Japanese Journal of Radiology最新文献

Purpose: To determine whether decision trees are useful for predicting organisms that cause community-acquired pneumonia (CAP).

Materials and methods: We developed a decision tree for predicting the organisms that cause CAP based on previously reported characteristic computed tomography findings. Sixteen readers (two student doctors, six residents, and eight radiologists) separately diagnosed 68 randomly selected cases of CAP using chest computed tomography. The first, second, and third most likely causative organisms were estimated for each case, and the percentages of correct answers were evaluated for consistency with the isolated organisms. The same 68 cases were then read again using the decision tree, with the first three most likely organisms again being estimated, and the percentage of agreement was evaluated as the percentage of correct responses after using the decision tree.

Results: For student doctors, residents, and radiologists, the percentage of correct responses increased significantly (p < 0.0001) when the decision tree was used to predict the first, second, and third most probable causative organism. The radiologists all obtained an accuracy rate of 80% or higher when estimating up to three candidate organisms using the decision tree. The organism for which the decision tree was most useful was Mycoplasma pneumoniae, followed by Haemophilus influenzae and Chlamydophila pneumoniae (p < 0.001).

Conclusion: Use of the decision tree made it possible to estimate the organisms responsible for CAP with a high correct response rate.

Purpose: To explore the diagnostic characteristics of cystitis glandularis (CG) using magnetic resonance imaging (MRI).

Materials and methods: A retrospective study was conducted on pathologically confirmed patients who underwent bladder MRI examination between January 2019 and November 2023. Image analysis was jointly conducted, with emphasis on lesion location, morphology, size, signal intensity, and pattern of enhancement, by two genitourinary radiologists with 22 and 15 years of experience, respectively.

Results: A total of 27 patients with 27 lesions were included (median age 47 years, 24 males). The lesions were mostly located in the bladder trigone area (18/27). The lesions could be categorized as focal thickening (17/27), nodular (8/27), and diffuse thickening of the entire bladder (2/27) in morphological terms. On T2-weighted imaging (T2WI), 15 of 17 focal thickening lesions appeared as a slightly hyperintense thickened inner layer, with a higher signal in the center of the thickened inner layer, resembling a sandwich sign, and 6 of 8 nodular lesions were slightly hyperintense. On T1-weighted imaging (T1WI), 19 patients showed slight hypointensity. The lesions on DWI showed mainly high (5/27) and slightly high signal (21/27), with an average mean apparent diffusion coefficient (mADC) value of 2.171 ± 0.052 × 10^-3mm²/s. Among the 23 patients who underwent dynamic contrast-enhanced (DCE) scanning, 18 lesions showed mild enhancement in the arterial phase (average 1.7 times comparing to unenhanced phase), and the degree of enhancement gradually increased in the venous and delayed phases (average 2.2 and 2.3 times compared to the unenhanced phase, respectively), showing a progressive enhancement pattern.

Conclusion: On MRI, the majority of CG manifest as focal thickening or nodules in the bladder trigone area, showing slight hyperintensity on T2WI, slight hypointensity on T1WI, and a progressive enhancement pattern, without significant restriction on DWI. Focal thickening lesions may exhibit a special sandwich sign.

Deposition arthropathies are a heterogeneous group of diseases in which organic and inorganic substances accumulate in different regions of the body with significant complications and morbidity. Although they are clearly distinct entities, the clinical manifestations are similar, so that joint evaluation by imaging provides a more accurate diagnostic approach by identifying findings characteristic of certain pathologies and is considered the gold standard in certain conditions. However, neuropathic arthropathy, especially Charcot's foot, is an essential differential diagnosis in the joint evaluation of these patients because, although clinically similar, it manifests differently on radiological evaluation, with different treatment and prognosis. It is essential to know the main findings of the different imaging modalities, as well as their surgical performance, to propose the ideal study and differentiate these conditions with certainty.

Recent advancements in breast magnetic resonance imaging (MRI) have significantly enhanced breast cancer detection and characterization. Breast MRI offers superior sensitivity, particularly valuable for high-risk screening and assessing disease extent. Abbreviated protocols have emerged, providing efficient cancer detection while reducing scan time and cost. Diffusion-weighted imaging (DWI), a non-contrast technique, has shown promise in differentiating malignant from benign lesions. It offers shorter scanning times and eliminates contrast agent risks. Apparent diffusion coefficient (ADC) values provide quantitative measures for lesion characterization, potentially reducing unnecessary biopsies. Studies have revealed some correlations between ADC values and hormone receptor status in breast cancers, although substantial variability exists among studies. However, standardization remains challenging. Initiatives such as European Society of Breast Imaging (EUSOBI), Diffusion-Weighted Imaging Screening Trial (DWIST), Quantitative Imaging Biomarkers Alliance (QIBA) have proposed guidelines to ensure consistency in imaging protocols and equipment specifications, addressing variability in ADC measurements across different sites and vendors. Advanced techniques like Intravoxel incoherent motion (IVIM) and non-Gaussian DWI offer insights into tissue microvasculature and microstructure. Despite ongoing challenges, the integration of these advanced MRI techniques shows great promise for improving breast cancer diagnosis, characterization, and treatment planning. Continued research and standardization efforts are crucial for maximizing the potential of breast DWI in enhancing patient care and outcomes.

Purpose: To compare image quality and visibility of anatomical structures on contrast-enhanced thin-slice abdominal CT images reconstructed using super-resolution deep learning reconstruction (SR-DLR), deep learning-based reconstruction (DLR), and hybrid iterative reconstruction (HIR) algorithms.

Materials and methods: This retrospective study included 54 consecutive patients who underwent contrast-enhanced abdominal CT. Thin-slice images (0.5 mm thickness) were reconstructed using SR-DLR, DLR, and HIR. Objective image noise and contrast-to-noise ratio (CNR) for liver parenchyma relative to muscle were assessed. Two radiologists independently graded image quality using a 5-point rating scale for image noise, sharpness, artifact/blur, and overall image quality. They also graded the visibility of small vessels, main pancreatic duct, ureters, adrenal glands, and right adrenal vein on a 5-point scale.

Results: SR-DLR yielded significantly lower objective image noise and higher CNR than DLR and HIR (P < .001). The visual scores of SR-DLR for image noise, sharpness, and overall image quality were significantly higher than those of DLR and HIR for both readers (P < .001). Both readers scored significantly higher on SR-DLR than on HIR for visibility for all structures (P < .01), and at least one reader scored significantly higher on SR-DLR than on DLR for visibility for all structures (P < .05).

Conclusion: SR-DLR reduced image noise and improved image quality of thin-slice abdominal CT images compared to HIR and DLR. This technique is expected to enable further detailed evaluation of small structures.

Objectives: To develop and validate a combined clinical and radiomics model for non-invasive prediction of lung cancer (LC) pathological types (lung adenocarcinoma, lung squamous cell carcinoma, and small cell lung cancer) based on patients' pre-treatment FDG PET/CT images and clinical data, as a complementary tool to aid in the diagnosis of LC pathological histological classification.

Methods: In total, 896 patients with pathological confirmation of lung cancer were part of this retrospective study. The training and test groups included 819 patients who underwent scanning using scanner 1. The independent validation group included 77 patients who using scanner 2. The optimal features were retained by least absolute shrinkage and selection operator algorithm dimensionality reduction screening of the collected radiomics features, clinical parameters, and PET metabolic parameters. Five models were established to predict the lung cancer pathological types by the k-nearest neighbor classification (KNN) algorithm. The performance of the prediction model was assessed by calculating the area under the curve (AUC) from the receiver operator characteristic curve (ROC).

Results: Of all five predictive models (the PET-only radiomics model, the CT-only radiomics model, the PET/CT radiomics model, the clinical-only model and the combined clinical and PET/CT radiomics model), the clinical combined PET/CT radiomics model exhibited best performance. The macro-AUC for the training, test and independent validation groups were 0.974, 0.931, 0.960, the micro-AUC were 0.976, 0.940, 0.970, and the accuracy were 0.963, 0.914, and 0.961, respectively.

Conclusions: Our model combined radiomics and clinical data and showed higher performance in non-invasively predicting the LC pathological types, which suggesting that PET/CT radiomics may be a promising technique for predicting LC histopathology.

Purpose: N-butyl-2-cyanoacrylate (NBCA) and Lipiodol mixture (NL) are widely used for emergency embolization due to their effective polymerization upon contact with blood. However, NBCA's strong adhesive properties can cause complications, leading to the development of an NBCA-Lipiodol-ethanol mixture (NLE), which has shown reduced catheter adhesion. This study aimed to observe the structural differences between NL and NLE polymers using scanning electron microscopy.

Materials and methods: Four different ratios of NBCA, Lipiodol, and ethanol (NLE230, NLE221, NLE150, and NLE141) were examined. The samples were injected into silicone tubes filled with human serum, and the polymerized specimens were collected and observed using scanning electron microscopy.

Results: NLE230 formed a dense, three-dimensional honeycomb-like structure, whereas NLE221 exhibited a two-dimensional folded-sheet structure. Both NLE150 and NLE141 exhibited a folded-sheet structure; however, NLE141 was considerably more fragile, with cracks and rough surfaces, resulting in a structure that lacked uniformity.

Conclusion: The differences in structure suggest that ethanol considerably influences the polymerization process. These differences may explain characteristics of NLE, such as low adhesion.

Background and purpose: This study investigated effects of target coverage on local recurrence (LR) in stereotactic body radiotherapy (SBRT) for early-stage lung squamous cell carcinoma (SCC).

Materials and methods: Patients with clinical stage IA1-IIA lung SCC treated with SBRT were included in the analysis. Doses of 48-52 Gy were prescribed to the isocenter of the planning target volume according to the tumor diameter. The primary endpoint was LR. To examine the independent effects of dosimetric factors on LR after adjustment for clinical factors, Fine-Gray model with death as a competing risk was used for evaluation.

Results: Among all 59 patients analyzed, the median follow-up was 42 months. The 3-year LR rate was 24.0%. Univariate analysis of clinical factors showed that biologically effective dose calculated with an α/β value of 10 (BED₁₀) was associated with LR (p = 0.033). After adjustment for clinical factors, internal target volume (ITV) Dmean was associated with LR (p = 0.049). Subgroup analysis was performed for each prescribed dose group. The results of Fine-Gray model and receiver operating characteristic curve analysis showed that ITV Dmean > 100% of the prescribed dose was the best indicator of preventing LR.

Conclusions: ITV coverage may be particularly important in SBRT for early-stage lung SCC.

Purpose: To determine the diagnostic merit of using quantitative imaging parameters measured on non-contrast CT (NCCT) in the diagnosis of cerebral venous thrombosis (CVT).

Materials and methods: 43 patients with CVT and 30 age and sex-matched controls were enrolled in this retrospective study. Two blinded neuroradiologists independently assessed the NCCT scans for direct and indirect signs of CVT. Absolute attenuation values of thrombosed and non-thrombosed sinuses were measured and the ratio of sinus attenuation to patient's hematocrit (H/H ratio) was calculated for each case. The attenuation value of the internal carotid artery was also measured to calculate the veno-arterial (V/A) difference. Inter-reader agreement was evaluated and all measurements were compared between patient and control groups.

Results: The sensitivity and specificity of the dense sinus sign for diagnosis of CVT ranged from 72 to 79% and from 83 to 87% respectively. Sinus attenuation, H/H ratio and V/A difference were significantly higher in the CVT group than in the control group (P < 0.0001). An attenuation threshold value of > 55 HU yielded a sensitivity of 86% and a specificity of 90% and had the largest AUC of 0.89 (95%CI 0.795-0.951) among all stand-alone parameters, while the combination of an attenuation value greater than 55, or a V/A difference greater than 22, yielded the best diagnostic performance among all the parameters with sensitivity and specificity at values of 86% and a 100% respectively and an AUC of 0.93 (95%CI 0.846 to 0.977).

Conclusions: Overall, the analysis of quantitative parameters resulted in a notable upgrade in the accuracy of the diagnosis of CVT over visual inspection alone. Their high specificities make them reliable markers of CVT, yet their relatively lower sensitivities may indicate a need to perform further studies to safely eliminate the possibility of CVT in highly suspicious cases.

Trial registration number: FMASU R 10/2020/2021.