexible PET Scanner Combined with 3 T MRI Using Non-local Means Reconstruction: Qualitative and Quantitative Comparison with Whole-Body PET/CT.

Purpose: Flexible positron emission tomography (fxPET) employing a non-local means reconstruction algorithm was designed to fit existing magnetic resonance imaging (MRI) systems. We aimed to compare the qualitative and quantitative performance of fxPET among fxPET with MR-based attenuation correction (MRAC), fxPET with CT-based attenuation correction (CTAC) using CT as a part of WB PET/CT, and whole-body (WB) PET/CT.

Procedures: Sixteen patients with suspected head and neck cancer underwent 2-deoxy-2-[F]fluoro-D-glucose WB PET/CT scans, followed by fxPET and 3 T MRI scans.

Deep Learning-based Noise Reduction for Fast Volume Diffusion Tensor Imaging: Assessing the Noise Reduction Effect and Reliability of Diffusion Metrics.

To assess the feasibility of a denoising approach with deep learning-based reconstruction (dDLR) for fast volume simultaneous multi-slice diffusion tensor imaging of the brain, noise reduction effects and the reliability of diffusion metrics were evaluated with 20 patients. Image noise was significantly decreased with dDLR. Although fractional anisotropy (FA) of deep gray matter was overestimated when the number of image acquisitions was one (NAQ1), FA in NAQ1 with dDLR became closer to that in NAQ5.

Subcategory classifications of Breast Imaging and Data System (BI-RADS) category 4 lesions on MRI.

Purpose: Category 4 in BI-RADS for magnetic resonance imaging (MRI) has a wide range of probabilities of malignancy, extending from > 2 to < 95%. We classified category 4 lesions into three subcategories and analyzed the positive predictive value (PPV) of malignancy in a tertiary hospital.

Materials And Methods: This retrospective study included 346 breast MRIs with 434 category 2-5 lesions.

Evaluation of Malignant Breast Lesions Using High-resolution Readout-segmented Diffusion-weighted Echo-planar Imaging: Comparison with Pathology.

Purpose: We aimed to investigate the performance of high resolution-diffusion-weighted imaging (HR-DWI) using readout-segmented echo-planar imaging in visualizing malignant breast lesions and evaluating their extent, using pathology as a reference.

Methods: This retrospective study included patients who underwent HR-DWI with surgically confirmed malignant breast lesions. Two radiologists blinded to the final diagnosis evaluated HR-DWI independently and identified the lesions, measuring their maximum diameters.

Background parenchymal enhancement and its effect on lesion detectability in ultrafast dynamic contrast-enhanced MRI.

Purpose: Background parenchymal enhancement (BPE) often affects interpretation of dynamic contrast-enhanced (DCE) MRI. There is limited evidence that reduced BPE is a feature of ultrafast DCE (UF-DCE) MRI. We aimed to evaluate the effect of BPE levels on lesion detectability on UF-DCE MRI in comparison with conventional DCE MRI.

The comparison of high-resolution diffusion weighted imaging (DWI) with high-resolution contrast-enhanced MRI in the evaluation of breast cancers.

Purpose: We sought to investigate the performance of high resolution (HR) diffusion-weighted imaging (DWI) using readout-segmented echo-planar imaging (rs-EPI), compared with high-resolution contrast-enhanced MRI (HR CE-MRI) in terms of morphological accuracy, on the basis of the Breast Imaging and Reporting and Data System (BI-RADS) MRI descriptors and lesion size.

Methods: This retrospective study included the image data of 94 patients with surgically confirmed malignant breast lesions who had undergone high resolution diffusion-weighted imaging (HR-DWI) and HR CE-MRI. Two radiologists blinded to the final diagnosis independently identified the lesions on HR-DWI, described the morphology of the lesions according to BI-RADS descriptors, and measured lesion size.

[Report in 2017 April ～ 2018 March].

Women physicians, scientists and nurses are addressing many problems encountered in the practice of their chosen fields. We carried out a survey of the women working in the nuclear medicine field. Two hundred and six professionals answered this questionnaire.

Optimal Cutoff Value of Fractional Flow Reserve Derived From Coronary Computed Tomography Angiography for Predicting Hemodynamically Significant Coronary Artery Disease.

Background: The optimal cutoff value of fractional flow reserve (FFR) derived from coronary computed tomography angiography (FFR) remains unclear.

Methods: The current study population consisted of 93 patients with 139 vessels, who had suspected coronary artery disease by computed tomography angiography and underwent invasive FFR. We evaluated diagnostic performance of FFR according to different FFR cutoff values and FFR ranges with invasive FFR ≤0.