Clinical Impact of Deep Learning Reconstruction in MRI.

Deep learning has been recognized as a paradigm-shifting tool in radiology. Deep learning reconstruction (DLR) has recently emerged as a technology used in the image reconstruction process of MRI, which is an essential procedure in generating MR images. Denoising, which is the first DLR application to be realized in commercial MRI scanners, improves signal-to-noise ratio. When applied to lower magnetic field-strength scanners, the signal-to-noise ratio can be increased without extending the imaging time, and image quality is comparable to that of higher-field-strength scanners. Shorter imaging times decrease patient discomfort and reduce MRI scanner running costs. The incorporation of DLR into accelerated acquisition imaging techniques, such as parallel imaging or compressed sensing, shortens the reconstruction time. DLR is based on supervised learning using convolutional layers and is divided into the following three categories: image domain, k-space learning, and direct mapping types. Various studies have reported other derivatives of DLR, and several have shown the feasibility of DLR in clinical practice. Although DLR efficiently reduces Gaussian noise from MR images, denoising makes image artifacts more prominent, and a solution to this problem is desired. Depending on the training of the convolutional neural network, DLR may change the imaging features of lesions and obscure small lesions. Therefore, radiologists may need to adopt the habit of questioning whether any information has been lost on images that appear clean. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Comparison of 1.5 T and 3 T magnetic resonance angiography for detecting cerebral aneurysms using deep learning-based computer-assisted detection software.

PURPOSE: To compare the diagnostic performance of 1.5 T versus 3 T magnetic resonance angiography (MRA) for detecting cerebral aneurysms with clinically available deep learning-based computer-assisted detection software (EIRL aneurysm® [EIRL_an]), which has been approved by the Japanese Pharmaceuticals and Medical Devices Agency. We also sought to analyze the causes of potential false positives. METHODS: In this single-center, retrospective study, we evaluated the MRA scans of 90 patients who underwent head MRA (1.5 T and 3 T in 45 patients each) in clinical practice. Overall, 51 patients had 70 aneurysms. We used MRI from a vendor not included in the dataset used to create the EIRL_an algorithm. Two radiologists determined the ground truth, the accuracy of the candidates noted by EIRL_an, and the causes of false positives. The sensitivity, number of false positives per case (FPs/case), and the causes of false positives were compared between 1.5 T and 3 T MRA. Pearson's χ2 test, Fisher's exact test, and the Mann‒Whitney U test were used for the statistical analyses as appropriate. RESULTS: The sensitivity was high for 1.5 T and 3 T MRA (0.875‒1), but the number of FPs/case was significantly higher with 3 T MRA (1.511 vs. 2.578, p < 0.001). The most common causes of false positives (descending order) were the origin/bifurcation of vessels/branches, flow-related artifacts, and atherosclerosis and were similar between 1.5 T and 3 T MRA. CONCLUSION: EIRL_an detected significantly more false-positive lesions with 3 T than with 1.5 T MRA in this external validation study. Our data may help physicians with limited experience with MRA to correctly diagnose aneurysms using EIRL_an.

Acceleration of knee magnetic resonance imaging using a combination of compressed sensing and commercially available deep learning reconstruction: a preliminary study.

PURPOSE: To evaluate whether deep learning reconstruction (DLR) accelerates the acquisition of 1.5-T magnetic resonance imaging (MRI) knee data without image deterioration. MATERIALS AND METHODS: Twenty-one healthy volunteers underwent MRI of the right knee on a 1.5-T MRI scanner. Proton-density-weighted images with one or four numbers of signal averages (NSAs) were obtained via compressed sensing, and DLR was applied to the images with 1 NSA to obtain 1NSA-DLR images. The 1NSA-DLR and 4NSA images were compared objectively (by deriving the signal-to-noise ratios of the lateral and the medial menisci and the contrast-to-noise ratios of the lateral and the medial menisci and articular cartilages) and subjectively (in terms of the visibility of the anterior cruciate ligament, the medial collateral ligament, the medial and lateral menisci, and bone) and in terms of image noise, artifacts, and overall diagnostic acceptability. The paired t-test and Wilcoxon signed-rank test were used for statistical analyses. RESULTS: The 1NSA-DLR images were obtained within 100 s. The signal-to-noise ratios (lateral: 3.27 ± 0.30 vs. 1.90 ± 0.13, medial: 2.71 ± 0.24 vs. 1.80 ± 0.15, both p < 0.001) and contrast-to-noise ratios (lateral: 2.61 ± 0.51 vs. 2.18 ± 0.58, medial 2.19 ± 0.32 vs. 1.97 ± 0.36, both p < 0.001) were significantly higher for 1NSA-DLR than 4NSA images. Subjectively, all anatomical structures (except bone) were significantly clearer on the 1NSA-DLR than on the 4NSA images. Also, in the former images, the noise was lower, and the overall diagnostic acceptability was higher. CONCLUSION: Compared with the 4NSA images, the 1NSA-DLR images exhibited less noise, higher overall image quality, and allowed more precise visualization of the menisci and ligaments.

Deep learning reconstruction for 1.5 T cervical spine MRI: effect on interobserver agreement in the evaluation of degenerative changes.

OBJECTIVES: To investigate whether deep learning reconstruction (DLR) provides improved cervical spine MR images using a 1.5 T unit in the evaluation of degenerative changes without increasing imaging time. METHODS: This study included 21 volunteers (age 42.4 ± 11.9 years; 17 males) who underwent 1.5 T cervical spine sagittal T2-weighted MRI. From the imaging data with number of acquisitions (NAQ) of 1 or 2, images were reconstructed with DLR (NAQ1-DLR) and without DLR (NAQ1) or without DLR (NAQ2), respectively. Two readers evaluated the images for depiction of structures, artifacts, noise, overall image quality, spinal canal stenosis, and neuroforaminal stenosis. The two readers read studies blinded and randomly. Values were compared between NAQ1-DLR and NAQ1 and between NAQ1-DLR and NAQ2 using the Wilcoxon signed-rank test. RESULTS: The analyses showed significantly better results for NAQ1-DLR compared with NAQ1 and NAQ2 (p < 0.023), except for depiction of disc and foramina by one reader and artifacts by both readers in the comparison between NAQ1-DLR and NAQ2. Interobserver agreements (Cohen's weighted kappa [97.5% confidence interval]) in the evaluation of spinal canal stenosis for NAQ1-DLR/NAQ1/NAQ2 were 0.874 (0.866-0.883)/0.778 (0.767-0.789)/0.818 (0.809-0.827), respectively, and those in the evaluation of neuroforaminal stenosis were 0.878 (0.872-0.883)/0.855 (0.849-0.860)/0.852 (0.845-0.860), respectively. CONCLUSIONS: DLR improved the 1.5 T cervical spine MR images in the evaluation of degenerative spine changes. KEY POINTS: • Two radiologists demonstrated that deep learning reconstruction reduced the noise in cervical spine sagittal T2-weighted MR images obtained using a 1.5 T unit. • Reduced noise in deep learning reconstruction images resulted in a clearer depiction of structures, such as the spinal cord, vertebrae, and zygapophyseal joint. • Interobserver agreement in the evaluation of spinal canal stenosis and foraminal stenosis on cervical spine MR images was significantly improved using deep learning reconstruction (0.874 and 0.878, respectively) versus without deep learning (0.778-0.818 and 0.852-0.855, respectively).

Deep learning reconstruction for the evaluation of neuroforaminal stenosis using 1.5T cervical spine MRI: comparison with 3T MRI without deep learning reconstruction.

PURPOSE: To compare image quality and interobserver agreement in evaluations of neuroforaminal stenosis between 1.5T cervical spine magnetic resonance imaging (MRI) with deep learning reconstruction (DLR) and 3T MRI without DLR. METHODS: In this prospective study, 21 volunteers (mean age: 42.4 ± 11.9 years; 17 males) underwent cervical spine T2-weighted sagittal 1.5T and 3T MRI on the same day. The 1.5T and 3T MRI data were used to reconstruct images with (1.5T-DLR) and without (3T-nonDLR) DLR, respectively. Regions of interest were marked on the spinal cord to calculate non-uniformity (NU; standard deviation/signal intensity × 100), as an indicator of image noise. Two blinded radiologists evaluated the images in terms of the depiction of structures, artifacts, noise, overall image quality, and neuroforaminal stenosis. The NU value and the subjective image quality scores were compared between 1.5T-DLR and 3T-nonDLR using the Wilcoxon signed-rank test. Interobserver agreement in evaluations of neuroforaminal stenosis for 1.5T-DLR and 3T-nonDLR was evaluated using Cohen's weighted kappa analysis. RESULTS: The NU value for 1.5T-DLR was 8.4, which was significantly better than that for 3T-nonDLR (10.3; p < 0.001). Subjective image scores were significantly better for 1.5T-DLR than 3T-nonDLR images (p < 0.037). Interobserver agreement (95% confidence intervals) in the evaluations of neuroforaminal stenosis was significantly superior for 1.5T-DLR (0.920 [0.916-0.924]) than 3T-nonDLR (0.894 [0.889-0.898]). CONCLUSION: By using DLR, image quality and interobserver agreement in evaluations of neuroforaminal stenosis on 1.5T cervical spine MRI could be improved compared to 3T MRI without DLR.

Effects of Gadolinium Deposition in the Brain on Motor or Behavioral Function: A Mouse Model.

Background Recent studies showing gadolinium deposition in multiple organs have raised concerns about the safety of gadolinium-based contrast agents (GBCAs). Purpose To explore whether gadolinium deposition in brain structures will cause any motor or behavioral alterations. Materials and Methods This study was performed from July 2019 to December 2020. Groups of 17 female BALB/c mice were each repeatedly injected with phosphate-buffered saline (control group, group A), a macrocyclic GBCA (group B), or a linear GBCA (group C) for 8 weeks (5 mmol per kilogram of bodyweight per week for GBCAs). Brain MRI studies were performed every other week to observe the signal intensity change caused by the gadolinium deposition. After the injection period, rotarod performance test, open field test, elevated plus-maze test, light-dark anxiety test, locomotor activity assessment test, passive avoidance memory test, Y-maze test, and forced swimming test were performed to assess the locomotor abilities, anxiety level, and memory. Among-group differences were compared by using one-way or two-way factorial analysis of variance with Tukey post hoc testing or Dunnett post hoc testing. Results Gadolinium deposition in the bilateral deep cerebellar nuclei was confirmed with MRI only in mice injected with a linear GBCA. At 8 weeks, contrast ratio of group C (0.11; 95% CI: 0.10, 0.12) was higher than that of group A (-2.1 × 10-3; 95% CI: -0.011, 7.5 × 10-3; P < .001) and group B (2.7 × 10-4; 95% CI: -8.2 × 10-3, 8.7 × 10-3; P < .001). Behavioral analyses showed that locomotor abilities, anxiety level, and long-term or short-term memory were not different in mice injected with linear or macrocyclic GBCAs. Conclusion No motor or behavioral alterations were observed in mice with brain gadolinium deposition. Also, the findings support the safety of macrocyclic gadolinium-based contrast agents. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Chen in this issue.

Embolization of visceral arterial aneurysms: Simulation with 3D-printed models.

OBJECTIVES: The present technical article aimed to describe the efficacy of three-dimensional (3D)-printed hollow vascular models as a tool in the preoperative simulation of endovascular embolization of visceral artery aneurysms. METHODS: From November 2015 to November 2016, four consecutive endovascular treatments of true visceral artery aneurysms were preoperatively simulated with 3D-printed hollow models. The mean age of the patients (one male and three females) was 54 (range: 40-71) years. Three patients presented with splenic artery aneurysm and one with anterior pancreaticoduodenal artery aneurysm. The average diameter of the aneurysms was 16.5 (range: 10-25) mm. The 3D-printed hollow models of the visceral artery aneurysms and involved arteries were created using computed tomography angiography data of the patients. After establishing treatment plans by simulations with the 3D-printed models, all patients received endovascular treatment. RESULTS: All four hollow aneurysm models were successfully fabricated and used in the preoperative simulation of endovascular treatment. In the preoperative simulations with 3D-printed hollow models, splenic aneurysms were embolized with coils and/or n-butyl-2-cyanoacrylate to establish the actual treatment plans, and a small arterial branch originating from an anterior pancreaticoduodenal artery aneurysm was selected to obtain feedback regarding the behavior of catheters and guidewires. After establishing treatment plans by simulations, the visceral artery aneurysms of all patients were successfully embolized without major complications and recanalization. CONCLUSIONS: Simulation with 3D-printed hollow models can help establish an optimal treatment plan and may improve the safety and efficacy of endovascular treatment for visceral artery aneurysms.

Deep learning to differentiate parkinsonian disorders separately using single midsagittal MR imaging: a proof of concept study.

OBJECTIVES: To evaluate the diagnostic performance of deep learning with the convolutional neural networks (CNN) to distinguish each representative parkinsonian disorder using MRI. METHODS: This clinical retrospective study was approved by the institutional review board, and the requirement for written informed consent was waived. Midsagittal T1-weighted MRI of a total of 419 subjects (125 Parkinson's disease (PD), 98 progressive supranuclear palsy (PSP), and 54 multiple system atrophy with predominant parkinsonian features (MSA-P) patients, and 142 normal subjects) between January 2012 and April 2016 was retrospectively assessed. To deal with the overfitting problem of deep learning, all subjects were randomly divided into training (85%) and validation (15%) data sets with the same proportions of each disease and normal subjects. We trained the CNN to distinguish each parkinsonian disorder using single midsagittal T1-weighted MRI with a training group to minimize the differences between predicted output probabilities and the clinical diagnoses; then, we adopted the trained CNN to the validation data set. Subjects were classified into each parkinsonian disorder or normal condition according to the final diagnosis of the trained CNN, and we assessed the diagnostic performance of the CNN. RESULTS: The accuracies of diagnostic performances regarding PD, PSP, MSA-P, and normal subjects were 96.8, 93.7, 95.2, and 98.4%, respectively. The areas under the receiver operating characteristic curves for distinguishing each condition from others (PD, PSP, MSA-P, and normal subjects) were 0.995, 0.982, 0.990, and 1.000, respectively. CONCLUSION: Deep learning with CNN enables highly accurate discrimination of parkinsonian disorders using MRI. KEY POINTS: • Deep learning convolution neural network achieves differential diagnosis of PD, PSP, MSA-P, and normal controls with an accuracy of 96.8, 93.7, 95.2, and 98.4%, respectively. • The areas under the curves for distinguishing between PD, PSP, MSA-P, and normality were 0.995, 0.982, 0.990, and 1.000, respectively. • CNN may learn important features that humans not notice, and has a possibility to perform previously impossible diagnoses.

PEG-poly(L-lysine)-based polymeric micelle MRI contrast agent: Feasibility study of a Gd-micelle contrast agent for MR lymphography.

PURPOSE: To investigate the feasibility of polymeric micelle of poly(ethyleneglycol) (PEG)-b-poly(L-lysine-DOTA) (Gd-micelle) as a contrast agent for magnetic resonance lymphography (MRL). MATERIALS AND METHODS: Twenty-four female BALB/c mice were randomly divided into four groups of six mice each. Among them, mice of two groups were injected of complete Freund's adjuvant to obtain inflamed lymph nodes. We subcutaneously injected 0.5 µmol Gd per mouse of Gd-micelle or gadofluorine P in the right rear footpad. Identical 3D T1 -weighted gradient-echo imaging (1T MRI system) were subsequently obtained to create time-intensity curves of the right popliteal, sacral, and lumbar-aortic lymph nodes and to measure the contrast ratios (CRs). The peak CR, area under the curve (AUC), and elimination half-life (T1/2 ) of CR of the popliteal lymph node were assessed by two-way factorial analysis of variance. We also performed a qualitative assessment of normal and inflamed lymph node at three timepoints. RESULTS: The mean peak CR of Gd-micelle was 2.64 and 1.89 for gadofluorine P in normal mice, and 3.48 and 2.73 in the inflamed lymph node. Statistically, peak CR was higher for Gd-micelle (P = 0.004). In addition, the AUC was larger (P < 0.001) and T1/2 was longer (P < 0.001) for Gd-micelle. In qualitative assessment, Gd-micelle demonstrated the same or higher scores in every lymph node, and demonstrated a higher score in lumbar-aortic lymph node of a 360-minute image (P = 0.006) and in inflamed lymph node of a 360-minute image (P = 0.009). CONCLUSION: Compared to gadofluorine P, Gd-micelle showed higher and more prolonged enhancement in MRL imaging in normal and inflamed lymph nodes. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:238-245.

The inhibitory effect of gadoxetate disodium on hepatic transporters: a study using indocyanine green.

OBJECTIVES: To assess the inhibitory effect of gadoxetate disodium on the transporter system using indocyanine green (ICG). MATERIALS AND METHODS: Groups of six female B6 Albino mice were injected with the test agent (0.62 mmol/kg gadoxetate disodium) or phosphate-buffered saline (control) 10 min before injection of ICG. Identical fluorescence images were subsequently obtained to create time-efficiency curves of liver parenchymal uptake. The study was performed on hypothermic and normothermic mice. The logarithms of the absorption rate constants (logKa values) and of the elimination rate constants (logKe values) were calculated for each experimental condition, and between-group differences were compared using Student's t-test. RESULTS: The logKe values of the test group were lower than those of the control group at both temperatures (-6.52 vs. -5.87 under hypothermic conditions and -4.54 vs. -4.14 under normothermic conditions), and both differences were statistically significant (p = 0.037, 0.015 respectively). In terms of the logKa values, although the difference did not reach statistical significance (p = 0.052), the test group had lower values than the control group under hypothermic conditions (-0.771 vs. -0.376). In normothermic mice, the logKa values for the test and control groups were 0.037 and 0.277 respectively, thus not significantly different (p = 0.404). CONCLUSIONS: Gadoxetate disodium inhibited ICG excretion. Thus, gadoxetate disodium inhibited the ATP-binding cassette sub-family C member 2 transporter. KEY POINTS: • Gadoxetate disodium inhibited ICG excretion. • Gadoxetate disodium tended to inhibit hepatic ICG uptake. • Drug-drug interactions of gadoxetate disodium need further investigation.

Gadoxetate disodium-induced tachypnoea and the effect of dilution method: a proof-of-concept study in mice.

OBJECTIVES: To directly investigate the rapid respiratory effect of gadoxetate disodium in an experimental study using mice. METHODS: After confirming the steady respiratory state under general anaesthesia, eight mice were injected with all test agents in the following order: phosphate-buffered saline (A, control group), 1.25 mmol/kg of gadoteridol (B) or gadopentetate dimeglumine (C), or 0.31 mmol/kg of gadoxetate disodium (D, E). The experimenter was not blinded to the agents. The injection dose was fixed as 100 µL for Groups A-D and 50 µL for Group E. We continuously monitored and recorded respiratory rate (RR), peripheral oxygen saturation (SpO2), and heart rate. The time-series changes from 0 to 30 s were compared by the linear mixed method RESULTS: Groups D and E showed the largest RR increase (20.6 and 20.3 breaths/min, respectively) and were significantly larger compared to Group A (3.36 breaths/min, both P<0.001). RR change of Groups D and E did not differ. RR change of Groups B and C was smaller (0.72 and 12.4 breaths/min, respectively) and did not differ statistically with Group A. Significant bradycardia was observed only in Group C (P<0.001). SpO2 was constant in all groups. CONCLUSIONS: Gadoxetate disodium causes a rapid tachypnoea without significant change of SpO2 and heart rate regardless of the dilution method. KEY POINTS: • Injection of gadoxetate disodium causes tachypnoea. • Dilution method did not alter the rapid respiratory effect of gadoxetate disodium. • The respiratory effect of gadoxetate disodium was larger than other contrast agents.

Imaging prediction of nonalcoholic steatohepatitis using computed tomography texture analysis.

OBJECTIVES: To determine if texture analysis of non-contrast-enhanced CT (NECT) images is able to predict nonalcoholic steatohepatitis (NASH). METHODS: NECT images from 88 patients who underwent a liver biopsy for the diagnosis of suspected NASH were assessed and texture feature parameters were obtained without and with filtration. The patient population was divided into a predictive learning dataset and a validation dataset, and further divided into groups according to the prediction of liver fibrosis as assessed by hyaluronic acid levels. The reference standard was the histological result of a liver biopsy. A predictive model for NASH was developed using parameters derived from the learning dataset that demonstrated areas under the receiver operating characteristic curve (AUC) of >0.65. The resulting model was then applied to the validation dataset. RESULTS: In patients without suspected fibrosis, the texture parameter mean without filter and skewness with a 2-mm filter were selected for the NASH prediction model. The AUC of the predictive model for the validation dataset was 0.94 and the accuracy was 94%. In patients with suspicion of fibrosis, the mean without filtration and kurtosis with a 4-mm filter were selected for the NASH prediction model. The AUC for the validation dataset was 0.60 and the accuracy was 42%. CONCLUSIONS: In patients without suspicion of fibrosis, NECT texture analysis effectively predicted NASH. KEY POINTS: • In patients without suspicion of fibrosis, NECT texture analysis effectively predicted NASH. • The mean without filtration and skewness with a 2-mm filter were modest predictors of NASH in patients without suspicion of liver fibrosis. • Hepatic fibrosis masks the characteristic texture features of NASH.

Combined intravitreal methotrexate and immunochemotherapy followed by reduced-dose whole-brain radiotherapy for newly diagnosed B-cell primary intraocular lymphoma.

Primary intraocular lymphoma (IOL) has a propensity for central nervous system (CNS) relapse within 2 years of initial diagnosis, affecting clinical outcome. To reduce CNS relapse, we performed the combination treatment protocols of intravitreal methotrexate injections, methotrexate-based systemic induction chemotherapy and consolidation high-dose cytarabine and reduced-dose whole brain radiation therapy (rdWBRT, 23·4 Gy) for B-cell primary IOL with or without newly diagnosed CNS involvement. All patients underwent longitudinal brain magnetic resonance imaging (MRI) and cognitive assessment for evaluation of treatment-induced leucoencephalopathy. Seventeen patients initiated and 16 completed the protocol treatment. CNS relapse occurred in 2 patients and intraocular relapse in 3. Four-year progression-free survival (PFS) was 74·9% and 4-year overall survival (OS) was 86·3%, with a median follow-up period of 48·9 months. Of 11 patients without CNS involvement, 1 had CNS relapse and 3 intraocular relapse, and 4-year PFS and OS was 72·7% and 88·9%, respectively. Although white matter abnormalities shown by MRI were significantly increased at 4 years after rdWBRT, only one patient developed mild cognitive impairment. The combination of intravitreal chemotherapy, prophylactic systemic chemotherapy and rdWBRT for primary IOL showed a potential to reduce CNS relapse rate and improved 4-year PFS and OS without increase of cognitive dysfunction.

Influence of outflow-obstructed liver volume and venous communication development: A three-dimensional volume study in living donors.

Living donor liver transplantation using the left liver graft with the middle hepatic vein (MHV) is a well-established procedure. Following such procedures, outflow obstruction occurs in remnant livers. However, the effects of the outflow-obstructed liver volume (LVOut-Ob ), with or without venous communication development, remain unclear. The aim of the study is to investigate effects of outflow-obstructed regions by focusing on short-term outcomes and remnant liver hypertrophy in left liver procurement donors. Of 532 donors, we collected data from 119 undergoing left liver procurement with the MHV. Postoperative hepatic parameters, venous communication development, and liver hypertrophy were evaluated in 2 donor groups based on LVOut-Ob . The left liver was procured with the MHV in 119 donors, who formed 2 more groups based on the median LVOut-Ob : large-outflow-obstruction group (n = 60; LVOut-Ob ≥ 263 mL) and small-outflow-obstruction (n = 59; LVOut-Ob < 263 mL) group. Postoperative liver function parameters were significantly impaired in the large-outflow-obstruction group compared with the small-outflow-obstruction group. Postoperative venous communication developed in 52 (66.7%) of 78 donors analyzed. Hypertrophy ratios in remnant right livers and right paramedian sectors were significantly higher in the small-outflow-obstruction group than in the large-outflow-obstruction group (P = 0.01 and P = 0.02, respectively). The liver hypertrophy ratio of outflow-obstructed regions was better, especially in small regions developing venous communication (P = 0.001). The postoperative morbidity rate did not differ significantly (P = 0.66). In conclusion, the procurement of the left liver graft with the MHV was safely performed with minimal morbidity by assessing the donor remnant right liver volume with and without outflow obstruction. Attention should be paid that postoperative hepatic parameters and remnant liver hypertrophy were impaired in the remnant livers with large outflow-obstructed regions compared with those with small outflow-obstructed regions. Liver Transplantation 23 1531-1540 2017 AASLD.

Persistent T2*-hypointensity of the liver parenchyma after irradiation to the SPIO-accumulated liver: An imaging marker for responses to radiotherapy in hepatic malignancies.

PURPOSE: To determine whether T2*-weighted MRI has the ability to visualize the irradiated liver parenchyma and liver tumor after irradiation to the previously superparamagnetic iron oxide (SPIO)-accumulated liver. MATERIALS AND METHODS: We examined 24 liver tumor-bearing rats. Nine rats (Group 1) received 20 µmol Fe/kg SPIO and subsequent 70-Gy irradiation to the tumor-bearing liver lobe. Four rats (Group 2) received SPIO and sham irradiation. Six rats (Group 3) received saline and irradiation. Finally, five rats (Group 4) received saline and sham irradiation. We acquired sequential 3 Tesla T2*-weighted images of the liver on day 7, and assessed MR image findings including signal intensity of the tumors and tumor-bearing liver lobes. RESULTS: In six rats in Group 1, tumors shrunk by 39-100% (303-0 mm3 ), and severely, well-defined hypointense irradiated areas were observed. In the other two rats, tumors enlarged by 25 and 172% (595 and 1148 mm3 ), and hypointense rings surrounded the tumors. The normalized relative signal intensity of the irradiated areas was significantly lower than that of the tumor (0.53 ± 0.06 versus 0.94 ± 0.06; P < 0.05). The severely, well-defined hypointense areas were not observed in the other groups. Histologically, necrotic regions dominated and minimal nonnecrotic tumor cells remained in irradiated areas. The number of CD68-positive cells was higher in irradiated areas than in nonirradiated areas. CONCLUSION: T2*-weighted MR imaging visualized the irradiated liver parenchyma as markedly, well-defined hypointense areas and liver cancer lesions as hyperintense areas only when SPIO was administered before irradiation. The visualization of the hypointense area was associated with tumor regression after irradiation. LEVEL OF EVIDENCE: 2 J. Magn. Reson. Imaging 2017;45:303-312.

Development of pancreatic cancer is predictable well in advance using contrast-enhanced CT: a case-cohort study.

OBJECTIVES: To investigate the radiological findings prognostic for the development of pancreatic adenocarcinoma in a cohort of patients with hepatocellular carcinoma, using multiphasic computed tomography (CT). METHODS: A case-cohort study performed in a single university hospital. A database of patients who received hepatocellular carcinoma (HCC) treatment and trimonthly follow-up with four-phase dynamic CT was used (n = 1848). The cohort group was randomly extracted from the database (n = 103). The case group comprised nine patients from the database who developed pancreatic adenocarcinoma. The radiological findings were assessed during follow-up (average, 32 months). RESULTS: The incidence of pancreatic mass, inhomogeneous parenchyma, loss of fatty marbling and main pancreatic duct dilatation gradually increased from 4 to 13 months before the diagnosis of pancreatic adenocarcinoma. There was a significantly higher incidence of pancreatic mass, inhomogeneous parenchyma and loss of fatty marbling on CT at baseline (average, 34 months before diagnosis) in the case group compared with the cohort group (P values < 0.01) and those findings at baseline were revealed as prognostic factors for pancreatic carcinogenesis, respectively (log-rank test, P values < 0.001). CONCLUSIONS: Several radiological findings observed on multiphasic CT can assist in predicting pancreatic carcinogenesis well in advance. KEY POINTS: • Pancreatic findings in multiphasic CT help predict development of pancreatic adenocarcinoma. • Key findings are mass, inhomogeneous parenchyma and loss of fatty marbling. • Those findings were observed 34 months before confirmed diagnosis of adenocarcinoma. • Those findings were prognostic factors for pancreatic carcinogenesis.

3D-Printed Visceral Aneurysm Models Based on CT Data for Simulations of Endovascular Embolization: Evaluation of Size and Shape Accuracy.

OBJECTIVE: The objective of this study is to verify the accuracy of 3D-printed hollow models of visceral aneurysms created from CT angiography (CTA) data, by evaluating the sizes and shapes of aneurysms and related arteries. SUBJECTS AND METHODS: From March 2006 to August 2015, 19 true visceral aneurysms were embolized via interventional radiologic treatment provided by the radiology department at our institution; aneurysms with bleeding (n = 3) or without thin-slice (< 1 mm) preembolization CT data (n = 1) were excluded. A total of 15 consecutive true visceral aneurysms from 11 patients (eight women and three men; mean age, 61 years; range, 53-72 years) whose aneurysms were embolized via endovascular procedures were included in this study. Three-dimensional-printed hollow models of aneurysms and related arteries were fabricated from CTA data. The accuracies of the sizes and shapes of the 3D-printed hollow models were evaluated using the nonparametric Wilcoxon signed rank test and the Dice coefficient index. RESULTS: Aneurysm sizes ranged from 138 to 18,691 mm3 (diameter, 6.1-35.7 mm), and no statistically significant difference was noted between patient data and 3D-printed models (p = 0.56). Shape analysis of whole aneurysms and related arteries indicated a high level of accuracy (Dice coefficient index value, 84.2-95.8%; mean [± SD], 91.1 ± 4.1%). CONCLUSION: The sizes and shapes of 3D-printed hollow visceral aneurysm models created from CTA data were accurate. These models can be used for simulations of endovascular treatment and precise anatomic information.

Computed tomography and magnetic resonance imaging of a plexiform angiomyxoid myofibroblastic tumor: a case report.

BACKGROUND: Plexiform angiomyxoid myofibroblastic tumor (PAMT) is a very rare mesenchymal tumor of the stomach. Here we report a case of pathologically confirmed PAMT with an unique cyst formation. CASE PRESENTATION: A 55-year-old male with a 10-year history of a gastric subepithelial tumor underwent computed tomography (CT) and magnetic resonance imaging (MRI). Two cysts were observed in the tumor, and the cyst wall showed moderately high intensity on T2-weighted images compared with the gastric wall. On dynamic study, the cyst wall showed a gradual enhancement pattern, and prominent enhancement was observed in the delayed phase. Laparoscopic partial gastric resection was performed, and a pathological diagnosis of PAMT was rendered. CONCLUSION: We present a rare case of gastric PAMT, which was uniquely presented as cysts. One of the cysts in the tumor had an epithelial wall lining, which had never been reported before in gastric mesenchymal tumor, in addition to partial glandular structure. We reviewed our case, focusing on radiologic-pathologic correlation, and suggested hypothesis of cyst formation. According to our findings, PAMT with cyst formation would be included of differential diagnosis of gastric subepithelial tumors.

Full and hybrid iterative reconstruction to reduce artifacts in abdominal CT for patients scanned without arm elevation.

Background Abdominal computed tomography (CT) without arm elevation is associated with degraded image quality due to streak artifacts. Purpose To compare the degree of streak artifacts in abdominal CT images without arm elevation between full iterative reconstruction (IR), hybrid IR, and filtered back projection (FBP) using two commercially available scanners. Material and Methods First, a phantom study simulating CT examination without arm elevation was performed. Second, unenhanced axial images of 33 patients (17 and 16 patients for each vendor) who underwent CT without arm elevation were reconstructed with full IR, hybrid IR and FBP. A radiologist placed 50 parallel lines with lengths of 50 pixels vertical to the streaks and quantitatively evaluated the images for streak artifacts in the phantom study. Two radiologists evaluated the images of patients for streak artifacts (on the liver and the kidney) and diagnostic acceptability using a four-point scale. Results The phantom study indicated that full IR algorithms were more effective than FBP in reducing streak artifacts. In the clinical patient study, streak artifacts were significantly more reduced with full IR compared with FBP in both the liver and kidney ( P < 0.012). Streak artifact reduction was limited with hybrid IR. Model-based iterative reconstruction (MBIR) (one of the full IR algorithms) provided diagnostically more acceptable image quality ( P < 0.016) compared with FBP. Conclusion In abdominal CT without arm elevation, full IR enabled a more efficient streak artifact reduction compared with FBP and MBIR was associated with diagnostically more acceptable images.

Effects of rTMS of pre-supplementary motor area on fronto basal ganglia network activity during stop-signal task.

Stop-signal task (SST) has been a key paradigm for probing human brain mechanisms underlying response inhibition, and the inhibition observed in SST is now considered to largely depend on a fronto basal ganglia network consisting mainly of right inferior frontal cortex, pre-supplementary motor area (pre-SMA), and basal ganglia, including subthalamic nucleus, striatum (STR), and globus pallidus pars interna (GPi). However, causal relationships between these frontal regions and basal ganglia are not fully understood in humans. Here, we partly examined these causal links by measuring human fMRI activity during SST before and after excitatory/inhibitory repetitive transcranial magnetic stimulation (rTMS) of pre-SMA. We first confirmed that the behavioral performance of SST was improved by excitatory rTMS and impaired by inhibitory rTMS. Afterward, we found that these behavioral changes were well predicted by rTMS-induced modulation of brain activity in pre-SMA, STR, and GPi during SST. Moreover, by examining the effects of the rTMS on resting-state functional connectivity between these three regions, we showed that the magnetic stimulation of pre-SMA significantly affected intrinsic connectivity between pre-SMA and STR, and between STR and GPi. Furthermore, the magnitudes of changes in resting-state connectivity were also correlated with the behavioral changes seen in SST. These results suggest a causal relationship between pre-SMA and GPi via STR during response inhibition, and add direct evidence that the fronto basal ganglia network for response inhibition consists of multiple top-down regulation pathways in humans.