Investigative Radiology最新文献

The next-generation, high relaxivity, gadolinium-based contrast agents (GBCAs) are discussed, together with new studies of safety, improvements in MR technique, and the ongoing development of additional agents. It is likely that the next generation agents, gadopiclenol and gadoquatrane, will largely replace the current standards, the macrocyclic gadolinium chelates, despite the excellent safety profile and very high stability of the latter. In the Group of Seven (G7) nations, which includes Canada, France, Germany, Italy, Japan, the United Kingdom and the United States, use of the linear gadolinium chelates has largely ceased, due to concerns regarding their relative instability as compared to the macrocyclic agents and the deposition of gadolinium that occurs in many tissues, including brain and bone, following their injection. Manganese-based compounds are once again being investigated, a field largely untouched since the initial development of clinical MR contrast media in the 1980s. Their potential impact on clinical imaging is, however, unclear. New information continues to emerge regarding differences in stability of the gadolinium-based agents. Artificial intelligence and deep learning techniques are maturing and are discussed briefly, given their potential and recent clinical application involving MR contrast media.

Objective: Contrast-enhanced ultrasound (CEUS) can be used to effectively monitor hepatocellular carcinoma (HCC) treatment response to percutaneous ablation and transarterial chemoembolization. Here, we performed a supplementary analysis of a prospective study to evaluate HCC participants treated with yttrium-90 transarterial radioembolization (Y90-TARE). We evaluated the utility of quantifiable parameters obtained from CEUS up to 2 weeks posttreatment for predicting treatment response compared with the standard of care cross-sectional imaging performed 2 to 6 months posttreatment (reference standard).

Materials and methods: In this IRB-approved, prospective clinical trial, participants with HCC scheduled for Y90-TARE underwent 3 CEUS sessions. These sessions occurred 1 to 4 hours post-Y90-TARE, 1 week, and 2 weeks posttreatment. Each CEUS examination involved a 10-minute infusion of Optison (GE HealthCare) using an Acuson Sequoia 2.0 or a HELX S3000 scanner (Siemens Healthineers) with 6C1 transducer. During each CEUS examination, flash-replenishment sequences were performed at the tumor midline for CEUS replenishment imaging. Changes between baseline and 1 or 2 weeks were used for quantitative analyses. Fractional tumor vascularity (FTV in %), perfusion (in mL/s*mg), peak enhancement (au), and time to peak (TTP in seconds) were calculated offline using Matlab (MathWorks) to quantitatively evaluate TARE response. Two abdominal radiologists read the reference standard MRI or CT obtained post-Y90-TARE and characterized the tumor as nonviable (complete response) or viable (partial response/stable disease). Unpaired t tests were performed to evaluate differences in nonviable versus viable disease. ROC analysis and logistic regression were evaluated to determine diagnostic performance and disease prediction.

Results: Final analysis included 38 participants. Of these, 22 had nonviable disease (58%, 22/38) and 16 had viable disease (42%, 16/38). FTV showed a difference between nonviable and viable tumors at 2 weeks post-Y90-TARE (38% ± 24% vs 62% ± 28%, P = 0.008). In addition, there was a statistically significant difference in the change in FTV from immediately post-Y90-TARE to 2 weeks after treatment between participants with viable and nonviable disease (41% ± 31% vs 11% ± 26%, P = 0.006). No significant difference was found between viable and nonviable disease across examinations for any of the other variables (P > 0.13).

Conclusions: Quantitative CEUS appears to provide an early indicator of treatment response ∼2 weeks post-Y90-TARE.

Background: Functional imaging of the kidney in pediatric patients is typically performed using contrast-enhanced MR urography (MRU) or nuclear scintigraphy, both of which require either gadolinium-based contrast agents or ionizing radiation. Furosemide, a loop diuretic routinely used in both modalities to stimulate urinary flow, acutely increases tubular fluid volume. These changes in renal water content can be detected by MRI-based quantitative T2 mapping, which may provide a contrast- and radiation-free alternative for evaluating kidney function.

Objective: To assess renal T2 relaxation time changes following intravenous furosemide administration as a surrogate marker for differential renal function (DRF) in pediatric MRU.

Materials and methods: In this prospective single-center study (June 2024 to March 2025), pediatric patients undergoing clinically indicated MRU received additional dynamic T2 mapping during furosemide administration using a respiratory-triggered gradient-and-spin-echo (GraSE) sequence. Two readers independently assessed T2 relaxation time changes. DRF was derived from the slope of the T2 increase (SlopeDRF) as well as from pre-T2 to post-T2 differences, expressed as each kidney's relative contribution to total function. These measures were compared with contrast-enhanced, Patlak-derived DRF (pDRF) using Pearson correlation and Bland-Altman analysis. Interreader agreement was assessed with the intraclass correlation coefficient (ICC).

Results: Thirty-two patients (16 males; median age: 7 y, IQR: 0 to 11) were included. Renal parenchymal T2 relaxation times increased significantly after furosemide administration (pre: 118.4 ms, IQR: 110.8 to 124.4; post: 134.8 ms, IQR: 126.9 to 141.3; P < 0.001). SlopeDRF correlated strongly with pDRF (r = 0.81), and T2-difference DRF also demonstrated strong correlation with pDRF (r = 0.80). Interreader agreement for DRF was excellent (ICC = 0.94).

Conclusion: Dynamic renal T2 mapping after intravenous furosemide administration shows strong correlation with Patlak-derived DRF from contrast-enhanced MRU and may provide a noninvasive, contrast- and radiation-free method for quantifying differential renal function in children.

Objectives: Effective dose management in computed tomography is impeded by 2 key operational challenges: error-prone manual protocol mapping and the high volume of nonactionable alerts from fixed diagnostic reference levels (DRLs). This "alert fatigue" creates a risk of overlooking clinically significant dose deviations. This study aimed to develop and evaluate a novel artificial intelligence (AI)-assisted framework to automate scan classification and provide a patient-specific context for dose assessment.

Materials and methods: This retrospective study analyzed 2955 CT irradiation events. A processing pipeline was developed that first performs automated body segmentation using a deep learning model. A random forest classifier was then trained on the resulting organ volumes to identify 15 distinct scan regions. For 4 common examination types, linear regression models were established to predict the CT dose index (CTDIvol) based on the patient's mean cross-sectional water-equivalent area. Cases were identified as statistical outliers if the absolute standardized residual was >2. The number of these outliers was compared with the number of conventional DRL exceedances.

Results: The automated scan region classifier achieved high accuracy, with a macro-averaged F1 score of 93.8% on the hold-out test set. The regression models demonstrated a clear linear correlation between patient anatomy and CTDIvol (r = 0.56 to 0.79). Crucially, the patient-specific models identified substantially fewer cases for review (60 statistical outliers) compared with the standard DRL-based method (170 exceedances). Manual analysis confirmed that all flagged cases were clinically justified.

Conclusions: Our findings validate that an AI-assisted, patient-centered framework is a highly effective strategy for dose management. By shifting the paradigm from rigid, population-based thresholds to a dynamic, patient-specific assessment, our approach provides a more effective method for identifying potential dose deviations while substantially reducing the burden of nonactionable alerts. This work charts a course towards a new standard of radiation dose monitoring, advancing the field in the direction of a more efficient and reliable form of personalized dose monitoring.

Objectives: To propose simultaneous acquisition of free-breathing, noncontrast-enhanced 3D perfusion-weighted (QW) and ventilation-weighted (VW) maps using 3D ultrashort echo-time (UTE) magnetic resonance imaging (MRI).

Materials and methods: This prospective study included 1 healthy volunteer (25 years; female) and 5 patients (65 ± 10 y; 1 female) with diffuse pulmonary diseases [2 chronic obstructive pulmonary disease (COPD), 2 interstitial lung disease (ILD), 1 asthma], conducted between January 2022 and March 2024. Three-dimensional QW and VW maps were obtained through retrospective cardiac and respiratory gating using 3D UTE MRI on a 3T clinical scanner (Magnetom Prisma; Siemens Healthineers). QW maps were generated by voxel-wise subtraction between maximum and minimum values of 8 cardiac phase-resolved images at end-expiration, and VW maps by subtraction between end-inspiration and end-expiration images. Validation of QW maps involved: (1) assessment of coefficient of variation (CV) across 12 lung segments compared with SPECT, (2) structural similarity index measure (SSIM) analysis compared with SPECT, and (3) evaluation of anteroposterior gravity-dependence by 1D coronal slice profiles. Repeatability was tested in one healthy subject with multiple scans on separate days. In patients, regional perfusion was assessed in lesions identified on CT, and V/Q match or mismatch was evaluated in asthma and emphysema-predominant COPD. Statistical analysis included SSIM and Mann-Whitney U tests (P < 0.05).

Results: UTE MRI-based QW and VW maps showed high similarity with corresponding SPECT maps [SSIM: 0.86 (QW), 0.87 (VW); P >0.05 for CV across 12 lung segments]. Both maps demonstrated gravity-dependence with high correlation to SPECT (correlation coefficient: QW = 0.91, VW = 0.96). QW maps show reduced perfusion in emphysema regions and increased perfusion in regions with consolidation, ground-glass opacity (GGO), and inflammation around fibrotic cysts. Comparing asthma and emphysema-predominant COPD, QW and VW maps demonstrated V/Q mismatch in asthma but matched defects in COPD.

Conclusions: Simultaneous noncontrast-enhanced 3D UTE MRI effectively provides reliable regional perfusion and ventilation information for pulmonary disease evaluation without exposure to ionizing radiation. By providing perfusion and ventilation information simultaneously, the proposed method can help to provide precise and comprehensive functional assessment of pulmonary diseases, including differentiation of pathophysiological conditions and improved evaluation of disease severity and prognosis.

Objectives: To explore magnetic resonance imaging (MRI) and gallium-68 (68Ga)-DOTATATE positron emission tomography (PET) performance in the assessment of neuroendocrine liver metastases (NELMs) on a per-lesion basis, with particular attention to the contribution of individual MRI sequences and assessment of other factors that might influence their detection.

Materials and methods: This observational retrospective study included patients with histologically confirmed neuroendocrine tumors who underwent both contrast-enhanced MRI and 68Ga-DOTATATE PET within 12 weeks between August 2017 and December 2023. Three readers in consensus assessed individual MRI sequences [diffusion-weighted imaging (DWI), dynamic contrast-enhanced imaging (DCE), and hepatobiliary phase (HBP) imaging when available], entire MRI data set, and PET in random order. The reference standard was histopathology or follow-up imaging. Diagnostic performance metrics were calculated using generalized estimating equations with Bonferroni correction. Correlations were assessed using Pearson correlation coefficients.

Results: A total of 1249 lesions, comprising 1050 metastases, were analyzed in 60 patients (mean age: 64.9±11.5 years; 56.7% male). Compared with PET, MRI demonstrated superior sensitivity (93% vs. 59%, P<0.001) and accuracy (93% vs. 63%, P<0.001), with DWI and HBP providing the highest sensitivity (89% and 92%). Size-stratified analysis showed that MRI outperformed PET, particularly for metastases <5 mm (81.6% vs. 19.7%) and 5 to 10 mm (96.1% vs. 61.8%) (P<0.001). Arterial enhancement and portal venous washout were present in 67.8% and 23.7% of metastases, respectively, with only portal venous washout showing size dependence (11.9% in <5 mm to 55.6% in >20 mm lesions, P<0.01). PET-negative metastases were smaller than PET-positives (5.0 vs. 8.0 mm, P=0.001), with lesion size correlating with maximum standardized uptake values and normalized uptake ratios (r=0.54 to 0.59, P<0.001).

Conclusions: MRI outperformed 68Ga-DOTATATE PET in detecting NELMs, with DWI and HBP providing particularly high sensitivity for small metastases.

Objectives: Photon-counting detector (PCD)-CT may improve noninvasive assessment of patients with peripheral artery disease (PAD), yet ideal conditions to unlock its full potential remain unexplored. Hence, this study aims to evaluate the effect of isotropic voxel spacing on image quality and performance in spectral ultrahigh-resolution (UHR) PCD-CT of lower limb CT-angiography (CTA).

Materials and methods: In this IRB-approved post hoc analysis of a prospective study cohort, consecutive patients with PAD underwent lower limb CTA between November 2024 and April 2025 using a dual-source PCD-CT system in spectral-UHR mode (collimation: 120×0.2 mm). Reconstructions included down-sampled images (DS, 0.8 mm section thickness), virtual monoenergetic images at 40 keV (0.4 mm), polychromatic UHR images (0.2 mm), iodine maps (IM, 0.4 mm), and, furthermore, focused per-extremity UHR and IM reconstructions with isotropic voxel spacing (UHRfocused and IMfocused). Two readers assessed image quality in consensus using a 4-point Likert scale (4: "excellent"). In the below-knee arteries with calcified stenosis, perpendicular attenuation profiles were used to calculate full width at half maximum for lumen (FWHMlumen) and plaque (FWHMplaque). Where available, diagnostic performance was evaluated against digital subtraction angiography for ≥50% stenosis.

Results: A total of 59 patients, mean age: 64.6 ± 13.5 years; 40 men (68%), with 111 extremities were included. DS yielded the lowest image quality (median: 2 [2-2]), while UHRfocused scored highest (median: 4,[4-4] P<0.001). UHRfocused and IMfocused achieved the highest lumen visibility (FWHMlumen, UHR: 1.68±0.76; IM: 1.70±0.76) and lowest blooming (FWHMplaque, UHR: 1.01±0.28; IM: 0.98±0.27), indicating superior anatomic resolution, while DS images were prone to blooming artifacts (FWHMlumen: 0.60±0.78; FWHMplaque: 2.11±0.60). UHRfocused and IMfocused both yielded sensitivity of 93% (95% CI: 77%-99%), while UHRfocused demonstrated the highest accuracy of 94% (95% CI: 83%-99%) per segment (n=50).

Conclusions: UHR PCD-CT with focused, per-extremity reconstruction using isotropic voxel spacing enhances image quality, improves lumen and plaque delineation, and yields high diagnostic accuracy in below-knee CTA.

Objective: To evaluate the impact of accelerated, deep learning-based reconstructed T1-weighted VIBE Dixon images on fat-signal fraction (FSF) quantification compared with standard protocols.

Methods: In this prospective single-center study, patients undergoing clinically indicated abdominal MRI underwent 3 T1-weighted VIBE acquisitions on a 1.5 T scanner: a standard sequence and 2 accelerated sequences ("fast" and "ultra-fast"). The accelerated scans employed higher CAIPIRINHA parallel imaging factors, partial Fourier sampling, and deep learning-based image reconstruction. Subsequently, whole-liver FSF was determined using a validated automated liver segmentation tool for in-phase and opposed-phase reconstructions. The quality of segmentation was assessed visually and by comparing liver volumes. Statistical analyses included calculation of mean absolute error and Spearman's correlation for FSF agreement.

Results: Between March 2025 and May 2025, 60 patients (mean age, 63.7 ± 13.9 y; 55% females) were enrolled. Acquisition times were 15 seconds for the standard sequence and 10 and 6 seconds for fast and ultra-fast sequences, respectively. The whole liver segmentations from the fast and ultra-fast sequences showed high correlations (ρ > 0.975, both P < 0.001) with minimal mean absolute error of 1.1% and 1.5% from the standard sequence. The liver fat quantification showed high concordance across protocols, too: median FSF was 2.3% (standard), 2.6% (fast), and 2.4% (ultra-fast), with a mean absolute error <0.6% from standard for both accelerated protocols (all ρ > 0.92, P < 0.001).

Conclusions: Liver fat quantification using highly accelerated, deep learning-enhanced MRI sequences enables reliable assessment of liver fat content with a significant reduction in scan time in low fat-fraction ranges.

Objectives: To evaluate the diagnostic accuracy and quantitative agreement of A-LIKNet (attention-incorporated network for sharing low-rank, image, and k-space information) deep learning (DL)-accelerated 2D cardiac CINE MRI acquired in a single breath-hold, compared with standard multi-breath-hold CINE sequences, for assessing biventricular volumes and function.

Materials and methods: In this single-center study, A-LIKNet DL-reconstructed CINE images were acquired at 3 acceleration factors (8×, 16×, and 24×) in 42 subjects using a single breath-hold protocol. Quantitative parameters, including left and right ventricular end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), ejection fraction (EF), and left ventricle myocardial mass (MM), were derived from standardized segmentation workflows. These were compared against standard multi-breath-hold CINE sequences and tested for agreement using Bland-Altman analysis and linear regression. Image quality was assessed using the coefficient of variation (CoV).

Results: Excellent agreement was observed between A-LIKNet DL-accelerated and standard CINE imaging for EDV, ESV, SV, and EF, with 95% limits of agreement (LoA) falling within predefined equivalence margins for nearly all parameters. No significant proportional bias was detected. Myocardial mass showed wider variability and exceeded equivalence thresholds, likely due to less distinct epicardial borders in higher acceleration. CoV values increased with higher acceleration, reflecting mild degradation in image quality, although segmentation performance remained robust across all levels.

Conclusion: A-LIKNet deep learning accelerated CINE sequences enable rapid and reliable assessment of cardiac function with excellent agreement to standard imaging. From a clinical perspective, image quality remains acceptable up to an acceleration factor of 16×, supporting routine application, while 24× acceleration may be reserved for selected use cases requiring maximal speed.

Objectives: To identify sequences and protocols for minimal metal-induced geometric distortion (MD) for improved spatial accuracy in MRI.

Materials and methods: A 3D lattice phantom containing a stainless-steel bracket or a crown-supported titanium implant was scanned using 6 MRI sequences (TSE, SEMAC, CS-SEMAC, SPACE, VIBE, and research sequence MSVAT-SPACE) in a 3T system. MD was assessed at 9360 crossing points as Euclidean distance using a standardized algorithm. MD was analyzed by total MD, affected volume (AV) at various thresholds, and directional dependency. Statistical analysis was performed by one-way ANOVA.

Results: For the stainless-steel bracket, TSE showed the highest total MD among all sequences (2187±297 mm, P<0.01) and maximum displacement (>4 mm), with 467 mL AV at MD>0.5 mm. CS-SEMAC and SEMAC yielded the lowest MD among all sequences (469±75 mm and 502±154 mm, P<0.01) and the smallest AV (55 mL and 45 mL) at MD>0.5 mm. 3D sequences exhibited intermediate performance with no significant difference (MSVAT-SPACE/VIBE/SPACE: 1569±204 mm/1137±71 mm/1513±143 mm; P>0.08). For the crown-supported titanium implant, all sequences showed reduced MD (<440 mm) and AV (<71 mL at MD>0.5 mm), while VIBE yielded a comparable AV (65 mL) but the highest MD (615 mm). MD was direction-dependent, particularly for the stainless-steel bracket, being highest along frequency-encoding direction (P<0.002); TSE also showed significantly higher MD in slice direction (P=0.0071), while distortions in phase direction were consistently lower.

Conclusions: Susceptibility artifact reduction sequences, particularly SEMAC and CS-SEMAC, effectively reduce total-MD by 79% and AV by 90%. Distortion varies by encoding direction and is most severe along the frequency-encoding axis, highlighting the importance of sequence and parameter selection for accurate MRI near metal implants.