Investigative Radiology最新文献

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.

Objectives: The aim of this study is to validate a 3-material decomposition algorithm for distinguishing between 2 contrast media (CM) (iodine-based and tungsten-based) and water in vivo using a commercial photon-counting CT (PCCT) unit, able to acquire 4 energy thresholds simultaneously.

Materials and methods: Six healthy rats were imaged during different CM distribution phases with both iodine-based and tungsten-based CM present in the animals, one administered orally and one intravenously. Material decomposition was used to compute quantitative contrast maps, virtual noncontrast (VNC) maps, and virtual monoenergetic images (VMI). The mean enhancement in CM-filled regions and in CM-free muscle was measured. This prospective preclinical study was conducted in accordance with the German Animal Welfare Act guidelines and with the approval of the local state animal welfare committee.

Results: Iodine-filled regions were exclusively enhanced (P<0.001) in the iodine map. Tungsten-filled regions were exclusively enhanced (P<0.001) in the tungsten map. VNC maps of a 3-material decomposition received no additional enhancement by CM. VMI, incorporating both iodine and tungsten CM, of different energy levels indicated the K-edge of tungsten.

Conclusions: This study successfully demonstrated the capability of PCCT combined with material decomposition to delineate 2 CM and water in rats. The contrast dynamics of the 2 CM in the vessels (aorta and vena cava) and intestines were successfully reproduced in the CM maps. VNC maps may omit the need for CT scans before contrast administration. VMI revealed distinct energy-dependent attenuation profiles of the given materials.

Objectives: The kidney plays a vital role in eliminating gadolinium-based contrast agents (GBCAs), and renal function may contribute to various GBCA-associated adverse drug reactions (ADRs), particularly acute kidney injury (AKI). The objective of the study is to investigate whether GBCA administration elevates AKI risk and explore the correlation between renal function and the incidence of GBCA-associated acute ADRs.

Materials and methods: Adult patients who underwent MRI examinations between January 2015 and June 2021 at the inpatient department of a single tertiary general hospital were retrospectively examined. Baseline estimated glomerular filtration rate (eGFR) before MRI examination, serum creatinine levels of the nearest timepoint before and after MRI examinations, and symptoms of GBCA-associated acute ADRs were retrospectively reviewed. AKI was diagnosed based on the Kidney Disease: Improving Global Outcomes guideline. Propensity score matching and inverse probability of treatment weighting were used to adjust for selection bias. The rates of GBCA-associated acute ADRs and AKI were compared using generalized estimating equation (GEE) for total data and randomly sampled one patient-one examination data.

Results: This study included 35,197 MRI examinations with available serum creatinine levels, and AKI was diagnosed in 569 cases (1.62%; 95% CI: 1.48%-1.75%). Logistic regression with GEE after propensity score matching revealed a significantly lower AKI incidence in examinations with GBCA enhancement (OR, 0.59; 95% CI: 0.46-0.77; P < 0.001); this finding was consistent across patient groups with both eGFR of >60 mL/min/1.73 m2 (OR, 0.53; 95% CI: 0.34-0.84; P = 0.007) and eGFR between 30 and 60 mL/min/1.73 m2 (OR, 0.49; 95% CI: 0.32-0.74; P < 0.001). The rates of GBCA-associated acute allergic-like reactions (adjusted OR, 1.01; 95% CI: 1.00-1.02; P = 0.125) and physiological reactions (adjusted OR, 1.00; 95% CI: 0.98-1.02; P = 0.997) showed no significant association with baseline eGFRs.

Conclusions: In this large retrospective study, the administration of GBCAs was not associated with higher rates of AKI, which remained consistent across varying levels of baseline renal function. Furthermore, no significant increase in GBCA-associated acute ADRs was observed in patients with impaired renal function. These findings suggest that GBCA administration is generally well-tolerated across a wide spectrum of renal function, without increasing the risk of AKI or GBCA-associated acute ADRs.

Objective: Coronary computed tomography (CT) allows the assessment of cardiovascular risk by imaging calcified plaques in coronary arteries. Because photon-counting CT (PC-CT) can analyze the effective atomic number (Zeff) of the subject, it is expected to be applied to the analysis of plaque components. The purpose of this study was to investigate the applicability of plaque analysis based on Zeff images with continuous gradation.

Methods: Zeff images were generated from virtual monoenergetic images (VMIs) obtained by PC-CT. Zeff values were derived from the difference between linear attenuation coefficients (μ) at low and high energies using an in-house program. Coronary CT images of 64 plaques in 10 patients were analyzed. The Zeff score, calculated as the sum of Zeff values within the plaque region, was calculated and compared with the conventional Agatston score and mean coronary artery calcium (CAC) score.

Results: The systematic uncertainty of Zeff images was estimated to be ±0.08. The Zeff score of actual patient data showed strong positive correlations with the conventional Agatston and mean CAC scores. The Zeff score uses all voxel data in the plaque area, whereas conventional scores consider only data from voxels with a CT value >130. We found that the conventional scores excluded 39% of the plaque area, and the Zeff score permitted the analysis of low- and high-density plaques.

Conclusions: Zeff imaging was shown to be applicable to plaque analysis that reflects the entire plaque volume. This study demonstrated its technical feasibility as a compositional analysis method using the Zeff image.

Purpose: Accurate target volume delineation is critical for effective stereotactic radiotherapy (SRT) of brain metastases. This study systematically investigates how MRI sequence selection and the time elapsed after contrast agent (CA) administration affect the apparent metastases volumes, with the goal of optimizing MRI protocols for radiation therapy planning.

Materials and methods: A total of 49 patients with 414 brain metastases were included and randomized into 6 groups with varying imaging sequences (MPRAGE, SPACE, and VIBE) and timepoints after CA administration. Lesions smaller than 0.03 cm3 were excluded due to resolution limitations. Lesion volumes were independently assessed by radiology and radiation oncology specialists, and mean values were analyzed. The effects of MRI sequence and time delay on lesion volume were evaluated using t tests, ANOVA, and multiple linear regression.

Results: Both MRI sequence and CA timing significantly influenced measured volumes. On average, SPACE volumes were 20% larger than MPRAGE, and VIBE volumes were 10% larger than SPACE, independent of timing. Lesion volumes increased progressively with time after CA administration at rates of 0.63%, 0.58%, and 0.36% per minute for MPRAGE, SPACE, and VIBE, respectively. Smaller lesions (<1 cm3) showed greater relative intersequence differences, primarily due to variations in visible lesion borders.

Conclusions: Both MRI sequence choice and imaging time after CA administration significantly affect the apparent volume of brain metastases in SRT planning. Although SPACE and VIBE sequences enhance small lesion detection, they may also increase border blurring and inter-rater variability. Standardizing protocols to account for these factors is essential for improving delineation accuracy, reducing toxicity risk, and optimizing SRT outcomes.

Objectives: Manual field-of-view (FoV) prescription in whole-body magnetic resonance imaging (WB-MRI) is vital for ensuring comprehensive anatomic coverage and minimising artifacts, thereby enhancing image quality. However, this procedure is time-consuming, subject to operator variability, and adversely impacts both patient comfort and workflow efficiency. To overcome these limitations, an automated system was developed and evaluated that prescribes multiple consecutive FoV stations for WB-MRI using deep-learning (DL)-based three-dimensional anatomic segmentations.

Materials and methods: A total of 374 patients (mean age: 50.5 ± 18.2 y; 52% females) who underwent WB-MRI, including T2-weighted Half-Fourier acquisition single-shot turbo spin-echo (T2-HASTE) and fast whole-body localizer (FWBL) sequences acquired during continuous table movement on a 3T MRI system, were retrospectively collected between March 2012 and January 2025. An external cohort of 10 patients, acquired on two 1.5T scanners, was utilized for generalizability testing. Complementary nnUNet-v2 models were fine-tuned to segment tissue compartments, organs, and a whole-body (WB) outline on FWBL images. From these predicted segmentations, 5 consecutive FoVs (head/neck, thorax, liver, pelvis, and spine) were generated. Segmentation accuracy was quantified by Sørensen-Dice coefficients (DSC), Precision (P), Recall (R), and Specificity (S). Clinical utility was assessed on 30 test cases by 4 blinded experts using Likert scores and a 4-way ranking against 3 radiographer prescriptions. Interrater reliability and statistical comparisons were employed using the intraclass correlation coefficient (ICC), Kendall W, Friedman, and Wilcoxon signed-rank tests.

Results: Mean DSCs were 0.98 for torso (P = 0.98, R = 0.98, S = 1.00), 0.96 for head/neck (P = 0.95, R = 0.96, S = 1.00), 0.94 for abdominal cavity (P = 0.95, R = 0.94, S = 1.00), 0.90 for thoracic cavity (P = 0.90, R = 0.91, S = 1.00), 0.86 for liver (P = 0.85, R = 0.87, S = 1.00), and 0.63 for spinal cord (P = 0.64, R = 0.63, S = 1.00). The clinical utility was evidenced by assessments from 2 expert radiologists and 2 radiographers, with 98.3% and 87.5% of cases rated as clinically acceptable in the internal test data set and the external test data set. Predicted FoVs received the highest ranking in 60% of cases. They placed within the top 2 in 85.8% of cases, outperforming radiographers with 9 and 13 years of experience (P < 0.001) and matching the performance of a radiographer with 20 years of experience.

Conclusions: DL-based three-dimensional anatomic segmentations enable accurate and reliable multistation FoV prescription for WB-MRI, achieving expert-level performance while significantly reducing manual workload. Automated FoV planning has the potential to standardize WB-MRI acquisition, reduce interoperator variability, and enhance workflow effi