European Radiology Experimental最新文献

Background: To validate pulmonary computed tomography (CT) perfusion in a porcine model by invasive monitoring of cardiac output (CO) using thermodilution method.

Methods: Animals were studied at a single center, using a Swan-Ganz catheter for invasive CO monitoring as a reference. Fifteen pigs were included. Contrast-enhanced CT perfusion of the descending aorta and right and left pulmonary artery was performed. For variation purposes, a balloon catheter was inserted to block the contralateral pulmonary vascular bed; additionally, two increased CO settings were created by intravenous administration of catecholamines. Finally, stepwise capillary occlusion was performed by intrapulmonary arterial injection of 75-μm microspheres in four stages. A semiautomatic selection of AFs and a recirculation-aware tracer-kinetics model to extract the first-pass of AFs, estimating blood flow with the Stewart-Hamilton method, was implemented. Linear mixed models (LMM) were developed to calibrate blood flow calculations accounting with individual- and cohort-level effects.

Results: Nine of 15 pigs had complete datasets. Strong correlations were observed between calibrated pulmonary (0.73, 95% confidence interval [CI] 0.6-0.82) and aortic blood flow measurements (0.82, 95% CI, 0.73-0.88) and the reference as well as agreements (± 2.24 L/min and ± 1.86 L/min, respectively) comparable to the state of the art, on a relatively wide range of right ventricle-CO measurements.

Conclusions: CT perfusion validly measures CO using LMMs at both individual and cohort levels, as demonstrated by referencing the invasive CO.

Relevance statement: Possible clinical applications of CT perfusion for measuring CO could be in acute pulmonary thromboembolism or to assess right ventricular function to show impairment or mismatch to the left ventricle.

Key points: • CT perfusion measures flow in vessels. • CT perfusion measures cumulative cardiac output in the aorta and pulmonary vessels. • CT perfusion validly measures CO using LMMs at both individual and cohort levels, as demonstrated by using the invasive CO as a reference standard.

Background: We investigated the tumor suppression effect of an ultrasound-sensitive doxorubicin-loaded liposome-based nanoparticle, IMP301, to enhance the synergistic effect with focused ultrasound (FUS) in an animal model of pancreatic cancer.

Methods: Thirty nude mice with xenografts of PANC-1 human pancreatic cancer cells were randomly and prospectively allocated to 6 different groups (5 per group) each for Study-1 (dose-response test) and Study-2 (synergistic effect test). Study-1 consisted of control, gemcitabine, Doxil with FUS, and three different doses of IMP301 (2, 4, 6 mg/kg) with FUS groups. Study-2 consisted of control, FUS only, gemcitabine, Doxil with FUS, and IMP301 (4 mg/kg) with or without FUS groups. Differences in tumor volume and growth rate were evaluated by one-way ANOVA and Student-Newman-Keuls test.

Results: In Study-1, 4 mg/kg or greater IMP301 with FUS groups showed lower tumor growth rates of 14 ± 4 mm³/day (mean ± standard deviation) or less, compared to the control, gemcitabine, and Doxil with FUS groups with rates exceeding 28 ± 5 (p < 0.050). The addition of FUS in Study-2 decreased the tumor growth rate in the IMP301-treated groups from 36 ± 17 to 9 ± 6, which was lower than the control, FUS only, gemcitabine, and Doxil with FUS groups (p < 0.050).

Conclusions: IMP301 combined with FUS exhibited higher tumor growth suppression compared to the use of a conventional drug alone or the combination with FUS. The present study showed the potential of IMP301 to enhance the synergistic effect with FUS for the treatment of pancreatic cancer.

Relevance statement: This article aims to evaluate the synergistic effect of FUS and ultrasound-responsive liposomal drug in tumor growth suppression by using xenograft mouse model of pancreatic ductal adenocarcinoma. FUS-induced ultrasound-sensitive drug release may be a potential noninvasive repeatable treatment option for patients with locally advanced or unresectable pancreatic cancer.

Key points: • Modification of conventional drugs combined with FUS would maximize tumor suppression. • IMP301 with FUS had higher tumor suppression effect compared to conventional chemotherapy. • This image-guided drug delivery would enhance therapeutic effects of systemic chemotherapy.

Background: Intravoxel incoherent motion (IVIM)-corrected diffusion tensor imaging (DTI) potentially enhances return-to-play (RTP) prediction after hamstring injuries. However, the long scan times hamper clinical implementation. We assessed accelerated IVIM-corrected DTI approaches in acute hamstring injuries and explore the sensitivity of the perfusion fraction (f) to acute muscle damage.

Methods: Athletes with acute hamstring injury received DTI scans of both thighs < 7 days after injury and at RTP. For a subset, DTI scans were repeated with multiband (MB) acceleration. Data from standard and MB-accelerated scans were fitted with standard and accelerated IVIM-corrected DTI approach using high b-values only. Segmentations of the injury and contralateral healthy muscles were contoured. The fitting methods as well as the standard and MB-accelerated scan were compared using linear regression analysis. For sensitivity to injury, Δ(injured minus healthy) DTI parameters between the methods and the differences between injured and healthy muscles were compared (Wilcoxon signed-rank test).

Results: The baseline dataset consisted of 109 athletes (16 with MB acceleration); 64 of them received an RTP scan (8 with MB acceleration). Linear regression of the standard and high-b DTI fitting showed excellent agreement. With both fitting methods, standard and MB-accelerated scans were comparable. Δ(injured minus healthy) was similar between standard and accelerated methods. For all methods, all IVIM-DTI parameters except f were significantly different between injured and healthy muscles.

Conclusions: High-b DTI fitting with MB acceleration reduced the scan time from 11:08 to 3:40 min:s while maintaining sensitivity to hamstring injuries; f was not different between healthy and injured muscles.

Relevance statement: The accelerated IVIM-corrected DTI protocol, using fewer b-values and MB acceleration, reduced the scan time to under 4 min without affecting the sensitivity of the quantitative outcome parameters to hamstring injuries. This allows for routine clinical monitoring of hamstring injuries, which could directly benefit injury treatment and monitoring.

Key points: • Combining high-b DTI-fitting and multiband-acceleration dramatically reduced by two thirds the scan time. • The accelerated IVIM-corrected DTI approaches maintained the sensitivity to hamstring injuries. • The IVIM-derived perfusion fraction was not sensitive to hamstring injuries.

Background: To compare image quality, metal artifacts, and diagnostic confidence of conventional computed tomography (CT) images of unilateral total hip arthroplasty patients (THA) with deep learning-based metal artifact reduction (DL-MAR) to conventional CT and 130-keV monoenergetic images with and without orthopedic metal artifact reduction (O-MAR).

Methods: Conventional CT and 130-keV monoenergetic images with and without O-MAR and DL-MAR images of 28 unilateral THA patients were reconstructed. Image quality, metal artifacts, and diagnostic confidence in bone, pelvic organs, and soft tissue adjacent to the prosthesis were jointly scored by two experienced musculoskeletal radiologists. Contrast-to-noise ratios (CNR) between bladder and fat and muscle and fat were measured. Wilcoxon signed-rank tests with Holm-Bonferroni correction were used.

Results: Significantly higher image quality, higher diagnostic confidence, and less severe metal artifacts were observed on DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001 for all comparisons). Higher image quality, higher diagnostic confidence for bone and soft tissue adjacent to the prosthesis, and less severe metal artifacts were observed on DL-MAR when compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.014). CNRs were higher for DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001). Higher CNRs were observed on DL-MAR images compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.010).

Conclusions: DL-MAR showed higher image quality, diagnostic confidence, and superior metal artifact reduction compared to conventional CT images and 130-keV monoenergetic images with and without O-MAR in unilateral THA patients.

Relevance statement: DL-MAR resulted into improved image quality, stronger reduction of metal artifacts, and improved diagnostic confidence compared to conventional and virtual monoenergetic images with and without metal artifact reduction, bringing DL-based metal artifact reduction closer to clinical application.

Key points: • Metal artifacts introduced by total hip arthroplasty hamper radiologic assessment on CT. • A deep-learning algorithm (DL-MAR) was compared to dual-layer CT images with O-MAR. • DL-MAR showed best image quality and diagnostic confidence. • Highest contrast-to-noise ratios were observed on the DL-MAR images.

Background: Accurate assessment of breast implants is important for appropriate clinical management. We evaluated silicone properties and diagnostic accuracy for characterizing silicone implants and detecting degenerative changes including rupture in photon-counting computed tomography (PCCT).

Methods: Over 16 months, we prospectively included patients with silicone implants and available breast magnetic resonance imaging (MRI) who received thoracic PCCT performed in prone position. Consensus reading of all available imaging studies including MRI served as reference standard. Two readers evaluated all implants in PCCT reconstructions for degenerative changes. In a subgroup of implants, mean density of silicone, adjacent muscle, and fat were measured on PCCT reconstructions. Contrast-to-noise ratios (CNRs) were calculated for implant-to-muscle and implant-to-fat.

Results: Among 21 subjects, aged 60 ± 13.1 years (mean ± standard deviation) with 29 implants PCCT showed the following: high accuracy for linguine sign, intraimplant fluid (all > 0.99), peri-implant silicone (0.95), keyhole sign (0.90), and folds of the membrane (0.81); high specificity for linguine sign, intraimplant fluid, keyhole sign, folds of the membrane (all > 0.99), and peri-implant silicone (0.98); and high sensitivity for linguine sign and intraimplant fluid (all > 0.99). In a subgroup of 12 implants, the highest CNR for implant-to-muscle was observed on virtual unenhanced reconstructions (20.9) and iodine maps (22.9), for implant-to-fat on iodine maps (27.7) and monoenergetic reconstructions (31.8).

Conclusions: Our findings demonstrate that silicone breast implants exhibit distinct contrast properties at PCCT, which may provide incremental information for detection of degenerative changes and rupture of implants.

Relevance statement: Thoracic photon-counting computed tomography is a promising modality for the diagnostic assessment of silicone breast implants.

Key points: • Thoracic photon-counting computed tomography demonstrates unique contrast properties of silicone breast implants. • Iodine map reconstructions reveal strong contrast-to-noise ratios for implant-to-muscle and implant-to-fat. • Thoracic photon-counting computed tomography shows high diagnostic accuracy in detecting implant degeneration and rupture.

Trial registration: German Clinical Trials Register number DRKS00028997, date of registration 2022-08-08, retrospectively registered.

Background: Phase-contrast magnetic resonance imaging (PC-MRI) quantifies blood flow and velocity noninvasively. Challenges arise in neurovascular disorders due to small vessels. We evaluated the impact of voxel size, number of signal averages (NSA), and velocity encoding (VENC) on PC-MRI measurement accuracy and precision in a small-lumen vessel phantom.

Methods: We constructed an in vitro model with a constant flow rate using a 2.2-mm inner diameter plastic tube. A reservoir with a weight scale and timer was used as standard reference. Gradient-echo T1 weighted PC-MRI sequence was performed on a 3-T scanner with varying voxel size (2.5, 5.0, 7.5 mm³), NSA (1, 2, 3), and VENC (200, 300, 400 cm/s). We repeated measurements nine times per setting, calculating mean flow rate, maximum velocity, and least detectable difference (LDD).

Results: PC-MRI flow measurements were higher than standard reference values (mean ranging from 7.3 to 9.5 mL/s compared with 6.6 mL/s). Decreased voxel size improved accuracy, reducing flow rate measurements from 9.5 to 7.3 mL/s. The LDD for flow rate and velocity varied between 1 and 5%. The LDD for flow rate decreased with increased voxel size and NSA (p = 0.033 and 0.042). The LDD for velocity decreased with increased voxel size (p < 10^-16). No change was observed when VENC varied.

Conclusions: PC-MRI overestimated flow. However, it has high precision in a small-vessel phantom with constant flow rate. Improved accuracy was obtained with increasing spatial resolution (smaller voxels). Improved precision was obtained with increasing signal-to-noise ratio (larger voxels and/or higher NSA).

Relevance statement: Phase-contrast MRI is clinically used in large vessels. To further investigate the possibility of using phase-contrast MRI for smaller intracranial vessels in neurovascular disorders, we need to understand how acquisition parameters affect phase-contrast MRI-measured flow rate and velocity in small vessels.

Key points: • PC-MRI measures flow and velocity in a small lumen phantom with high precision but overestimates flow rate. • The precision of PC-MRI measurements matches the precision of standard reference for flow rate measurements. • Optimizing PC-MRI settings can enhance accuracy and precision in flow rate and velocity measurements.

Background: This study evaluated a deep learning (DL) algorithm for detecting vessel steno-occlusions in patients with peripheral arterial disease (PAD). It utilised a private dataset, which was acquired and annotated by the authors through their institution and subsequently validated by two blinded readers.

Methods: A single-centre retrospective study analysed 105 magnetic resonance angiography (MRA) images using an EfficientNet B0 DL model. Initially, inter-reader variability was assessed using the complete dataset. For a subset of these images (29 from the left side and 35 from the right side) where digital subtraction angiography (DSA) data was available as the ground truth, the model's accuracy and the area under the curve at receiver operating characteristics analysis (ROC-AUC) were evaluated.

Results: A total of 105 patient examinations (mean age, 75 years ±12 [mean ± standard deviation], 61 men) were evaluated. Radiologist-DL model agreement had a quadratic weighted Cohen κ ≥ 0.72 (left side) and ≥ 0.66 (right side). Radiologist inter-reader agreement was ≥ 0.90 (left side) and ≥ 0.87 (right side). The DL model achieved a 0.897 accuracy and a 0.913 ROC-AUC (left side) and 0.743 and 0.830 (right side). Radiologists achieved 0.931 and 0.862 accuracies, with 0.930 and 0.861 ROC-AUCs (left side), and 0.800 and 0.799 accuracies, with 0.771 ROC-AUCs (right side).

Conclusion: The DL model provided valid results in identifying arterial steno-occlusion in the superficial femoral and popliteal arteries on MRA among PAD patients. However, it did not reach the inter-reader agreement of two radiologists.

Relevance statement: The tested DL model is a promising tool for assisting in the detection of arterial steno-occlusion in patients with PAD, but further optimisation is necessary to provide radiologists with useful support in their daily routine diagnostics.

Key points: • This study focused on the application of DL for arterial steno-occlusion detection in lower extremities on MRA. • A previously developed DL model was tested for accuracy and inter-reader agreement. • While the model showed promising results, it does not yet replace human expertise in detecting arterial steno-occlusion on MRA.

Background: Magnetic resonance (MR) imaging of deuterated glucose, termed deuterium metabolic imaging (DMI), is emerging as a biomarker of pathway-specific glucose metabolism in tumors. DMI is being studied as a useful marker of treatment response in a scan-rescan scenario. This study aims to evaluate the repeatability of brain DMI.

Methods: A repeatability study was performed in healthy volunteers from December 2022 to March 2023. The participants consumed 75 g of [6,6'-²H₂]glucose. The delivery of ²H-glucose to the brain and its conversion to ²H-glutamine + glutamate, ²H-lactate, and ²H-water DMI was imaged at baseline and at 30, 70, and 120 min. DMI was performed using MR spectroscopic imaging on a 3-T system equipped with a ¹H/²H-tuned head coil. Coefficients of variation (CoV) were computed for estimation of repeatability and between-subject variability. In a set of exploratory analyses, the variability effects of region, processing, and normalization were estimated.

Results: Six male participants were recruited, aged 34 ± 6.5 years (mean ± standard deviation). There was 42 ± 2.7 days between sessions. Whole-brain levels of glutamine + glutamate, lactate, and glucose increased to 3.22 ± 0.4 mM, 1.55 ± 0.3 mM, and 3 ± 0.7 mM, respectively. The best signal-to-noise ratio and repeatability was obtained at the 120-min timepoint. Here, the within-subject whole-brain CoVs were -10% for all metabolites, while the between-subject CoVs were -20%.

Conclusions: DMI of glucose and its downstream metabolites is feasible and repeatable on a clinical 3 T system.

Trial registration: ClinicalTrials.gov, NCT05402566 , registered the 25th of May 2022.

Relevance statement: Brain deuterium metabolic imaging of healthy volunteers is repeatable and feasible at clinical field strengths, enabling the study of shifts in tumor metabolism associated with treatment response.

Key points: • Deuterium metabolic imaging is an emerging tumor biomarker with unknown repeatability.  • The repeatability of deuterium metabolic imaging is on par with FDG-PET.  • The study of deuterium metabolic imaging in clinical populations is feasible.

Background: Multi-b-value diffusion-weighted imaging (DWI) with different postprocessing models allows for evaluating hepatocellular carcinoma (HCC) proliferation, spatial heterogeneity, and feasibility of treatment strategies. We assessed synergistic effects of bufalin+sorafenib in orthotopic HCC-LM3 xenograft nude mice by using intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), a stretched exponential model (SEM), and a fractional-order calculus (FROC) model.

Methods: Twenty-four orthotopic HCC-LM3 xenograft mice were divided into bufalin+sorafenib, bufalin, sorafenib treatment groups, and a control group. Multi-b-value DWI was performed using a 3-T scanner after 3 weeks' treatment to obtain true diffusion coefficient D_t, pseudo-diffusion coefficient D_p, perfusion fraction f, mean diffusivity (MD), mean kurtosis (MK), distributed diffusion coefficient (DDC), heterogeneity index α, diffusion coefficient D, fractional order parameter β, and microstructural quantity μ. Necrotic fraction (NF), standard deviation (SD) of hematoxylin-eosin staining, and microvessel density (MVD) of anti-CD31 staining were evaluated. Correlations of DWI parameters with histopathological results were analyzed, and measurements were compared among four groups.

Results: In the final 22 mice, f positively correlated with MVD (r = 0.679, p = 0.001). Significantly good correlations of MK (r = 0.677), α (r = -0.696), and β (r= -0.639) with SD were observed (all p < 0.010). f, MK, MVD, and SD were much lower, while MD, α, β, and NF were higher in bufalin plus sorafenib group than control group (all p < 0.050).

Conclusion: Evaluated by IVIM, DKI, SEM, and FROC, bufalin+sorafenib was found to inhibit tumor proliferation and angiogenesis and reduce spatial heterogeneity in HCC-LM3 models.

Relevance statement: Multi-b-value DWI provides potential metrics for evaluating the efficacy of treatment in HCC.

Key points: • Bufalin plus sorafenib combination may increase the effectiveness of HCC therapy. • Multi-b-value DWI depicted HCC proliferation, angiogenesis, and spatial heterogeneity. • Multi-b-value DWI may be a noninvasive method to assess HCC therapeutic efficacy.