European Radiology Experimental最新文献

Background: We evaluated the acceleration of a three-dimensional isotropic flow-independent magnetic resonance angiography (MRA) (relaxation-enhanced angiography without contrast and triggering, REACT) of neck arteries using compressed SENSE (CS) combined with deep learning (adaptive intelligence, AI)-based reconstruction (CS-AI).

Methods: Thirty-four volunteers received 3-T REACT MRA, acquired threefold: (i) CS acceleration factor 7 (CS7), scan time 1:20 min:s; (ii) CS acceleration factor 10 (CS10), scan time 0:55 min:s; and (iii) CS-AI acceleration factor 10 (CS10-AI), scan time 0:55 min:s. Two radiologists rated the image quality of seven arterial segments and overall image noise. Additionally, a pairwise forced-choice comparison was conducted. Apparent signal-to-noise ratio (aSNR) and contrast-to-noise ratio (aCNR) were measured, and image sharpness was assessed using the edge-rise distance (ERD). Multiple t-tests and nonparametric tests with Bonferroni correction were performed for comparison to CS7 as the reference standard.

Results: Compared to CS7, CS10 showed lower image quality (p < 0.001) while CS10-AI obtained higher scores (p = 0.010). Image noise was similar between CS7 and CS10 (p = 0.138) while CS10-AI yielded a lower noise (p = 0.008). Forced choice revealed preferences for CS7 over CS10 (p < 0.001), but no preference between CS7 and CS10-AI (p > 0.999). Compared to CS7, aSNR and aCNR were lower in CS10 (p < 0.001) and the ERD was longer (p = 0.004), while CS10-AI provided better aSNR and aCNR (p = 0.001) and showed no difference in ERD (p = 0.776).

Conclusion: Sub-1-min CS-AI cervical REACT MRA was acquired without compromising image quality.

Relevance statement: The implementation of a fast and reliable non-contrast MRA has the potential to reduce costs and time while increasing patient comfort and safety. Clinical studies evaluating the diagnostic performance for stenosis or dissection are needed.

Trial registration: DRKS00030210 (German Clinical Trials Register; https://drks.de/ ) KEY POINTS: Deep learning reconstruction enables sub-1-min non-contrast-enhanced MRA of extracranial arteries. Acceleration without deep learning reconstruction causes inferior image quality. Acceleration with deep learning reconstruction exceeds, in part, the clinical standard.

Background: Gadobenate and gadoxetate are hepatobiliary magnetic resonance imaging (MRI) contrast agents. We intraindividually compared these two agents for the characterization of focal liver lesions (FLLs).

Methods: A total of 140 adult subjects were randomized to undergo two 3-T MRI exams separated by 7-14 days, one with 0.05 mmol/kg gadobenate and one with 0.025 mmol/kg gadoxetate. For both exams, we acquired the same unenhanced T1-weighted, T2-weighted, and diffusion-weighted sequences, followed by contrast-enhanced T1-weighted sequences during the dynamic and hepatobiliary phases (HBP) (at 20 min for gadoxetate, at 120 min for gadobenate). Three experienced unaffiliated readers independently evaluated each exam in blinded, randomized order for lesion nature (benign/malignant) and specific lesion diagnosis. McNemar test, Wald tests. paired t-tests and κ statistics were used.

Results: A total of 208 FLLs (108 malignant and 100 benign) were confirmed at final diagnosis. Sensitivity and specificity for malignant/benign differentiation ranged from 91.6% to 99.1% and from 87.5% to 90.5% for gadobenate, and from 86.0% to 91.6% and from 79.7% to 83.6% for gadoxetate. Significantly (p ≤ 0.025) higher values for gadobenate were determined for all diagnostic performance parameters except for sensitivity and negative predictive value for one reader. Significantly (p < 0.001) greater accuracy and confidence for specific lesion diagnosis was achieved with gadobenate for two of three blinded readers. Interreader agreement for malignant/benign differentiation was better with gadobenate (κ = 0.91 versus κ = 0.72).

Conclusion: Gadobenate was superior to gadoxetate for the differentiation and diagnosis of malignant and benign FLLs for two of three readers. Further confirmatory studies that include a wider representation of different types of FLLs are warranted.

Relevance statement: Better diagnostic performance and greater confidence in the characterization of FLLs with gadobenate might improve patient management decisions and timings, and potentially lead to better patient outcomes.

Key points: Better diagnostic performance for the differentiation of FLLs was achieved with gadobenate for two of three readers. Reader confidence for lesion diagnosis was greater with gadobenate. Superior dynamic phase imaging with gadobenate was crucial for accurate lesion diagnosis.

Background: We established and validated an innovative two-phase pipeline for automated detection and segmentation on multi-parametric cervical cancer magnetic resonance imaging (MRI) and investigated the clinical efficacy.

Methods: The retrospective multicenter study included 125 cervical cancer patients enrolled in two hospitals for 14,547 two-dimensional images. All the patients underwent pelvic MRI examinations consisting of diffusion-weighted imaging (DWI), T2-weighted imaging (T2WI), and contrast-enhanced T1-weighted imaging (CE-T1WI). The deep learning framework involved a multiparametric detection module utilizing ConvNeXt blocks and a subsequent segmentation module utilizing 3-channel DoubleU-Nets. The pipeline was trained and tested (80:20 ratio) on 3,077 DWI, 2,990 T2WI, and 8,480 CE-T1WI slices.

Results: In terms of reference standards from gynecologic radiologists, the first automated detection module achieved overall results of 93% accuracy (95% confidence interval 92-94%), 93% precision (92-94%), 93% recall (92-94%), 0.90 κ (0.89-0.91), and 0.93 F1-score (0.92-0.94). The second-stage segmentation exhibited Dice similarity coefficients and Jaccard values of 83% (81-85%) and 71% (69-74%) for DWI, 79% (75-82%), and 65% (61-69%) for T2WI, 74% (71-76%) and 59% (56-62%) for CE-T1WI.

Conclusion: Independent experiments demonstrated that the pipeline could get high recognition and segmentation accuracy without human intervention, thus effectively reducing the delineation burden for radiologists and gynecologists.

Relevance statement: The proposed pipeline is potentially an alternative tool in imaging reading and processing cervical cancer. Meanwhile, this can serve as the basis for subsequent work related to tumor lesions. The pipeline contributes to saving the working time of radiologists and gynecologists.

Key points: An AI-assisted multiparametric MRI-based pipeline can effectively support radiologists in cervical cancer evaluation. The proposed pipeline shows high recognition and segmentation performance without manual intervention. The proposed pipeline may become a promising auxiliary tool in gynecological imaging.

Background: We aimed to validate a low-dose two-volume pulmonary computed tomography (CT) perfusion technique.

Methods: Five Yorkshire swine (weight 53.6 ± 2.6 kg) underwent 21 independent CT perfusion acquisitions. Intravenous contrast material (370 mg/mL iodine, 0.5 mL/kg) and saline chaser (0.5 mL/kg) were injected at 5 mL/s for each acquisition. Two-volume and multivolume dynamic CT perfusion data were acquired using a 320-slice CT, with multivolume measurements serving as the reference standard. The two-volume CT perfusion involved a low-dose (50 mA) volume scan before contrast injection and a diagnostic (300 mA) volume scan after bolus-tracking in the main pulmonary artery at the peak contrast enhancement. Multivolume CT perfusion included 15-20 volume scans for blood flow measurement. Paired sample t-test, linear regression, and Bland-Altman analysis compared both global and regional two-volume perfusion measurements to the reference standard. The reproducibility of the two-volume CT perfusion was assessed from two independent measurements under the same perfusion condition.

Results: Two-volume global perfusion measurements (P_2V) were related to reference multivolume (P_MV) measurements by P_2V = 0.96 × P_MV + 0.45 (r = 0.92), with a root-mean-square error of 1.29 mL/min/g and a root-mean-square deviation of 1.29 mL/min/g. The CT dose index for the two-volume and multivolume CT perfusion measurements were 9.3 mGy and 184.8 mGy, respectively.

Conclusion: We successfully validated a prospective, two-volume CT perfusion technique in a swine model. The findings affirm the feasibility of accurate and reproducible pulmonary blood flow measurement.

Relevance statement: This two-volume CT pulmonary perfusion technique, validated in a swine model, demonstrates the feasibility of blood flow measurement with a substantial reduction in radiation exposure. It could allow low-dose regional blood flow measurement in the assessment of pulmonary artery disease in humans.

Key points: Lung perfusion can be measured in mL/min/g using a prospective, two-volume CT technique. Flow measurement is achievable in a swine model with a radiation dose as low as 9.3 mGy. CT angiography and perfusion can be acquired following a single contrast injection.

Background: The objective of this study was to evaluate the therapeutic effectiveness and safety of transarterial chemoembolization (TACE) combined with programmed cell death-1 (PD-1) inhibitors and lenvatinib in the treatment of unresectable intrahepatic cholangiocarcinoma (uICC).

Methods: This multicenter retrospective study screened patients with uICC who underwent TACE in combination with PD-1 inhibitors and lenvatinib between January 2019 and June 2023. Tislelizumab or camrelizumab (200 mg) was intravenously administered every three weeks. The daily dose of lenvatinib was 8 mg for patients weighing < 60 kg and 12 mg for those weighing ≥ 60 kg. In cases of disease progression, the therapeutic strategy was adjusted based on the clinical condition and individual patient's treatment preferences. Options included transitioning to standard or supportive care or continuing treatment with TACE in combination with PD-1 inhibitors and lenvatinib. The primary outcomes were overall survival (OS) and progression-free survival (PFS), while secondary outcomes included the objective response rate (ORR), disease control rate (DCR), and the incidence of adverse events (AEs).

Results: A total of 59 patients with uICC were included. Over a median follow-up period of 32.3 months, the median OS and PFS were 25.8 months (95% confidence interval [CI]: 17.9-33.7) and 9.5 months (95% CI: 7.9-11.0), respectively. The ORR was 55.9%, and the DCR was 96.6%. Grade 3 or four AEs were observed in 15 of 59 patients (25.4%).

Conclusion: TACE combined with PD-1 inhibitors and lenvatinib demonstrated a promising therapeutic potential with a manageable safety profile for patients with uICC.

Relevance statement: The combination of TACE, PD-1 inhibitors, and lenvatinib represents a novel therapeutic option for patients with uICC.

Key points: TACE plus PD-1 inhibitors and lenvatinib represent a promising therapeutic strategy for uICC. The safety profile of TACE plus PD-1 inhibitors and lenvatinib was manageable. This study demonstrated improved outcomes compared to prior standard-of-care treatments.

Background: To evaluate the efficacy of computed tomography (CT) lymphangiography after direct mesenteric lymph node injection for thoracic duct (TD) visualization in mice.

Methods: Twelve female BALB/c mice were injected with 35 μL of iodinated contrast medium (iomeprol 350 mgI/mL) into the mesenteric (mesenteric group) or popliteal (popliteal group) lymph nodes. CT images were acquired before injection and 1 min, 3 min, 5 min, 10 min, and 15 min after injection using a micro-CT scanner. Contrast ratios (CRs) were measured at the cisterna chyli and three levels of the TD (diaphragm, carina, and venous angle). Two experienced radiologists qualitatively assessed images as good, fair, or poor.

Results: The mesenteric group had significantly higher mean (± standard deviation) CRs than the popliteal group for all examined regions at 1 min after injection: cisterna chyli (14.01 ± 4.77 versus 1.47 ± 1.21, p < 0.001), diaphragm (7.28 ± 2.50 versus 0.85 ± 0.61, p = 0.0011), carina (10.33 ± 3.42 versus 0.44 ± 0.40, p < 0.001), and venous angle (6.26 ± 2.02 versus 0.79 ± 0.75, p < 0.001). For the TD between the cisterna chyli and the diaphragm, 6/6 mice in the mesenteric group showed strong enhancement, whereas 5/6 mice in the popliteal group showed minimal or no enhancement. The visual scores of the mesenteric group were significantly higher than those of the popliteal group for all the evaluated regions (p = 0.002).

Conclusion: CT lymphangiography via mesenteric lymph node injection provides better imaging of the TD in mice than popliteal lymph node injection.

Relevance statement: This study enhances TD visualization in mice, advancing preclinical research on lymphatic disorders and improving translational applications for better clinical diagnostics and treatments.

Key points: Mesenteric lymph node injection improved the efficacy of TD CT lymphangiography in mice. Mesenteric injection provided significantly better TD visualization than popliteal injection. Enhanced TD visualization in mice advances preclinical research on lymphatic diseases.

Background: The poor uptake of imaging referral guidelines in Europe results in a substantial amount of inappropriate computed tomography (CT) scans. Publicly available chatbots, ChatGPT and Gemini, offer an alternative for justifying real-world referrals. Recent research reports high ChatGPT accuracy when analysing American College of Radiology Appropriateness Criteria variants. We compared the chatbots' performance in interpreting, justifying, and suggesting alternative imaging for unstructured adult brain CT referrals in accordance with the European Society of Radiology iGuide. Our prediction model for automated iGuide categorisation of referrals was also compared against the chatbots.

Methods: The iGuide justification of 143 real-world CT brain referrals, used to evaluate a prediction model, was analysed by two radiographers and radiologists. ChatGPT-4's and Gemini's imaging recommendations and pathology suspicions were compared with those of humans, with respect to referral completeness. Inter-rater reliability with κ statistics determined the agreement between entities.

Results: Chatbots' performance was limited (κ = 0.3) but improved for more complete referrals. The prediction model outperformed the chatbots in justification analysis (κ = 0.853). The chatbots' interpretations of complete referrals were highly consistent (49/52, 94.2%). The agreement regarding alternative imaging was high for both complete and ambiguous referrals, with ChatGPT and Gemini correctly identifying imaging modality and anatomical region in 83/96 (86.5%) and 81/96 (84.4%) cases, respectively.

Conclusion: The chatbots' ability to analyse the justification of adult brain CT referrals is limited to complete referrals, unlike our prediction model. Further research is needed to confirm these findings for other types of CT scans and modalities.

Relevance statement: ChatGPT and Gemini exhibit potential in justifying free text brain CT referrals; however, further improvements are required to handle real-world referrals of varying quality.

Key points: Custom prediction model's justification analysis strongly aligns with iGuide and surpasses chatbots. Chatbots incorrectly justified almost one-half of all CT brain referrals. Chatbots have limited performance in justifying ambiguous CT brain referrals. Chatbot performance improved when referrals were detailed and included suspected pathology.

Background: We assessed the safety and efficacy of computed tomography (CT)-guided high-dose-rate (HDR) brachytherapy in treating hepatocellular carcinoma (HCC) with portal vein tumor thrombosis (PVTT).

Methods: From January 2010 to January 2022, 56 patients (median age 67.5 years) with HCC and PVTT underwent 64 procedures. PVTT was further classified according to the Japan liver cancer study group into VP1-VP4. Tumor response was evaluated by cross-sectional imaging 6 weeks after CT-guided HDR brachytherapy and every 3 months thereafter. Local tumor control (LTC), progression-free survival (PFS), and overall survival (OS) were assessed using Kaplan-Meier curves. The severity of procedure-related complications was classified according to the Society of Interventional Radiology guidelines.

Results: Patients were available for imaging evaluation for a median follow-up of 14.0 months. The median diameter of the largest lesion was 56 mm. Estimated median PFS, LTC, and OS were 7.0 (95% CI 5.0-13.0), 14.0 (95% CI 7.0-21.0), and 20.0 (95% CI 13.0-26.0) months respectively. Actuarial 1-, 2-, and 3-year OS rates were 66%, 41%, and 27%, respectively. Subclassified for VP1, VP2, VP3, and VP4 estimated OS was 38.0 (95% CI 9.0-Not-a-number), 21.5 (95% CI 15.0-25.0), 15.0 (95% CI 7.0-33.0), and 13.0 (95% CI 6.0-34.0) months, respectively. Considering the 64 procedures, we recorded no complications for 49 (76.6%), mild-to-moderate complications for 12 (18.8%), and major complications for 3 (4.7%).

Conclusion: CT-guided HDR brachytherapy was safe and effective for locoregional treatment in patients with advanced HCC due to PVTT, achieving long-lasting local tumor control.

Relevance statement: CT-guided HDR brachytherapy is an option to be considered for locoregional treatment of patients with advanced HCC due to PVTT.

Key points: Evaluation of CT-guided high-dose-rate (HDR) brachytherapy in treating HCC patients with portal vein tumor thrombosis (PVTT). Median OS was 20.0 months ranging between 13.0 and 38.0 months. CT-guided HDR brachytherapy seems to be a safe and effective treatment option in HCC patients with PVTT.

Background: Gadolinium-enhanced "sampling perfection with application-optimized contrasts using different flip angle evolution" (SPACE) sequence allows better visualization of brain metastases (BMs) compared to "magnetization-prepared rapid acquisition gradient echo" (MPRAGE). We hypothesize that this better conspicuity leads to high-quality annotation (HAQ), enhancing deep learning (DL) algorithm detection of BMs on MPRAGE images.

Methods: Retrospective contrast-enhanced (gadobutrol 0.1 mmol/kg) SPACE and MPRAGE data of 157 patients with BM were used, either annotated on MPRAGE resulting in normal annotation quality (NAQ) or on coregistered SPACE resulting in HAQ. Multiple DL methods were developed with NAQ or HAQ using either SPACE or MRPAGE images and evaluated on their detection performance using positive predictive value (PPV), sensitivity, and F1 score and on their delineation performance using volumetric Dice similarity coefficient, PPV, and sensitivity on one internal and four additional test datasets (660 patients).

Results: The SPACE-HAQ model reached 0.978 PPV, 0.882 sensitivity, and 0.916 F1-score. The MPRAGE-HAQ reached 0.867, 0.839, and 0.840, the MPRAGE NAQ 0.964, 0.667, and 0.798, respectively (p ≥ 0.157). Relative to MPRAGE-NAQ, the MPRAGE-HAQ F1-score detection increased on all additional test datasets by 2.5-9.6 points (p < 0.016) and sensitivity improved on three datasets by 4.6-8.5 points (p < 0.001). Moreover, volumetric instance sensitivity improved by 3.6-7.6 points (p < 0.001).

Conclusion: HAQ improves DL methods without specialized imaging during application time. HAQ alone achieves about 40% of the performance improvements seen with SPACE images as input, allowing for fast and accurate, fully automated detection of small (< 1 cm) BMs.

Relevance statement: Training with higher-quality annotations, created using the SPACE sequence, improves the detection and delineation sensitivity of DL methods for the detection of brain metastases (BMs)on MPRAGE images. This MRI cross-technique transfer learning is a promising way to increase diagnostic performance.

Key points: Delineating small BMs on SPACE MRI sequence results in higher quality annotations than on MPRAGE sequence due to enhanced conspicuity. Leveraging cross-technique ground truth annotations during training improved the accuracy of DL models in detecting and segmenting BMs. Cross-technique annotation may enhance DL models by integrating benefits from specialized, time-intensive MRI sequences while not relying on them. Further validation in prospective studies is needed.

Background: A variety of animal models has been developed for research on atherosclerosis and neointimal hyperplasia. While small animal models contain limits for translational research, we aimed to develop an atherosclerosis model with lumen-narrowing plaques to foster basic research in vascular biology, the development of new angioplasty devices, and vessel wall imaging approaches.

Methods: Endothelial denudation was performed via a minimally invasive approach through the auricular artery, followed by stent-retriever mediated endothelial injury in New Zealand White rabbits (n = 10). Along with a high-fat diet, the rabbits developed lumen-narrowing atherosclerosis and neointimal hyperplasia of the iliac arteries within a 6-week period after mechanical injury. The stent-retriever method was compared with a conventional rabbit model (n = 10) using balloon denudation via surgical access, and both models were analyzed with a particular focus on animal welfare. Fisher's exact, Mann-Whitney U, and unpaired t-tests were used.

Results: The average time for the entire procedure was 62 min for the balloon group and 31 min for the stent-retriever group (p < 0.001). The stent-retriever model resulted in less periprocedural morbidity (including expenditure, intubation time, anesthetics, and end-tidal CO₂ level) and mortality (40% mortality in the conventional group compared to 0% in the stent-retriever model, p = 0.011), while generating lumen-narrowing atherosclerotic lesions with key features as compared to humans as revealed by time-of-flight magnetic resonance imaging and histology.

Conclusion: We developed a minimally invasive model of iliac atherosclerosis with high reproducibility and improved animal welfare for translational research.

Relevance statement: This advanced rabbit model could allow for translational research in atherosclerosis, including pharmacological investigations as well as research on interventional angioplasty procedures.

Key points: Rabbit models show similar lipid metabolism as humans. Stent-retriever mediated endothelial denudation causes neointimal hyperplasia and lumen narrowing. This minimal invasive model allows for clinical translation, including pharmacological investigations and vessel wall imaging.