Investigative Radiology最新文献

Objectives: The aim of this study was to assess the impact of an iterative metal artifact reduction (iMAR) algorithm combined with virtual monoenergetic images (VMIs) for artifact reduction in photon-counting detector computed tomography (PCDCT) during interventions.

Materials and methods: Using an abdominal phantom, we conducted evaluations on the efficacy of iMAR and VMIs for mitigating image artifacts during interventions on a PCDCT. Four different puncture devices were employed under 2 scan modes (QuantumSn at 100 kV, Quantumplus at 140 kV) to simulate various clinical scenarios. Image reconstructions were initially performed without iMAR and subsequently with iMAR settings. The latter was tested with 7 different metal presets for each case. Furthermore, iMAR-reconstructed images were paired with VMIs at energy levels of 70 keV, 110 keV, 150 keV, and 190 keV. Qualitative assessments were conducted to evaluate image quality, artifact expression, and the emergence of new artifacts using a Likert scale. Image quality was rated on a scale of 1 (nondiagnostic) to 5 (excellent), whereas artifact severity was rated from 0 (none) to 5 (massive). Preferences for specific iMAR presets were documented. Quantitative analysis involved calculating Hounsfield unit (HU) differences between artifact-rich and artifact-free tissues.

Results: Overall, 96 different scanning series were evaluated. The optimal combination for artifact reduction was found to be iMAR neurocoils with VMIs at 150 keV and 190 keV, showcasing the most substantial reduction in artifacts with a median rating of 1 (standard: 4). VMIs at higher keV levels, such as 190 keV, resulted in reduced image quality, as indicated by a median rating of 3 (compared with 70 keV with a median of 5). Newly emerged artifact expression related to reconstructions varied among intervention devices, with iMAR thoracic coils exhibiting the least extent of artifacts (median: 2) and iMAR neurocoils displaying the most pronounced artifacts (median: 4). Qualitative analysis favored the combination of iMAR neurocoils with VMIs at 70 keV, showcasing the best results. Conversely, quantitative analysis revealed that the combination of iMAR neurocoils with VMIs at 190 keV yielded the best results, with an average artifact expression of 20.06 HU (standard: 167.98 HU; P < 0.0001).

Conclusions: The study underscores a substantial reduction in artifacts associated with intervention devices during PCDCT scans through the synergistic application of VMI and iMAR techniques. Specifically, the combination of VMIs at 70 keV with iMAR neurocoils was preferred, leading to enhanced diagnostic assessability of surrounding tissues and target lesions. The study demonstrates the potential of iMAR and VMIs for PCDCT-guided interventions. These advancements could improve accuracy, safety, efficiency, and patient outcomes in clinical practice.

Objectives: Accurate lymph node (LN) staging is crucial for managing upper abdominal cancers. Ultrasmall superparamagnetic iron oxide (USPIO)-enhanced magnetic resonance imaging effectively distinguishes healthy and metastatic LNs through fat/water and -weighted imaging. However, respiratory motion artifacts complicate detection of abdominal LNs. This study evaluates if a free-breathing radial stack-of-stars acquisition can match or outperform Cartesian reference scans to visualize LNs and depict uptake of USPIO nanoparticles.

Materials and methods: Five volunteers with USPIO and 20 patients without USPIO were scanned using radial stack-of-stars, Cartesian dual-echo, and fat-saturated Cartesian multiecho sequences for fat/water imaging and estimation. Reconstructed images from radial and Cartesian patient data underwent qualitative comparison by 2 radiologists. LNs were identified in all fat/water images, LN short-axis sizes were measured, and relaxation rates were analyzed using linear correlations and Bland-Altman plots.

Results: Radial imaging provided better image quality than the Cartesian reference standard, according to both readers. Substantially, more LNs were identified in radial compared with Cartesian datasets (349 vs 202). Median short-axis diameters showed a significant difference, measuring 2.7 mm (interquartile range [IQR]: 2.7-4.6 mm) for radial images and 4.5 mm (IQR: 3.7-5.6 mm) for Cartesian images ( P < 0.0001). Relaxation rates measured in radial data showed a significant linear correlation with the Cartesian reference (Pearson correlation coefficient: 0.90 with P < 0.0001). Bland-Altman plots indicated a slight bias with a mean difference (MD) of 3.9 s -1 and limits of agreement at MD ± 16.4 s -1 .

Conclusions: This work presents a promising magnetic resonance imaging method to depict upper abdominal LNs and to visualize their USPIO uptake. Instead of multiple Cartesian breath-hold scans, all relevant contrasts and parameters are obtained from a single free-breathing radial acquisition. The proposed method yielded higher image quality and more sensitive detection of small LNs. value analysis showed a strong linear correlation with the reference, albeit with minimal biases.

Objectives: Impaired image quality and long scan times frequently occur in respiratory-triggered sequences in liver magnetic resonance imaging (MRI). We evaluated the impact of an in-bore active breathing guidance (BG) application on image quality and scan time of respiratory-triggered T2-weighted (T2) and diffusion-weighted imaging (DWI) by comparing sequences with standard triggering (T2 S and DWI S ) and with BG (T2 BG and DWI BG ).

Materials and methods: In this prospective study, random patients with clinical indications for liver MRI underwent 3 T MRI with standard and BG acquisitions. The audiovisual BG application received the respiratory signal from the scanner, and animated breathing instructions were displayed using a mirror and screen behind the MRI bore. Prior to the DWI BG and T2 BG acquisition, patients received a short video instruction about MRI with BG. Suitable parameters for desired breathing pattern for T2 BG and DWI BG were set individually for each patient based on the patient's physical respiratory ability (ie, 4 seconds breathing followed by 4.5 seconds breath holding). Artifacts, sharpness, lesion conspicuity, and overall image quality were assessed using a Likert scale from 1 (nondiagnostic) to 5 (excellent). Scan time, apparent contrast-to-noise ratio, and apparent signal-to-noise ratio (aSNR) for all sequences were analyzed. Paired t test and Wilcoxon test were used for statistical analysis.

Results: Thirty-two patients (mean age: 55 ± 13 years, 13 female) were included. T2 BG showed less artifacts (4.5 ± 0.7 vs 4.1 ± 0.8, P < 0.001) and better sharpness, lesion conspicuity, and overall image quality (eg, overall image quality 4.6 ± 0.7 vs 4.4 ± 0.7, P = 0.004) compared with T2 S . DWI BG demonstrated improved image quality in all categories compared with DWI S (eg, overall image quality 4.5 ± 0.5 vs 4.3 ± 0.5, P = 0.005) and less artifacts (4.1 ± 0.5 vs 3.8 ± 0.7, P = 0.007). Scan times of T2 BG (286 ± 23 vs 345 ± 68 seconds, P < 0.001) and DWI BG (160 ± 4 vs 252 ± 70 seconds, P < 0.001) were reduced by 17% and 37%, respectively. aSNR and apparent contrast-to-noise ratio (eg, aSNR: 23.45 ± 11.31 [T2 BG ] vs 25.84 ± 10.76 [T2 S ]; P = 0.079) were similar for both sequences for both approaches.

Conclusions: Active BG for respiratory-triggered liver T2w and DWI sequences led to significant reduction of breathing artifacts, improved image quality, and shorter scan time compared with standard acquisitions.

Purpose: This study documents the gadolinium (Gd) content in urine over time after the administration of a single dose of Gd-based contrast agent (GBCA) in patients diagnosed with Gd deposition disease.

Materials and methods: In this retrospective observational study, 45 subjects with normal renal function who had performed 1 contrast-enhanced magnetic resonance imaging and had a nonprovoked (native) 24-hour urine test for Gd quantification after the examination were evaluated. The GBCA brand and the time interval in days between the GBCA administration and 24-hour urine Gd measurements were recorded. Log-log plot visualization of time points for urine Gd content was obtained.

Results: Time points collected for urine Gd content showed that Gd was above the reference levels for 3 months postinjection. The urinary concentration of Gd was similar for all agents, including linear and macrocyclic. The urinary content decreased in a dog-leg fashion. Gd urine content was substantially elevated at 1 month and decreased to remain above the accepted normal range by 3 months.

Conclusions: Gd is retained in the body and shows demonstrable continued spontaneous elimination in urine for at least several months after administration, including the most stable macrocyclic agents. The Gd elimination pattern shows a logarithmic decrease pattern between 1 and 3 months for all agents, regardless of their structure.

Objectives: Pancreatic diffusion-weighted imaging (DWI) has numerous clinical applications, but conventional single-shot methods suffer from off resonance-induced artifacts like distortion and blurring while cardiovascular motion-induced phase inconsistency leads to quantitative errors and signal loss, limiting its utility. Multishot DWI (msDWI) offers reduced image distortion and blurring relative to single-shot methods but increases sensitivity to motion artifacts. Motion-compensated diffusion-encoding gradients (MCGs) reduce motion artifacts and could improve motion robustness of msDWI but come with the cost of extended echo time, further reducing signal. Thus, a method that combines msDWI with MCGs while minimizing the echo time penalty and maximizing signal would improve pancreatic DWI. In this work, we combine MCGs generated via convex-optimized diffusion encoding (CODE), which reduces the echo time penalty of motion compensation, with deep learning (DL)-based denoising to address residual signal loss. We hypothesize this method will qualitatively and quantitatively improve msDWI of the pancreas.

Materials and methods: This prospective institutional review board-approved study included 22 patients who underwent abdominal MR examinations from August 22, 2022 and May 17, 2023 on 3.0 T scanners. Following informed consent, 2-shot spin-echo echo-planar DWI (b = 0, 800 s/mm 2 ) without (M0) and with (M1) CODE-generated first-order gradient moment nulling was added to their clinical examinations. DL-based denoising was applied to the M1 images (M1 + DL) off-line. ADC maps were reconstructed for all 3 methods. Blinded pair-wise comparisons of b = 800 s/mm 2 images were done by 3 subspecialist radiologists. Five metrics were compared: pancreatic boundary delineation, motion artifacts, signal homogeneity, perceived noise, and diagnostic preference. Regions of interest of the pancreatic head, body, and tail were drawn, and mean ADC values were computed. Repeated analysis of variance and post hoc pairwise t test with Bonferroni correction were used for comparing mean ADC values. Bland-Altman analysis compared mean ADC values. Reader preferences were tabulated and compared using Wilcoxon signed rank test with Bonferroni correction and Fleiss κ.

Results: M1 was significantly preferred over M0 for perceived motion artifacts and signal homogeneity ( P < 0.001). M0 was significantly preferred over M1 for perceived noise ( P < 0.001), but DL-based denoising (M1 + DL) reversed this trend and was significantly favored over M0 ( P < 0.001). ADC measurements from M0 varied between different regions of the pancreas ( P = 0.001), whereas motion correction with M1 and M1 + DL resulted in homogeneous ADC values ( P = 0.24), with values similar to those reported for ssDWI with motion correction. ADC values from M0 were significantly higher than M1 in the head (bias 16.6%; P < 0.0001), body (bias 11.0%

Objective: The aim of this study was to intraindividually compare the conspicuity of focal liver lesions (FLLs) between low- and ultra-low-dose computed tomography (CT) with deep learning reconstruction (DLR) and standard-dose CT with model-based iterative reconstruction (MBIR) from a single CT using dual-split scan in patients with suspected liver metastasis via a noninferiority design.

Materials and methods: This prospective study enrolled participants who met the eligibility criteria at 2 tertiary hospitals in South Korea from June 2022 to January 2023. The criteria included ( a ) being aged between 20 and 85 years and ( b ) having suspected or known liver metastases. Dual-source CT scans were conducted, with the standard radiation dose divided in a 2:1 ratio between tubes A and B (67% and 33%, respectively). The voltage settings of 100/120 kVp were selected based on the participant's body mass index (<30 vs ≥30 kg/m 2 ). For image reconstruction, MBIR was utilized for standard-dose (100%) images, whereas DLR was employed for both low-dose (67%) and ultra-low-dose (33%) images. Three radiologists independently evaluated FLL conspicuity, the probability of metastasis, and subjective image quality using a 5-point Likert scale, in addition to quantitative signal-to-noise and contrast-to-noise ratios. The noninferiority margins were set at -0.5 for conspicuity and -0.1 for detection.

Results: One hundred thirty-three participants (male = 58, mean body mass index = 23.0 ± 3.4 kg/m 2 ) were included in the analysis. The low- and ultra-low- dose had a lower radiation dose than the standard-dose (median CT dose index volume: 3.75, 1.87 vs 5.62 mGy, respectively, in the arterial phase; 3.89, 1.95 vs 5.84 in the portal venous phase, P < 0.001 for all). Median FLL conspicuity was lower in the low- and ultra-low-dose scans compared with the standard-dose (3.0 [interquartile range, IQR: 2.0, 4.0], 3.0 [IQR: 1.0, 4.0] vs 3.0 [IQR: 2.0, 4.0] in the arterial phase; 4.0 [IQR: 1.0, 5.0], 3.0 [IQR: 1.0, 4.0] vs 4.0 [IQR: 2.0, 5.0] in the portal venous phases), yet within the noninferiority margin ( P < 0.001 for all). FLL detection was also lower but remained within the margin (lesion detection rate: 0.772 [95% confidence interval, CI: 0.727, 0.812], 0.754 [0.708, 0.795], respectively) compared with the standard-dose (0.810 [95% CI: 0.770, 0.844]). Sensitivity for liver metastasis differed between the standard- (80.6% [95% CI: 76.0, 84.5]), low-, and ultra-low-doses (75.7% [95% CI: 70.2, 80.5], 73.7 [95% CI: 68.3, 78.5], respectively, P < 0.001 for both), whereas specificity was similar ( P > 0.05).

Conclusions: Low- and ultra-low-dose CT with DLR showed noninferior FLL conspicuity and detection compared with standard-dose CT with MBIR. Caution is needed due to a potential decrease in sensitivity for metastasis ( clinicaltrials.gov/NCT05324046 ).

Objectives: The aim of this study was to investigate the occurrence of motion artifacts and image quality of brain magnetic resonance imaging (MRI) T1-weighted imaging applying 3D motion correction via the Scout Accelerated Motion Estimation and Reduction (SAMER) framework compared with conventional T1-weighted imaging at 1.5 T.

Materials and methods: A preliminary study involving 14 healthy volunteers assessed the impact of the SAMER framework on induced motion during 3 T MRI scans. Participants performed 3 different motion patterns: (1) step up, (2) controlled breathing, and (3) free motion. The patient study included 82 patients who required clinically indicated MRI scans. 3D T1-weighted images (MPRAGE) were acquired at 1.5 T. The MRI data were reconstructed using either regular product reconstruction (non-Moco) or the 3D motion correction SAMER framework (SAMER Moco), resulting in 145 image sequences. For the preliminary and the patient study, 3 experienced radiologists evaluated the image data using a 5-point Likert scale, focusing on overall image quality, artifact presence, diagnostic confidence, delineation of pathology, and image sharpness. Interrater agreement was assessed using Gwet's AC 2 , and an exploratory analysis (non-Moco vs SAMER Moco) was performed.

Results: Compared with non-Moco, the preliminary study demonstrated significant improvements across all imaging parameters and motion patterns with SAMER Moco ( P < 0.001). Odds ratios favoring SAMER Moco were >999.999 for freedom of artifact and overall image quality ( P < 0.0001). Excellent or good ratings for freedom of artifact were 52.4% with SAMER Moco, compared with 21.4% for non-Moco. Similarly, 66.7% of SAMER Moco images were rated excellent or good for overall image quality versus 21.4% for non-Moco. Multireader interrater agreement was excellent across all parameters.The patient study confirmed that SAMER Moco provided significantly superior image quality across all evaluated imaging parameters, particularly in the presence of motion ( P < 0.001). Diagnostic confidence was rated as excellent or good in 95.1% of SAMER Moco cases, compared with 78.1% for non-Moco cases. Similarly, overall image quality was rated as excellent or good in 89.8% of SAMER Moco cases versus 65.9% for non-Moco cases. The odds ratios for diagnostic confidence and for overall image quality were 6.698 and 6.030, respectively, both favoring SAMER Moco ( P < 0.0001). Multireader interrater agreement was excellent across all parameters.

Conclusions: The application of SAMER in T1-weighted imaging datasets is feasible in clinical routine and significantly increases image quality and diagnostic confidence in 1.5 T brain MRI by effectively reducing motion artifacts.

Background: Glymphatic-lymphatic coupling is difficult to visualize in humans.

Purpose: To evaluate the transport from the basal subarachnoid space to lymphatic vessels in the nasal mucosa and in the parasagittal dura, respectively.

Methods: A highly resolved 3D compressed sensing black blood sequence with almost isotropic resolution (0.5 ×0.5 ×0.6 mm3) was acquired in 26 patients before and 2 to 4, 6 to 8, 24 to 48, and 72 to 96 hours after intrathecal injection of 0.5 mL gadobutrol. T1 signal intensities were measured in CSF spaces (perisylvian, above cribriform plate, midsylvian, and parasagittal), in the olfactory bulbs, fila olfactoria, and nasal mucosa, as well as in the cortex, white matter, and parasagittal dura.

Results: In the perisylvian CSF, in the CSF above the cribriform plate, in the olfactory bulbs, fila olfactoria, nasal mucosa, and in the cortex, percentage T1 signal intensities showed a rapid increase, peaking at 2 to 4 hours and 6 to 8 hours, respectively. The midsylvian and parasagittal CSF exhibited a slower increase with peak enhancement at 24 to 48 hours. Similarly, in the white matter of the temporal lobe, T1 signal intensities increased gradually, reaching their peak at 24 to 48 hours, followed by a decline after 72 to 96 hours. In the parasagittal dura, T1 signal intensities continued to rise even beyond 72 to 96 hours.

Conclusions: Intrathecally injected gadolinium reaches the lymphatic vessels in the nasal mucosa earlier than those in the parasagittal dura. Transport to the nasal mucosa takes place directly via the subarachnoid space. For the transport to the parasagittal dura, findings are compatible with a trans-parenchymal transport route.

Objectives: Diffusion-weighted imaging (DWI) is pivotal for prostate magnetic resonance imaging. This is rooted in the generally reduced apparent diffusion coefficient (ADC) observed in prostate cancer in comparison to healthy prostate tissue. This difference originates from microstructural tissue composition changes, including a potentially decreased fluid-containing lumen volume. This study explored the nature of the observed ADC contrast in prostate tissue through inversion recovery-prepared DWI examinations that generated varying levels of fluid suppression.

Materials and methods: This institutional review board-approved, single-center, prospective study was conducted from 2023 to 2024; all participants underwent magnetic resonance imaging including DWI with b-values of 50 and 800 s/mm 2 at 16 inversion times (TI; 60-4000 milliseconds). The measured ADC was interpreted with a 2-compartment model (compartments: tissue and fluid). Descriptive statistics were computed for all analyzed parameters.

Results: Twelve healthy male volunteers (45 ± 17 years) and 1 patient with prostate adenocarcinoma (66 years) were evaluated. The ADC map appearance depended heavily on the TI, and we observed a feature-rich ADC(TI) curve. The ADC in the transition zone (TZ) of healthy volunteers increased between TI = 60 milliseconds and approximately 1100 milliseconds, then dropped drastically before increasing again, stabilizing at a very high TI. This effect was greatly reduced in the patient's prostate cancer lesion. The 2-compartment model described this behavior well. After the inversion, tissue magnetization recovers faster, decreasing its signal contribution in absolute terms and resulting in an increase in the ADC. At the tipping point, the total magnetization is zero at b = 0, when the positive tissue magnetization and still-inverted fluid magnetization cancel out. A small diffusion encoding leads to a positive signal, thus generating an infinite ADC. After the tipping point, the fluid magnetization remains negative and thereby reduces the ADC.

Conclusions: Prostate fluid appears to contribute significantly to prostate ADCs. Its contribution could be adjusted by choosing an appropriate inversion recovery preparation, potentially enhancing contrast for prostate cancer lesions.

Objectives: Detecting premalignant lesions for pancreatic ductal adenocarcinoma, mainly pancreatic intraepithelial neoplasia (PanIN), is critical for early diagnosis and for understanding PanIN biology. Based on PanIN's histology, we hypothesized that diffusion tensor imaging (DTI) and T2* could detect PanIN.

Materials and methods: DTI was explored for the detection and characterization of PanIN in genetically engineered mice (KC, KPC). Following in vivo DTI, ex vivo ultrahigh-field (16.4 T) MR microscopy using DTI, T2* was performed with histological validation. Sources of MR contrasts and histological features were investigated, including histological scoring for disease burden (lesion span) and severity (adjusted score). To test if findings in mice can be translated to humans, human pancreas specimens were imaged.

Results: DTI detected PanIN and pancreatic ductal adenocarcinoma in vivo (6 KPC, 4 KC, 6 controls) with high discriminative ability: fractional anisotropy (FA) and radial diffusivity with area under the curve = 0.983 (95% confidence interval: 0.932-1.000); mean diffusivity and axial diffusivity (AD) with area under the curve = 1 (95% confidence interval: 1.000-1.000). MR microscopy with histological correlation (20 KC/KPC; 5 controls) revealed that sources of MR contrasts likely arise from microarchitectural signatures: high FA, AD in fibrotic areas surrounding lesions, high diffusivities within cysts, and high T2* within lesions' stroma. The strongest histological correlations for lesion span and adjusted score were obtained with AD ( R = 0.708, P < 0.001; R = 0.789, P < 0.001, respectively). Ex vivo observations in 5 human pancreases matched our findings in mice, revealing substantial contrast between PanIN and normal pancreas.

Conclusions: DTI and T2* are useful for detecting and characterizing PanIN in genetically engineered mice and in the human pancreas, especially with AD and FA. These are encouraging findings for future clinical applications of pancreatic imaging.