Investigative Radiology最新文献

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

Objectives: Cerebral angiography remains the gold standard for the diagnosis and endovascular management of cerebral aneurysms. Three-dimensional rotational angiography (3D-RA) provides superior anatomic resolution compared with conventional 2D imaging; however, it is associated with relatively high radiation exposure, raising specific concerns regarding the ocular lens dose. This study aims to evaluate the potential of copper (Cu) filtration for reducing radiation dose in 3D-RA.

Materials and methods: Forty subsequent patients undergoing endovascular treatment of unruptured cerebral aneurysms were included. All received 3D-RA using the ARTIS icono angiography system (Siemens Healthineers). In 20 patients, standard hardware with a 0.8 mm aluminum (Al) filter was applied; in the subsequent 20 patients, the Al filter was replaced by a 0.1 mm Cu filter. Image quality was assessed quantitatively through contrast-to-noise ratio (CNR) and qualitatively using a 5-point scale.

Results: There were no differences in image quality between the two groups in the 3D neurovascular native/contrast images, both quantitatively (eg, mean CNR ± SD, Al: 20.72 ± 1.82 vs Cu: 20.66 ± 1.54; P = 0.93) and qualitatively (mean score ± SD, Al: 4.55 ± 0.54 vs Cu: 4.63 ± 0.46; P = 0.75), with excellent image quality achieved in both groups. Total radiation dose was lower with the Cu filter (e.g., mGy ± SD, Al: 110.63 ± 10.75 vs Cu: 68.70 ± 6.03; Gy·cm2 ± SD, Al: 6.26 ± 1.57 vs 3.35 ± 0.67, P < 0.001 respectively), corresponding to a dose reduction of 38% (entrance-skin dose) and 46% (dose-area product).

Conclusion: The use of a copper filter in cerebral 3D-RA substantially reduces radiation dose without compromising diagnostic quality, representing a practical advancement in patient safety in 3D-RA. The method integrates seamlessly into existing protocols and can be readily implemented in clinical practice.

Background: Photon-counting detector computed tomography (PCD CT) offers higher dose efficiency than conventional energy-integrating detector CT (EID CT), which is particularly beneficial for children. Broad evidence is missing whether frequently acquired pediatric low-dose lung imaging can be further improved using PCD CT.

Objective: To compare radiation exposure, quantitative and qualitative image quality of pediatric low-dose chest PCD CT versus EID CT examinations.

Methods: Unenhanced low-dose chest PCD CT and EID CT examinations acquired for clinical indications were retrospectively compared. Cohorts were matched by water-equivalent diameter (Dw) and age (n=44 each; median age 6.3 y PCD CT vs. 7.4 y EID CT). Radiation exposure was analyzed by volume CT dose index (CTDIvol), dose length product (DLP), and size-specific dose estimate (SSDE). Quantitative image quality assessment featured the placement of regions of interest (ROIs) in the lung, heart, and liver for the extraction of mean attenuation, noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and figures of merit (FOMs). Qualitative image quality was evaluated by 3 readers using Likert scales and additional direct comparisons in a blinded manner.

Results: Weight, height, and body mass index (BMI) were not significantly different between the 2 cohorts (P>0.05). PCD CT examinations showed lower median CTDIvol (0.27 vs. 0.39 mGy, P<0.0001), DLP (6.71 vs. 8.75 mGy*cm, P<0.0001), and SSDE (0.55 vs. 0.83 mGy, P<0.0001) compared with EID CT. Mean attenuation [-797.76 vs. -772.50 Hounsfield units (HU), P=0.51], noise (17.82 vs. 17.69 HU, P=0.73), SNR (-46.10 vs. -45.40, P=0.63), and CNR (39.26 vs. 39.76, P=0.68) of lung parenchyma were not significantly different; respective dose efficiency expressed by FOM was higher in PCD CT compared with EID CT (mean 8030 vs. 5482 mGy-1, P<0.0001). Qualitative rating showed equal and overall excellent scores for both cohorts.

Conclusions: PCD CT enables pediatric low-dose chest imaging with lower radiation exposure at similar image quality compared with EID CT.

Objectives: MR elastography (MRE) offers valuable mechanical tissue characterization for clinical diagnosis. However, conventional single-driver, single-frequency MRE systems are often limited by insufficient coverage of deep-seated organs like the pancreas. This study investigates whether multiplex MRE using multiple drivers and vibration frequencies can overcome these limitations.

Materials and methods: This prospective study used single-shot spin-echo MRE in 18 healthy volunteers (mean age 30±8 y) targeting the liver, pancreas, kidneys, and spleen. Each healthy volunteer underwent 16 MRE examinations with different sets of 4 vibration frequencies in the range of 30 to 60 Hz and 4 driver combinations, and an additional null experiment without vibrations. In addition, a cohort of 14 patients with pancreatic ductal adenocarcinoma (PDAC, mean age 57±15 y) were retrospectively assessed. The quality of shear-wave fields and stiffness maps were assessed in terms of displacement amplitudes and image sharpness.

Results: In healthy volunteers, abdominal coverage with displacement amplitudes above the pre-determined noise level of 4 µm varied among the MRE investigated: 24.2% (0.0% to 56.2%, single-driver at 60 Hz), 66.9% (24.8% to 97.7%, single-driver at 30 to 60 Hz), 70.2% (0.0% to 92.5%, multi-driver at 60 Hz), and 99.9% (89.4% to 100%, multi-driver at 30 to 60 Hz). In the pancreas, more than 60% coverage was achieved in all subjects using 4 drivers and multiple frequencies. This was achieved in only 2 of 18 subjects (11%) using single-driver/single-frequency MRE. Superficial organs were adequately assessed with all configurations. In patients with PDAC, multi-driver MRE at 30 to 60 Hz achieved 99.1% (91.4% to 100%) coverage of the pancreas and 96.3% (63.1% to 100%) abdominal coverage, suggesting that tomographic stiffness mapping is clinically feasible.

Conclusion: MRE with at least 4 drivers and multiple vibration frequencies in the range of 30 to 60 Hz enables tomographic mapping of tissue stiffness across the entire abdomen, including the pancreas. Our results thus indicate that multiplex MRE is a promising approach for generating detailed images of abdominal stiffness that can improve clinical diagnosis of abdominal and pancreatic diseases.

Objectives: The aim of this study was to evaluate the feasibility and reproducibility of a novel deep learning (DL)-based coronary plaque quantification tool with automatic case preparation in patients undergoing ultra-high resolution (UHR) photon-counting detector CT coronary angiography (CCTA), and to assess the influence of temporal resolution on plaque quantification.

Materials and methods: In this retrospective single-center study, 45 patients undergoing clinically indicated UHR CCTA were included. In each scan, 2 image data sets were reconstructed: one in the dual-source mode with 66 ms temporal resolution and one simulating a single-source mode with 125 ms temporal resolution. A novel, DL-based algorithm for fully automated coronary segmentation and intensity-based plaque quantification was applied to both data sets in each patient. Plaque volume quantification was performed at the vessel-level for the entire left anterior descending artery (LAD), left circumflex artery (CX), and right coronary artery (RCA), as well as at the lesion-level for the largest coronary plaque in each vessel. Diameter stenosis grade was quantified for the coronary lesion with the greatest longitudinal extent in each vessel. To assess reproducibility, the algorithm was rerun 3 times in 10 randomly selected patients, and all outputs were visually reviewed and confirmed by an expert reader. Paired Wilcoxon signed-rank tests with Benjamini-Hochberg correction were used for statistical comparisons.

Results: One hundred nineteen out of 135 (88.1%) coronary arteries showed atherosclerotic plaques and were included in the analysis. In the reproducibility analysis, repeated runs of the algorithm yielded identical results across all plaque and lumen measurements (P > 0.999). All outputs were confirmed to be anatomically correct, visually consistent, and did not require manual correction. At the vessel level, total plaque volumes were higher in the 125 ms reconstructions compared with the 66 ms reconstructions in 28 of 45 patients (62%), with both calcified and noncalcified plaque volumes being higher in 32 (71%) and 28 (62%) patients, respectively. Total plaque volumes in the LAD, CX, and RCA were significantly higher in the 125 ms reconstructions (681.3 vs. 647.8  mm3, P < 0.05). At the lesion level, total plaque volumes were higher in the 125 ms reconstructions in 44 of 45 patients (98%; 447.3 vs. 414.9  mm3, P < 0.001), with both calcified and noncalcified plaque volumes being higher in 42 of 45 patients (93%). The median diameter stenosis grades for all vessels were significantly higher in the 125 ms reconstructions (35.4% vs. 28.1%, P < 0.01).

Conclusions: This study evaluated a novel DL-based tool with automatic case preparation for quantitative coronary plaque in UHR CCTA data sets. The algorithm was technically robust and reproducible, delivering anatomically consistent outputs

The recent advent of anti-amyloid-β monoclonal antibodies has introduced new demands for MRI-based screening of amyloid-related imaging abnormalities, particularly the hemorrhage subtype (ARIA-H). In this editorial, we discuss the study by Loftus and colleagues, which evaluates the diagnostic performance of echo-planar accelerated gradient-recalled echo (GRE) and susceptibility-weighted imaging (SWI) sequences for ARIA-H screening. Their results demonstrate that significant scan time reductions-up to 86%-can be achieved without substantial loss in diagnostic accuracy, particularly for accelerated GRE. These findings align with recently issued MRI guidelines and offer practical solutions for improving workflow efficiency in Alzheimer's care. However, challenges remain in terms of inter-rater variability and image quality, especially with accelerated SWI. We also highlight the emerging role of artificial intelligence-assisted analysis and the importance of reproducibility and data sharing in advancing clinical implementation. Balancing speed and sensitivity remains a central theme in optimizing imaging strategies for antiamyloid therapeutic protocols.

Objectives: Some renal masses remain indeterminate after both contrast-enhanced CT (CE-CT) and contrast-enhanced MRI (CE-MRI), with uncertainty concerning their cystic or solid composition, raising an issue in patient management. The aim of this article was to assess the diagnostic performance of contrast-enhanced ultrasound (CEUS) in the characterization of indeterminate renal masses in this specific context.

Materials and methods: Starting from CEUS examinations investigating renal masses, we retrospectively identified patients with renal masses that remained indeterminate after both unenhanced and enhanced CT and MRI. CEUS examinations were performed in a single center between February 2009 and September 2019. Cross-sectional imaging and nonenhanced US images were individually reviewed to confirm each lesion's indeterminate nature. CEUS was performed to differentiate solid and cystic lesions. CEUS findings were correlated to pathologic analysis or follow-up (minimum 3 y) to assess diagnostic performance. Inter-reader agreement was also analyzed.

Results: Sixty-four patients [mean age: 60.5±12.1 (SD), 49 men; 15 women] with 73 indeterminate renal masses (median: 24 mm, range: 10 to 122 mm) were identified. CEUS enabled further characterization of 71 out of the 73 indeterminate lesions (97.3%). To establish the solid nature of a renal mass, CEUS had a sensitivity of 81.3% (95% CI: 54.5%-95.9%), a specificity of 98.2% (95% CI: 90.3%-99.9%), a positive predictive value of 92.9% (95% CI: 64.8%-98.9%), a negative predictive value of 94.7% (95% CI: 86.6%-98.0%), and an accuracy of 94.4% (95% CI: 86.2%-98.4%), with excellent inter-reader agreement.

Conclusion: CEUS can accurately distinguish solid from cystic lesions in renal masses indeterminate after CE-CT and CE-MRI.

Objective: To investigate the objective performance and subjective image quality of lower extremity CT angiography (CTA) in peripheral artery disease (PAD) through comparison of the first-generation photon-counting CT (PCCT) technology and the third-generation dual source energy-integrating detector CT (DECT) technology.

Materials and methods: Patients who underwent a CTA either on a PCCT or on a DECT were included in this retrospective analysis. All included patients received a digital subtraction angiography (DSA) as reference standard for stenosis grading. Virtual monoenergetic image data sets were reconstructed at 40, 45, 50, 55, and 60 keV. The noise, the signal-to-noise ratio (SNR), and the contrast-to-noise ratio (CNR) of vascular structures, as well as the subjective image quality using a standardized 5-point Likert Scale, were determined. Finally, the sensitivity, specificity, and accuracy of the stenotic disease detection for either technology (DECT and PCCT) were analyzed.

Results: PCCT angiography was performed in 50 PAD patients (31 males, mean age 76.16 ± 10.26), and DECT angiography was pursued in 50 PAD patients as well (29 males, mean age 74.0 ± 14.26). PCCT reached significantly higher CNR compared with DECT in all assessed arterial territories [eg, 27.84 (IQR: 22.57 to 34.66) vs 17.25 (IQR: 12.12 to 23.71), at the iliac arterial vasculature at 40 keV, P < 0.001]. Image quality and contrast were rated significantly higher for PCCT compared with DECT [eg, mean vessel contrast 5 (IQR: 4 to 5) vs 4 (IQR: 4 to 4)], at the calf arterial vasculature at 40 keV, P <0.001. Overall sensitivity, specificity, and accuracy for PCCT were 96%, 97%, and 97%, respectively, in comparison to 93%, 96%, and 94%, respectively, for DECT image data sets at 55 keV.

Conclusion: PCCT offers superior objective performance and better subjective image quality compared with DECT. Hence, PCCT angiography is improving cross-sectional PAD imaging.