Japanese Journal of Radiology最新文献

Purpose: Screening tests are the cornerstone for early detection and optimal management of cancers. Most of the present cancer-screening tests are intrusive, time-consuming, and specifically target a particular anatomical site or cancer type. Only a few studies have reported the objective measures of ¹⁸F-FDG PET-based cancer screening in asymptomatic individuals. This review and meta-analysis is an attempt to assess the applicability and performance of ¹⁸F-FDG PET-based modalities for whole-body cancer screening.

Materials and methods: The systematic review and meta-analysis were performed following PRISMA guidelines. Literature searches in PubMed, Scopus, and Embase were conducted using relevant MeSH terms and keywords, for articles published in the last 2 decades (2000-2022). Pooled estimates of diagnostic test accuracy-including sensitivity, specificity, positive-likelihood ratio, negative-likelihood ratio, and hierarchical summary ROC (HSROC) curve were generated using bivariate random-effects meta-analysis.

Results: Seventeen studies were included in the systematic review and 13 studies were deemed eligible for meta-analysis. The mean estimates of pooled sensitivity, specificity, positive-likelihood ratio, negative-likelihood ratio, and Odds ratio using ¹⁸F-FDG PET with a 95% confidence interval were 0.47 (0.25-0.69), 0.97 (0.95-0.98), 18.8 (6.8-51.5), 0.45 (0.27-0.76), 41.0 (7.9-211.8) and for ¹⁸F-FDG PET/CT were 0.83 (0.75-0.88), 0.98 (0.97-0.99), 49.7 (29.2-84.5), 0.15 (0.8-0.28), 329.9 (125.0-870.8), respectively. Among screening modalities, ¹⁸F-FDG PET/CT had a higher accuracy i.e., the area under the HSROC curve (AUC): 0.91 (0.87-0.95) compared to ¹⁸F-FDG PET: 0.72 (0.61-0.82).

Conclusion: This study demonstrates that currently ¹⁸F-FDG PET-based screening has limited applicability for population-based cancer-screening programs. However, it has a promising role as a combined screening strategy for at-risk individuals and allows for comprehensive diagnostic and prognostic evaluation in high-resource settings.

Diffusion MRI was introduced in 1985, showing how the diffusive motion of molecules, especially water, could be spatially encoded with MRI to produce images revealing the underlying structure of biologic tissues at a microscopic scale. Diffusion is one of several Intravoxel Incoherent Motions (IVIM) accessible to MRI together with blood microcirculation. Diffusion imaging first revolutionized the management of acute cerebral ischemia by allowing diagnosis at an acute stage when therapies can still work, saving the outcomes of many patients. Since then, the field of diffusion imaging has expanded to the whole body, with broad applications in both clinical and research settings, providing insights into tissue integrity, structural and functional abnormalities from the hindered diffusive movement of water molecules in tissues. Diffusion imaging is particularly used to manage many neurologic disorders and in oncology for detecting and classifying cancer lesions, as well as monitoring treatment response at an early stage. The second major impact of diffusion imaging concerns the wiring of the brain (Diffusion Tensor Imaging, DTI), allowing to obtain from the anisotropic movement of water molecules in the brain white-matter images in 3 dimensions of the brain connections making up the Connectome. DTI has opened up new avenues of clinical diagnosis and research to investigate brain diseases, neurogenesis and aging, with a rapidly extending field of application in psychiatry, revealing how mental illnesses could be seen as Connectome spacetime disorders. Adding that water diffusion is closely associated to neuronal activity, as shown from diffusion fMRI, one may consider that diffusion MRI is ideally suited to investigate both brain structure and function. This article retraces the early days and milestones of diffusion MRI which spawned over 40 years, showing how diffusion MRI emerged and expanded in the research and clinical fields, up to become a pillar of modern clinical imaging.

Purpose

This study aimed to evaluate the MRI features of the main histological subtypes of thyroid cancer and enable differentiation between anaplastic thyroid carcinoma (ATC), poorly differentiated thyroid carcinoma (PDTC), and papillary thyroid carcinoma (PTC).

Materials and methods

This study included 79 patients with histopathologically proven thyroid cancer (14 ATCs, 8 PDTCs, and 57 PTCs) who underwent neck MRI. MRI images were retrospectively reviewed and compared between the three pathologies.

Results

The maximum diameter was larger in ATCs and PDTCs than in PTCs (65.2 mm and 38.4 mm vs. 26.0 mm, p < 0.01). The signal intensity ratio of the solid components on T2-weighted images (T2WIs) was higher in ATCs than in PTCs (1.13 vs. 0.89, p < 0.05). The predominant signal intensity of the solid components on T2WI exhibited hyperintensity relative to the spinal cord in ATCs more frequently than in PTCs (71% vs. 30%, p < 0.01), whereas hypointensity was more frequent in PTCs than in ATCs and PDTCs (60% vs. 0% and 13%, p < 0.01). Intratumoral ring-shaped hypointensity on T2WI was more frequent in ATCs than in PDTCs and PTCs (64% vs. 13% and 18%, p < 0.01). An ill-defined margin was more frequent in ATCs and PDTCs than in PTCs (93% and 63% vs. 25%, p < 0.01). Extrathyroidal extension, tracheal invasion, esophageal invasion, vascular invasion, and venous thrombosis were more frequently observed in ATCs than in PTCs (p < 0.05).

Conclusions

MRI could characterize the differences between ATCs, PDTCs, and PTCs.

Purpose

This study retrospectively evaluated the feasibility and safety of implanting a newly developed central venous access port (CV-port) that allows catheter insertion into a vein without the use of a peel-away sheath, with a focus on its potential to minimize risks associated with conventional implantation methods.

Materials and methods

All procedures were performed using a new device (P-U CelSite Port™ MS; Toray Medical, Tokyo, Japan) under ultrasound guidance. The primary endpoint was the implantation success rate. The secondary endpoints were the safety and risk factors for infection in the early postprocedural period (< 30 days).

Results

We assessed 523 CV-port implantations performed in a cumulative total of 523 patients (240 men and 283 women; mean age, 61.6 ± 13.1 years; range, 18–85 years). All implantations were successfully performed using an inner guide tube and over-the-wire technique through 522 internal jugular veins and one subclavian vein. The mean procedural time was 33.2 ± 10.9 min (range 15–112 min). Air embolism, rupture/perforation of the superior vena cava, or hemothorax did not occur during catheter insertion. Eleven (2.1%) intraprocedural complications occurred, including Grade I arrhythmia (n = 8) and subcutaneous bleeding (n = 1), Grade II arrhythmia (n = 1), and Grade IIIa pneumothorax (n = 1). Furthermore, 496 patients were followed up for ≥ 30 days. Six early postprocedural complications were encountered (1.1%), including Grade IIIa infection (n = 4), catheter occlusion (n = 1), and skin necrosis due to subcutaneous leakage of trabectedin (n = 1). These six CV-ports were withdrawn, and no significant risk factors for infection in the early postprocedural period were identified.

Conclusion

The implantation of this CV-port device demonstrated comparable success and complication rates to conventional devices, with the added potential benefit of eliminating complications associated with the use of a peel-away sheath.

The clinical imaging features of photon-counting detector (PCD) computed tomography (CT) are mainly known as dose reduction, improvement of spatial resolution, and reduction of artifacts compared to energy-integrating detector CT (EID-CT). The utility of cranial and spinal PCD-CT and PCD-CT angiography (CTA) has been previously reported. CTA is a widely used technique for noninvasive evaluation. Cranial CTA is important in brain tumors, especially glioblastoma; it evaluates whether the tumor is highly vascularized prior to an operation and helps in the diagnosis and assessment of bleeding risk. Spinal CTA has an important role in the estimation of feeders and drainers prior to selective angiography in the cases of spinal epidural arteriovenous fistulas and spinal tumors, especially in hemangioblastoma. So far, EID-CTA is commonly performed in an adjunctive role prior to selective angiography; PCD-CTA with high spatial resolution can be an alternative to selective angiography. In the cases of cerebral aneurysms, flow diverters are important tools for the treatment of intracranial aneurysms, and postoperative evaluation with cone beam CT with angiography using diluted contrast media is performed to evaluate stent adhesion and in-stent thrombosis. If CTA can replace selective angiography, it will be less invasive for the patient. In this review, we present representative cases with PCD-CT. We also show how well the cranial and spinal PCD-CTA approaches the accuracy of angiographic and intraoperative findings.

Introduction

The administration of intravenous (IV) contrast media during computed tomography (CT) examinations is essential to enhance diagnostic accuracy in various clinical scenarios. Traditionally, older age is considered a risk factor for the development of post-contrast Acute Kidney Injury (PC-AKI); however, there is limited information available for the super-elderly population (aged ≥ 85). This study aims to investigate the incidence and risk factors associated with PC-AKI in individuals aged 85 and older undergoing CT scans with IV contrast.

Methods

A retrospective cohort study, including all hospitalized patients aged 85 or older who underwent CT scans between the years 2005 and 2021. Patients were categorized into IV contrast and non-IV contrast groups. Baseline demographic and clinical data, along with kidney function parameters, were collected.

Results

The final cohort included 7,078 patients who underwent CT scans, with 40% receiving IV contrast. The overall AKI occurrence within 72 h post-CT was 5.72%, slightly elevated in the non-IV contrast group (6.25% vs. 4.94%, p = 0.02). However, multivariate analysis revealed no significant difference between the groups (OR 1, CI 0.8–1.2, p = 0.92), even after stratifying by kidney function. A secondary analysis, using a less strict AKI definition, supported these findings. Baseline creatinine levels emerged as prominent risk factor associated with PC- AKI.

Conclusion

The current study provides reassurance regarding the safety of contrast-enhanced CT scans in super-elderly patients, particularly those with baseline normal to mild kidney dysfunction. These findings may contribute to the ongoing discussion on the risk–benefit balance of contrast-enhanced CT scans in the super-elderly population.

Objective

To evaluate the usefulness of novel diffusion-weighted imaging (DWI) findings for diagnosing placenta accreta spectrum (PAS).

Materials and methods

This retrospective study included 49 pregnant women with suspected PAS who underwent 1.5 T placental MRI. Diffusion lacunae were defined as intraplacental areas showing hypointensity on DWI and hyperintensity on the apparent diffusion coefficient map. Two radiologists evaluated the number and size of placental lacunae on DWI, and flow void in the diffusion lacunae on T2-weighted imaging. The radiologists also evaluated established MRI features of PAS described in the SAR-ESUR consensus statement. Pearson's chi-square test or Mann–Whitney U test was used to compare findings between patients with and without PAS. Interobserver reliability for DWI and established MRI features was also assessed. Optimal thresholds for the number and maximum size of diffusion lacunae for differentiating PAS from the no-PAS group were determined using receiver operating characteristic curve analyses.

Results

Eighteen patients were diagnosed with PAS, and 31 patients with placental previa without PAS. The number and maximum size of diffusion lacunae were significantly larger in patients with than in patients without PAS (p < 0.0001). Combining assessment of the number of diffusion lacunae with assessment of their maximum size yielded a diagnostic performance with sensitivity, specificity and accuracy of 83%, 94% and 90%, respectively. Flow voids within the diffusion lacunae had sensitivity, specificity and accuracy of 88%, 84% and 86%, respectively.

Conclusion

The number and size of diffusion lacunae, and T2 flow void in diffusion lacunae may be useful findings for diagnosing PAS.

Holoprosencephaly (HPE) is a complex forebrain congenital malformation with widely variable outcomes. It represents a disorder of ventral induction, which begins in the fifth gestational week. Its main feature is forebrain cleavage failure, which prevents the brain complete division into right and left hemispheres, the normal development of midline structures, and the deep brain structure. Based on the severity of prosencephalic cleavage failure, three classic forms (lobar, semilobar, and alobar) were described, and subsequently, interhemispheric variant (syntelencephaly) and septopreoptic variants were proposed. This review proposes a practical imaging approach to diagnosing HPE spectrum disorders, allowing an easier recognition and earlier diagnosis, which is essential for prenatal care and adequate parental counseling. In addition, we intend to simplify the understanding of HPE through a didactic discussion, schematic illustrations, and descriptions of each entity’s current classification and critical neuroimaging features, as well as the main differential diagnosis of HPE.

Purpose

The existence of glioma stem cells (GSCs) in cancer is related to glioma radiotherapy resistance. In this research, the effect of protein arginine methyltransferase 1 (PRMT1) on the radiosensitivity of glioma stem cell (GSC)-like cells, as well as its underlying mechanism, was investigated.

Methods

GSCs-like cells were analyzed and identified by flow cytometry. The self-renewal capability was evaluated by sphere-forming assay. The PRMT1 expression level in glioblastoma were analyzed using the Gene Expression Profiling Interactive Analysis database. The mRNA and protein were scrutinized by RT-qPCR and western blot, respectively. The radiosensitivity was evaluated by clonogenic survival assay. Ferroptosis was evaluated by detecting the levels of reactive oxygen species, malondialdehyde, Fe²⁺, glutathione, and 4-hydroxynonenal.

Results

U87 and SHG44 cells with GSC-like phenotype (GSC-U87 and GSC-SHG44) displayed strong expression of CD133 and nestin versus the glioma cells. GSC-U87 and GSC-SHG44 possess the self-renewal capability. The level of PRMT1 was higher in glioblastoma tumor tissues than in the normal paracancer tissues. Knockdown of PRMT1 enhanced the radiotherapy sensitivity of GSCs-like cells, which was evidenced by reduced survival fraction in GSC-U87 and GSC-SHG44 underwent sh-PRMT1 transfection. But, this effect was attenuated by Fer-1 (a ferroptosis inhibitor) treatment, accompanied by the abatement of ferroptosis.

Conclusion

PRMT1 promoted radiotherapy resistance in GSCs-like cells by inhibiting ferroptosis.

Objectives

To develop and identify machine learning (ML) models using pretreatment 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]-FDG)-positron emission tomography (PET)-based radiomic features to differentiate benign from malignant parotid gland diseases (PGDs).

Materials and methods

This retrospective study included 62 patients with 63 PGDs who underwent pretreatment [¹⁸F]-FDG-PET/computed tomography (CT). The lesions were assigned to the training (n = 44) and testing (n = 19) cohorts. In total, 49 [¹⁸F]-FDG-PET-based radiomic features were utilized to differentiate benign from malignant PGDs using five different conventional ML algorithmic models (random forest, neural network, k-nearest neighbors, logistic regression, and support vector machine) and the deep learning (DL)-based ensemble ML model. In the training cohort, each conventional ML model was constructed using the five most important features selected by the recursive feature elimination method with the tenfold cross-validation and synthetic minority oversampling technique. The DL-based ensemble ML model was constructed using the five most important features of the bagging and multilayer stacking methods. The area under the receiver operating characteristic curves (AUCs) and accuracies were used to compare predictive performances.

Results

In total, 24 benign and 39 malignant PGDs were identified. Metabolic tumor volume and four GLSZM features (GLSZM_ZSE, GLSZM_SZE, GLSZM_GLNU, and GLSZM_ZSNU) were the five most important radiomic features. All five features except GLSZM_SZE were significantly higher in malignant PGDs than in benign ones (each p < 0.05). The DL-based ensemble ML model had the best performing classifier in the training and testing cohorts (AUC = 1.000, accuracy = 1.000 vs AUC = 0.976, accuracy = 0.947).

Conclusions

The DL-based ensemble ML model using [¹⁸F]-FDG-PET-based radiomic features can be useful for differentiating benign from malignant PGDs.

Second abstract

The DL-based ensemble ML model using [¹⁸F]-FDG-PET-based radiomic features can overcome the previously reported limitation of [¹⁸F]-FDG-PET/CT scan for differentiating benign from malignant PGDs. The DL-based ensemble ML approach using [¹⁸F]-FDG-PET-based radiomic features can provide useful information for managing PGD.