Japanese Journal of Radiology最新文献

Purpose: ⁶⁸Ga-Pentixafor PET/CT is a novel imaging modality targeting the C-X-C chemokine receptor type 4 (CXCR4), which plays a crucial role in immune regulation, stem cell homing, and tumor progression. While its clinical use is expanding, comprehensive characterization of its physiological biodistribution remains limited.

Methods: This study retrospectively included 73 individuals who underwent ⁶⁸Ga-Pentixafor PET/CT, comprising patients with various benign and malignant conditions, as well as healthy volunteers. Time-activity curves (TACs) were generated in two volunteers with dynamic and static imaging at multiple timepoints. Semi-quantitative uptake metrics (SUV_max and SUV_mean) were measured across normal organs and tissues. Age- and sex-related uptake patterns were analyzed in the cohort. Moreover, a subgroup of 12 participants underwent dual-timepoint imaging at 30 and 60 min post-injection of ⁶⁸Ga-Pentixafor was analyzed.

Results: ⁶⁸Ga-Pentixafor demonstrated primarily urinary clearance with intense radiotracer accumulation in the kidneys and bladder, and displayed obvious physiological uptake in the nasopharynx, palatine tonsils, thymus, spleen, adrenal glands, and pediatric bone. Males showed higher muscle SUV_max than females (P = 0.036), while females displayed higher thymus SUV_max and SUV_mean than males (both P < 0.001). Pediatric subjects exhibited higher radiotracer uptake in the nasopharynx, thymus and bone than adults (P < 0.05), whereas adults demonstrated higher radioactivity uptake in the thyroid, stomach, prostate, testes, and muscle than children (P < 0.05). Moreover, significantly lower radiotracer uptake was observed at 60 min compared to 30 min post-injection in the nasopharynx, parotid glands, lungs, blood pool, spleen, pancreas, kidneys, bone, and muscle (P < 0.05). This suggested that imaging at 60 min provided superior target-to-background contrast compared to 30 min.

Conclusions: ⁶⁸Ga-Pentixafor exhibited significant physiological uptake in nasopharynx, palatine tonsils, thymus, spleen, adrenal glands, pediatric bone, kidneys, and bladder. Semi-quantitative uptake values varied with sex, age and imaging time. These findings provided essential guidance for interpreting CXCR4-targeted PET/CT imaging.

Purpose: To assess and compare the accuracy and legitimacy of multimodal large language models (LLMs) on the Japan Diagnostic Radiology Board Examination (JDRBE).

Materials and methods: The dataset comprised questions from JDRBE 2021, 2023, and 2024, with ground-truth answers established through consensus among multiple board-certified diagnostic radiologists. Questions without associated images and those lacking unanimous agreement on answers were excluded. Eight LLMs were evaluated: GPT-4 Turbo, GPT-4o, GPT-4.5, GPT-4.1, o3, o4-mini, Claude 3.7 Sonnet, and Gemini 2.5 Pro. Each model was evaluated under two conditions: with inputting images (vision) and without (text-only). Performance differences between the conditions were assessed using McNemar's exact test. Two diagnostic radiologists (with 2 and 18 years of experience) independently rated the legitimacy of responses from four models (GPT-4 Turbo, Claude 3.7 Sonnet, o3, and Gemini 2.5 Pro) using a five-point Likert scale, blinded to model identity. Legitimacy scores were analyzed using Friedman's test, followed by pairwise Wilcoxon signed-rank tests with Holm correction.

Results: The dataset included 233 questions. Under the vision condition, o3 achieved the highest accuracy at 72%, followed by o4-mini (70%) and Gemini 2.5 Pro (70%). Under the text-only condition, o3 topped the list with an accuracy of 67%. Addition of image input significantly improved the accuracy of two models (Gemini 2.5 Pro and GPT-4.5), but not the others. Both o3 and Gemini 2.5 Pro received significantly higher legitimacy scores than GPT-4 Turbo and Claude 3.7 Sonnet from both raters.

Conclusion: Recent multimodal LLMs, particularly o3 and Gemini 2.5 Pro, have demonstrated remarkable progress on JDRBE questions, reflecting their rapid evolution in diagnostic radiology. Eight multimodal large language models were evaluated on the Japan Diagnostic Radiology Board Examination. OpenAI's o3 and Google DeepMind's Gemini 2.5 Pro achieved high accuracy rates (72% and 70%) and received good legitimacy scores from human raters, demonstrating steady progress.

Objective: The purpose of this research was to evaluate the effectiveness of contrast-enhanced computed tomography (CECT)-based habitat radiomics in differentiating low-risk thymomas from high-risk thymomas prior to surgery.

Materials and methods: A retrospective study was conducted involving patients with thymomas who had undergone CECT at three medical centers. The patients were divided into two cohorts: a training cohort comprising 134 patients from Centers A and B, and a validation cohort consisting of 41 patients from Center C. The k-means clustering algorithm was employed to segment the CECT images into distinct tumor habitats. Radiomic features were extracted from the entire tumor and the specific habitats identified. After feature selection, logistic regression (LR) model was developed to distinguish between low-risk and high-risk thymomas.

Results: A total of 175 patients were enrolled in the study, with 106 diagnosed with low-risk thymomas and 69 with high-risk thymomas. In the validation cohort, the area under the receiver operating characteristic curve (AUC) values for the models derived from the whole tumor, habitat_1, habitat_2, and habitat_3 were 0.806 (95% CI 0.675-0.938), 0.946 (95% CI 0.861-1.000), 0.620 (95% CI 0.446-0.794), and 0.946 (95% CI 0.885-1.000), respectively. The habitats model demonstrated superior predictive performance compared to the whole tumor model.

Conclusion: CECT-based habitat radiomics represents a promising diagnostic approach for distinguishing between low-risk and high-risk thymomas in the preoperative setting, highlighting its potential for enhanced diagnostic accuracy.

Purpose: This systematic review aims to assess the efficacy and safety of percutaneous aspiration and sclerotherapy (PAS) for patients with symptomatic simple hepatic cysts (SHCs).

Materials and methods: We systematically searched the electronic databases of PubMed, Embase, the Cochrane Library and Ichushi-Web for studies published up to November 2024, reporting outcomes of PAS for symptomatic SHCs. The primary outcomes were rates of symptomatic relief or disappearance of symptoms. The secondary outcomes were cyst volume reduction rates and complication rates. Subgroup analyses compared ethanol with the other sclerosants. Single-arm meta-analyses were performed, with meta-regression conducted when substantial heterogeneity (I² > 50%) was observed. Risk of bias was assessed using the Cochrane RoB2 tool for randomized controlled trials and RoBANS2 for non-randomized studies.

Results: Sixteen studies were included. Fourteen studies were assessed as having a high risk of bias. The pooled symptomatic relief or disappearance rate was 86.9% (95% CI 80.2-91.6%, I² = 0%). The cyst volume reduction rate was 86.4% (95% CI 74.1-93.3%, I² = 95%). There were no major complications. The pooled minor complication rates were 13.6% (95% CI 6.5-26.4%, I² = 67.2%) for pain and 7.4% (95% CI 4.1-13.0%, I² = 38%) for fever. Subgroup analysis showed no significant differences between ethanol and other sclerosants. High heterogeneity was observed for cyst volume reduction and pain, indicating variability across studies. Meta-regression analysis for cyst volume reduction rate and pain did not identify any significant associations.

Conclusion: PAS appears to be a relatively safe and effective treatment option for patients with symptomatic SHCs and provides high rates of symptomatic relief with low complication rates. However, given the high risk of bias in the available evidence and the lack of direct comparison with surgical treatment, these findings should be interpreted with caution. Further high-quality comparative studies are warranted to confirm these results.

Purpose: To evaluate the image quality and clinical utility of ultra-fast T2-weighted imaging (UF-T2WI), which acquires all slice data in 7 s using a single-shot turbo spin-echo technique combined with dual-type deep learning (DL) reconstruction, incorporating DL-based image denoising and super-resolution processing, by comparing UF-T2WI with conventional T2WI.

Material and methods: We analyzed data from 38 patients who underwent both conventional T2WI and UF-T2WI with the dual-type DL-based image reconstruction. Two board-certified radiologists independently performed blinded qualitative assessments of the patients' images obtained with UF-T2WI with DL and conventional T2WI, evaluating the overall image quality, anatomical structure visibility, and levels of noise and artifacts. In cases that included central nervous system diseases, the lesions' delineation was also assessed. The quantitative analysis included measurements of signal-to-noise ratios in white and gray matter and the contrast-to-noise ratio between gray and white matter.

Results: Compared to conventional T2WI, UF-T2WI with DL received significantly higher ratings for overall image quality and lower noise and artifact levels (p < 0.001 for both readers). The anatomical visibility was significantly better in UF-T2WI for one reader, with no significant difference for the other reader. The lesion visibility in UF-T2WI was comparable to that in conventional T2WI. Quantitatively, the SNRs and CNRs were all significantly higher in UF-T2WI than conventional T2WI (p < 0.001).

Conclusion: The combination of SSTSE with dual-type DL reconstruction allows for the acquisition of clinically acceptable T2WI images in just 7 s. This technique shows strong potential to reduce MRI scan times and improve clinical workflow efficiency.

Gadoxetic acid-enhanced magnetic resonance imaging (MRI) has become a pivotal imaging modality in hepatocellular carcinoma (HCC) management, offering unique advantages owing to its hepatocyte-specific contrast properties. Its technical foundation includes optimized dynamic phase imaging and hepatobiliary phase (HBP) acquisition, which together provide functional information unattainable with conventional extracellular contrast agents. This modality enhances sensitivity in detecting HCC and enables superior characterization of focal liver lesions based on hepatocyte-specific uptake patterns. In high-risk patients with chronic liver disease, gadoxetic acid-enhanced MRI facilitates the early detection of small and early-stage HCCs, enabling timely intervention and potentially improving clinical outcomes. Beyond diagnosis, gadoxetic acid-enhanced MRI aids in predicting treatment response by evaluating tumor biological characteristics. Key imaging biomarkers include: hyperintense or heterogeneous HCC on HBP, suggesting tumor immune microenvironment; peritumoral hypointensity on HBP, suggesting microvascular invasion; and clear hypointensity on HBP with several other findings, indicating vessels encapsulating tumor clusters, characteristic of the macrotrabecular-massive HCC subtype. These biomarkers support a comprehensive evaluation of histological differentiation and biological aggressiveness. Furthermore, this modality demonstrates superior accuracy in assessing local therapy effectiveness and monitoring systemic treatment responses compared to conventional imaging. Major international hepatology societies have incorporated gadoxetic acid-enhanced MRI into their HCC diagnostic algorithms, albeit with regional differences in emphasis. Eastern guidelines (e.g., from the Japan Society of Hepatology and the Asian Pacific Association for the Study of the Liver) prioritize sensitivity, whereas Western guidelines (e.g., from the European Association for the Study of the Liver and the Liver Imaging Reporting and Data System) emphasize specificity. Despite certain limitations, including potential suboptimal arterial phase visualization, challenges in interpreting the transitional phase, higher cost, and longer examination times, gadoxetic acid-enhanced MRI remains an indispensable tool in precision oncology, enabling personalized treatment strategies and supporting optimal patient outcomes through comprehensive HCC characterization and accurate treatment monitoring.

Background: Hepatocellular carcinoma (HCC), particularly in recurrent or treatment-refractory cases, often exhibits poor responsiveness to radiation therapy, increasing the risk of radiation-induced liver disease, necessitating innovative treatment approaches. Boric acid-mediated boron neutron capture therapy (BA-BNCT) has emerged as a promising approach for liver cancer. This study aims to improve BA-BNCT efficacy for radioresistant HCC by exploring sensitization agents, enhancing treatment while minimizing irradiation doses and side effects.

Methods: We targeted the DNA homologous recombination repair (HRR) protein RAD51. Before neutron irradiation, a RAD51 inhibitor, B02, was administered to evaluate its sensitization effect on both HepG2 and the radioresistant HepG2R cells. We examined the cell death mechanism, focusing on the expression profile of LC3B after BA-BNCT, to investigate its impact on DNA repair responses, especially on autophagy and apoptosis.

Results: We observed that inhibition of RAD51 led to increased γH2AX, the DNA double-strand break marker. Additionally, combining the RAD51 inhibitor B02 with BA-BNCT resulted in tumor cell arrest in the G₀/G₁ phase, indicating altered cell cycle regulation. In exploring cell death mechanisms, we observed increased autophagy following BNCT, potentially as a response to cellular stress induced by DNA damage in tumor cells. The combination of B02 and BA-BNCT significantly disrupted autophagic flux and promoted apoptosis in the tumor cells.

Conclusions: Combining a RAD51 inhibitor with BA-BNCT significantly enhances the anti-tumor efficacy against radioresistant HCC and parental HCC cells. This proof-of-concept study suggests that the combination treatment can achieve comparable or superior therapeutic effects using lower radiation doses, thereby reinforcing the potential of BNCT for treating recurrent HCC.

Purpose: To evaluate the MRI and CT features of head and neck myoepithelioma in comparison with parotid pleomorphic adenoma.

Methods: This retrospective study included 11 patients with histopathologically confirmed myoepithelioma of the head and neck and 103 patients with pleomorphic adenoma of the parotid gland, all of whom underwent preoperative MRI. Among them, seven patients with myoepithelioma and 29 with pleomorphic adenoma also underwent preoperative CT. MRI and CT findings were compared between the two groups.

Results: Multinodular configuration (27% vs. 4%), mild hyperintensity relative to the spinal cord on T2-weighted images (91% vs. 48%), and focal unenhanced areas on fat-suppressed contrast-enhanced T1-weighted images (100% vs. 47%) were significantly more frequent in myoepithelioma than in pleomorphic adenoma, respectively (p < 0.05). In contrast, marked hyperintensity relative to the spinal cord on T2-weighted images (46% vs. 9%), higher signal intensity ratios on T2-weighted images (1.68 ± 0.47 vs. 1.40 ± 0.39), and higher apparent diffusion coefficient (ADC) values (1.68 ± 0.36 vs. 1.38 ± 0.23 × 10^-3 mm²/s) were significantly more common in pleomorphic adenoma than in myoepithelioma, respectively (p < 0.05). Contrast-enhanced CT attenuation was significantly higher in myoepithelioma than in pleomorphic adenoma (93.3 ± 10.5 vs. 59.2 ± 22.8 HU, p < 0.05).

Conclusions: Although MRI and CT features of myoepithelioma and pleomorphic adenoma can overlap, the presence of a multinodular configuration, focal unenhanced areas, lower T2 signal intensity, lower ADC values, and higher contrast-enhanced CT attenuation may aid in differentiating myoepithelioma from pleomorphic adenoma.

Objectives: To identify the optimal material decomposition (MD) images for diagnosis of pancreatic ductal adenocarcinoma (PDAC) and evaluate the added value of the MD image to 50-keV virtual monoenergetic images (VMIs) by comparing with iodine-based images and 50-keV VMIs.

Methods: This retrospective study included patients who underwent pancreatic protocol dual-energy CT (DECT) between February 2019 and May 2023. First, a radiologist evaluated 702 image datasets generated using 27 different materials to identify the top three MD images which provided maximum contrast difference between normal pancreas and PDAC, and subsequently, the best MD image was selected based on z value and image quality by four radiologists. Then, another four radiologists independently interpreted the conventional image dataset (iodine-based images and 50-keV VMIs) and new optimal image dataset (optimal MD images and 50-keV VMIs), and graded the presence or absence of PDAC. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were compared between the two image datasets using generalized estimating equations.

Results: Overall, 110 patients (median age, 73 years; 63 men) were included. Among them, 67 patients (61%) had pathologically proven PDAC, and the optimal MD image selected was Silicon/Struvite. The optimal image dataset had higher specificity (88% vs. 81%; P = 0.006), PPV (93% vs. 89%; P < 0.001), and accuracy (94% vs. 92%; P = 0.01) than the conventional image dataset. No difference was found in the sensitivity (P = 0.34) and NPV (P = 0.33) between the two image datasets.

Conclusion: Silicon/Struvite images provided high contrast difference between normal pancreas and PDAC and higher diagnostic performance for diagnosis of PDAC in combination of 50-keV VMIs compared to iodine-based images and 50-keV VMIs.