Performance of Machine Learning Methods Based on Multi-Sequence Textural Parameters Using Magnetic Resonance Imaging and Clinical Information to Differentiate Malignant and Benign Soft Tissue Tumors.

Rationale And Objectives: To evaluate the performance of a machine learning method to differentiate malignant from benign soft tissue tumors based on textural features on multiparametric magnetic resonance imaging (mpMRI).

Materials And Methods: We enrolled 163 patients with soft tissue tumors whose diagnosis was pathologically proven (71 malignant, 92 benign). All patients underwent mpMRI.

Hybrid deep-learning-based denoising method for compressed sensing in pituitary MRI: comparison with the conventional wavelet-based denoising method.

Objectives: This study aimed to evaluate the efficacy of a combined wavelet and deep-learning reconstruction (DLR) method for under-sampled pituitary MRI.

Methods: This retrospective study included 28 consecutive patients who underwent under-sampled pituitary T2-weighted images (T2WI). Images were reconstructed using either the conventional wavelet denoising method (wavelet method) or the wavelet and DLR methods combined (hybrid DLR method) at five denoising levels.

Virtual Monochromatic Image Quality from Dual-Layer Dual-Energy Computed Tomography for Detecting Brain Tumors.

Objective: To evaluate the usefulness of virtual monochromatic images (VMIs) obtained using dual-layer dual-energy CT (DL-DECT) for evaluating brain tumors.

Materials And Methods: This retrospective study included 32 patients with brain tumors who had undergone non-contrast head CT using DL-DECT. Among them, 15 had glioblastoma (GBM), 7 had malignant lymphoma, 5 had high-grade glioma other than GBM, 3 had low-grade glioma, and 2 had metastatic tumors.

Non-contrast renal MRA using multi-shot gradient echo EPI at 3-T MRI.

Objectives: The purpose of this study was to investigate the feasibility of non-contrast renal MRA using multi-shot gradient echo planar imaging (MSG-EPI) with a 3-T MRI system.

Methods: Seventeen healthy volunteers underwent non-contrast renal MRA using MSG-EPI and balanced steady-state free precession (b-SSFP) sequences on a 3-T MRI system. Two radiologists independently recorded the images' contrast, noise, sharpness, artifacts, and overall quality on 4-point scales.

A primer for understanding radiology articles about machine learning and deep learning.

The application of machine learning and deep learning in the field of imaging is rapidly growing. Although the principles of machine and deep learning are unfamiliar to the majority of clinicians, the basics are not so complicated. One of the major issues is that commentaries written by experts are difficult to understand, and are not primarily written for clinicians.

Diagnostic Performance of I-FPCIT SPECT Specific Binding Ratio in Progressive Supranuclear Palsy: Use of Core Clinical Features and MRI for Comparison.

Progressive supranuclear palsy (PSP) is listed as a core clinical feature in the Movement Disorder Society 2017 criteria, along with ocular motor dysfunction, postural instability, akinesia, and cognitive dysfunction. Imaging evidence shows predominant mid-brain atrophy and postsynaptic striatal dopaminergic degeneration as two supportive features. The purpose of this study was to investigate the diagnostic performance of I- ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl) nortropane (I-FP-CIT) SPECT by comparing it with evaluation of core clinical features and MRI in the diagnosis of PSP.

A preliminary study of deep learning-based reconstruction specialized for denoising in high-frequency domain: usefulness in high-resolution three-dimensional magnetic resonance cisternography of the cerebellopontine angle.

Purpose: Deep learning-based reconstruction (DLR) has been developed to reduce image noise and increase the signal-to-noise ratio (SNR). We aimed to evaluate the efficacy of DLR for high spatial resolution (HR)-MR cisternography.

Methods: This retrospective study included 35 patients who underwent HR-MR cisternography.

Adrenal Adenomas versus Metastases: Diagnostic Performance of Dual-Energy Spectral CT Virtual Noncontrast Imaging and Iodine Maps.

Background Dual-energy CT allows virtual noncontrast (VNC) attenuation and iodine density measurements from contrast material-enhanced examination, potentially enabling adrenal lesion characterization. However, data regarding diagnostic performance remain limited, and combined diagnostic values have never been investigated. Purpose To determine whether VNC attenuation, iodine density, and combination of the two allow reliable differentiation between adrenal adenomas and metastases.

Trends in Diagnostic Imaging of Cardiac Amyloidosis: Emerging Knowledge and Concepts.

Cardiac amyloidosis (CA) has long been recognized as a rare disease. However, recent advances in cardiac imaging have led to increased identification of hidden CA in patients diagnosed with heart failure. This shift suggests that the actual incidence of CA is underestimated.

A diagnostic strategy for Lewy body disease using DAT-SPECT, MIBG and Combined index.

Purpose: The functional imaging methods widely used for the diagnosis of Lewy body disease (LBD) are I-N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl) nortropan (FP-CIT) with dopamine transporter single photon emission computed tomography (DAT-SPECT) and I-iodobenzylguanidine (MIBG) myocardial scintigraphy. The aim of this study was to determine whether DAT-SPECT or I-MIBG myocardial scintigraphy should be examined first and to evaluate whether the combined use of DAT-SPECT and MIBG myocardial scintigraphy is superior to using either modality alone for diagnosing suspected LBD.

Methods: In this retrospective study, a total of 117 patients suspected of having LBD underwent DAT-SPECT imaging followed by MIBG myocardial scintigraphy.

Diagnostic Performance of Dual-Layer Computed Tomography for Deep Vein Thrombosis in Indirect Computed Tomography Venography.

Background: The aim of this study was to evaluate the quality and diagnostic performance of virtual monochromatic images (VMI) obtained with dual-layer dual-energy computed tomography (DL-DECT) during indirect CT venography (CTV) for deep vein thrombosis (DVT).

Methods and results: This retrospective study was approved by the Institutional Review Board, which waived the requirement for informed consent. We retrospectively enrolled 45 patients who underwent CTV with DL-DECT, and VMI were retrospectively generated.

Impact of hydrostatic pressure on fractional flow reserve: in vivo experimental study of anatomical height difference of coronary arteries.

Background: Although pressure equalization of the sensor-tipped guidewire and systemic pressure is mandatory in measuring fractional flow reserve (FFR), pressure in the distal artery (Pd) with wire advancement can be influenced by hydrostatic pressure related to the height difference between the catheter tip and the distal pressure sensor. We therefore analyzed the impact of hydrostatic pressure on FFR in vivo by modification of the height difference.

Methods: To reveal the anatomical height difference in human coronary arteries, measurement was performed during computed tomography angiography (CTA) of five consecutive patients.

Effects of Deep Learning Reconstruction Technique in High-Resolution Non-contrast Magnetic Resonance Coronary Angiography at a 3-Tesla Machine.

Purpose: To evaluate the effects of deep learning reconstruction (DLR) in qualitative and quantitative image quality of non-contrast magnetic resonance coronary angiography (MRCA).

Methods: Ten healthy volunteers underwent conventional MRCA (C-MRCA) and high-resolution (HR) MRCA on a 3T magnetic resonance imaging with a voxel size of 1.8 × 1.

Usefulness of Virtual Monochromatic Dual-Layer Computed Tomographic Imaging for Breast Carcinoma.

Objective: This study aimed to evaluate virtual monochromatic images (VMIs) obtained using dual-layer dual-energy computed tomography (CT) for breast carcinoma.

Methods: We retrospectively enrolled 28 patients with breast cancer who were pathologically diagnosed using dual-layer dual-energy CT. Virtual monochromatic images (40-200 keV) were generated.

Machine Learning to Predict the Rapid Growth of Small Abdominal Aortic Aneurysm.

Objective: The purpose of this study was to determine whether computed tomography (CT) angiography with machine learning (ML) can be used to predict the rapid growth of abdominal aortic aneurysm (AAA).

Materials And Methods: This retrospective study was approved by our institutional review board. Fifty consecutive patients (45 men, 5 women, 73.

An initial experience of machine learning based on multi-sequence texture parameters in magnetic resonance imaging to differentiate glioblastoma from brain metastases.

Purpose: To evaluate the performance of a machine learning method based on texture parameters in conventional magnetic resonance imaging (MRI) in differentiating glioblastoma (GB) from brain metastases (METs).

Materials And Methods: In this retrospective study conducted between November 2008 and July 2017, we included 73 patients diagnosed with GB (n = 73) and METs (n = 53) who underwent contrast-enhanced 3 T brain MRI. Twelve histogram and texture parameters were assessed on T2-weighted images (T2WIs), apparent diffusion coefficient maps (ADCs), and contrast-enhanced T1-weighted images (CE-T1WIs).

Prevalence of extracardiac findings in patients undergoing coronary computed tomography and additional low-dose whole-body computed tomography.

Purpose: In patients with suspected coronary artery disease (CAD), coexisting extracardiac abnormalities have a major impact on the patient management. This study aimed to evaluate the image quality of whole-body computed tomography (CT) immediately after the coronary computed tomography angiography (CTA) and investigate the incidence of extracardiac findings in patients with suspected CAD.

Materials And Methods: We enrolled 450 patients undergoing whole-body CT at 100 kVp and model-based iterative reconstruction immediately after the coronary CTA (Group A) and retrospectively reviewed 144 control patients who underwent conventional contrast-enhanced CT (120 kVp) with filtered back projection (Group B).

Contrast enhancement on 100- and 120 kVp hepatic CT scans at thin adults in a retrospective cohort study: Bayesian inference of the optimal enhancement probability.

Purpose: To assess the probability of achieving optimal contrast enhancement in 100 kVp and 120 kVp-protocol on hepatic computed tomography (CT) scans.

Materials And Methods: We enrolled 200 patients in a retrospective cohort study. Hundred patients were scanned with 120 kVp setting, and other 100 patients were scanned with 100 kVp setting.

Clinical usefulness of quantification of myocardial blood flow and flow reserve using CZT-SPECT for detecting coronary artery disease in patients with normal stress perfusion imaging.

Background: Relative myocardial perfusion imaging can misdiagnose "balanced" ischemia caused by coronary artery disease (CAD). We assessed the feasibility of myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) using dynamic single-photon emission computed tomography (SPECT) with a cadmium-zinc-telluride (CZT) camera for estimating underlying CAD in patients with normal stress myocardial perfusion SPECT (MPS).

Methods: 125 patients with normal stress MPS (summed stress score ≤3) were enrolled.

Perfusion abnormality on three-dimensional arterial spin labeling in patients with acute encephalopathy with biphasic seizures and late reduced diffusion.

Purpose: Acute encephalopathy with biphasic seizures and late reduced diffusion (AESD) is the most common encephalopathy subtype in Japanese children. Few case reports have shown perfusion abnormality on arterial spin labeling (ASL) in patients with AESD. The present study aimed to review the chronological change of cerebral perfusion on three-dimensional (3D) ASL in patients with AESD.

Combining quantitative susceptibility mapping to the morphometric index in differentiating between progressive supranuclear palsy and Parkinson's disease.

Purpose: To determine whether the susceptibility value in the deep gray matter obtained by quantitative susceptibility mapping (QSM) provides additive value to the morphometric index for differentiating progressive supranuclear palsy (PSP) from Parkinson's disease (PD).

Materials And Methods: PSP- (n = 8) and PD patients (n = 18) and 18 age-matched healthy controls who underwent QSM and 3D magnetization-prepared rapid gradient echo (MPRAGE) sequences. The mean susceptibility values (MSVs) of the deep gray matter structures on QSM- and areas of the midbrain (morphometric index, MI) on 3D MPRAGE images were measured by two neuroradiologists.

Tc-99m PMT scintigraphy in the diagnosis of pediatric biliary atresia.

Purpose: Hepatobiliary scintigraphy plays an important role in the differentiation of biliary atresia (BA) and non-BA. The usefulness of Tc-iminodiacetic acid (IDA) derivatives in BA diagnosis is reported in several papers. In contrast, there are no comprehensive data on differentiating BA from non-BA using Tc-N-pyridoxyl-5-methyl-tryptophan (PMT).

Prospective Comparison of 70-kVp Single-Energy CT versus Dual-Energy CT: Which is More Suitable for CT Angiography with Low Contrast Media Dosage?

Rationale And Objectives: To compare the objective and subjective image qualities between single-energy computed tomography (CT) at 70 kVp and virtual monoenergetic imaging (VMI) of dual-source dual-energy CT for CT angiography with 180 mgI/kg.

Materials And Methods: Total 63 patients scanned with 180 mgI/kg were randomly divided into two groups: Group A (32 patients) underwent CT angiography at 70-kVp, and Group B (31 patients) underwent dual-energy CT. VMI sets were generated at 10-keV increments between 40 and 100 keV.

Myocardial extracellular volume quantification in cardiac CT: comparison of the effects of two different iterative reconstruction algorithms with MRI as a reference standard.

Objectives: To compare the effects of hybrid iterative reconstruction (HIR) and model-based iterative reconstruction (MBIR) that incorporates a beam-hardening model for myocardial extracellular volume (ECV) quantification by cardiac CT using MRI as a reference standard.

Methods: In this retrospective study, a total of 34 patients were evaluated using cardiac CT and MRI. Paired CT image sets were created using HIR and MBIR with a beam-hardening model.