Iterative Motion Correction Technique with Deep Learning Reconstruction for Brain MRI: A Volunteer and Patient Study.

The aim of this study was to investigate the effect of iterative motion correction (IMC) on reducing artifacts in brain magnetic resonance imaging (MRI) with deep learning reconstruction (DLR). The study included 10 volunteers (between September 2023 and December 2023) and 30 patients (between June 2022 and July 2022) for quantitative and qualitative analyses, respectively. Volunteers were instructed to remain still during the first MRI with fluid-attenuated inversion recovery sequence (FLAIR) and to move during the second scan. IMCoff DLR images were reconstructed from the raw data of the former acquisition; IMCon and IMCoff DLR images were reconstructed from the latter acquisition. After registration of the motion images, the structural similarity index measure (SSIM) was calculated using motionless images as reference. For qualitative analyses, IMCon and IMCoff FLAIR DLR images of the patients were reconstructed and evaluated by three blinded readers in terms of motion artifacts, noise, and overall quality. SSIM for IMCon images was 0.952, higher than that for IMCoff images (0.949) (p < 0.001). In qualitative analyses, although noise in IMCon images was rated as increased by two of the three readers (both p < 0.001), all readers agreed that motion artifacts and overall quality were significantly better in IMCon images than in IMCoff images (all p < 0.001). In conclusion, IMC reduced motion artifacts in brain FLAIR DLR images while maintaining similarity to motionless images.

Super-resolution Deep Learning Reconstruction for 3D Brain MR Imaging: Improvement of Cranial Nerve Depiction and Interobserver Agreement in Evaluations of Neurovascular Conflict.

RATIONALE AND OBJECTIVES: To determine if super-resolution deep learning reconstruction (SR-DLR) improves the depiction of cranial nerves and interobserver agreement when assessing neurovascular conflict in 3D fast asymmetric spin echo (3D FASE) brain MR images, as compared to deep learning reconstruction (DLR). MATERIALS AND METHODS: This retrospective study involved reconstructing 3D FASE MR images of the brain for 37 patients using SR-DLR and DLR. Three blinded readers conducted qualitative image analyses, evaluating the degree of neurovascular conflict, structure depiction, sharpness, noise, and diagnostic acceptability. Quantitative analyses included measuring edge rise distance (ERD), edge rise slope (ERS), and full width at half maximum (FWHM) using the signal intensity profile along a linear region of interest across the center of the basilar artery. RESULTS: Interobserver agreement on the degree of neurovascular conflict of the facial nerve was generally higher with SR-DLR (0.429-0.923) compared to DLR (0.175-0.689). SR-DLR exhibited increased subjective image noise compared to DLR (p ≥ 0.008). However, all three readers found SR-DLR significantly superior in terms of sharpness (p < 0.001); cranial nerve depiction, particularly of facial and acoustic nerves, as well as the osseous spiral lamina (p < 0.001); and diagnostic acceptability (p ≤ 0.002). The FWHM (mm)/ERD (mm)/ERS (mm-1) for SR-DLR and DLR was 3.1-4.3/0.9-1.1/8795.5-10,703.5 and 3.3-4.8/1.4-2.1/5157.9-7705.8, respectively, with SR-DLR's image sharpness being significantly superior (p ≤ 0.001). CONCLUSION: SR-DLR enhances image sharpness, leading to improved cranial nerve depiction and a tendency for greater interobserver agreement regarding facial nerve neurovascular conflict.

Super-resolution Deep Learning Reconstruction Cervical Spine 1.5T MRI: Improved Interobserver Agreement in Evaluations of Neuroforaminal Stenosis Compared to Conventional Deep Learning Reconstruction.

The aim of this study was to investigate whether super-resolution deep learning reconstruction (SR-DLR) is superior to conventional deep learning reconstruction (DLR) with respect to interobserver agreement in the evaluation of neuroforaminal stenosis using 1.5T cervical spine MRI. This retrospective study included 39 patients who underwent 1.5T cervical spine MRI. T2-weighted sagittal images were reconstructed with SR-DLR and DLR. Three blinded radiologists independently evaluated the images in terms of the degree of neuroforaminal stenosis, depictions of the vertebrae, spinal cord and neural foramina, sharpness, noise, artefacts and diagnostic acceptability. In quantitative image analyses, a fourth radiologist evaluated the signal-to-noise ratio (SNR) by placing a circular or ovoid region of interest on the spinal cord, and the edge slope based on a linear region of interest placed across the surface of the spinal cord. Interobserver agreement in the evaluations of neuroforaminal stenosis using SR-DLR and DLR was 0.422-0.571 and 0.410-0.542, respectively. The kappa values between reader 1 vs. reader 2 and reader 2 vs. reader 3 significantly differed. Two of the three readers rated depictions of the spinal cord, sharpness, and diagnostic acceptability as significantly better with SR-DLR than with DLR. Both SNR and edge slope (/mm) were also significantly better with SR-DLR (12.9 and 6031, respectively) than with DLR (11.5 and 3741, respectively) (p < 0.001 for both). In conclusion, compared to DLR, SR-DLR improved interobserver agreement in the evaluations of neuroforaminal stenosis using 1.5T cervical spine MRI.

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.

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.

Clinical Practice Guidelines for Hepatocellular Carcinoma: The Japan Society of Hepatology 2021 version (5th JSH-HCC Guidelines).

The fifth version of the Clinical Practice Guidelines for Hepatocellular Carcinoma was revised by the Japan Society of Hepatology, according to the methodology of evidence-based medicine and partly to the Grading of Recommendations Assessment, Development and Evaluation system, which was published in October 2021 in Japanese. In addition to surveillance-diagnostic and treatment algorithms, a new algorithm for systemic therapy has been created, as multiple drugs for hepatocellular carcinoma can be currently selected. Here, new or revised algorithms and evidence on which the recommendations are based are described.

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.

Commercially Available Deep-learning-reconstruction of MR Imaging of the Knee at 1.5T Has Higher Image Quality Than Conventionally-reconstructed Imaging at 3T: A Normal Volunteer Study.

PURPOSE: This study aimed to evaluate whether the image quality of 1.5T magnetic resonance imaging (MRI) of the knee is equal to or higher than that of 3T MRI by applying deep learning reconstruction (DLR). METHODS: Proton density-weighted images of the right knee of 27 healthy volunteers were obtained by 3T and 1.5T MRI scanners using similar imaging parameters (21 for high resolution image and 6 for normal resolution image). Commercially available DLR was applied to the 1.5T images to obtain 1.5T/DLR images. The 3T and 1.5T/DLR images were compared subjectively for visibility of structures, image noise, artifacts, and overall diagnostic acceptability and objectively. One-way ANOVA and Friedman tests were used for the statistical analyses. RESULTS: For the high resolution images, all of the anatomical structures, except for bone, were depicted significantly better on the 1.5T/DLR compared with 3T images. Image noise scored statistically lower and overall diagnostic acceptability scored higher on the 1.5T/DLR images. The contrast between lateral meniscus and articular cartilage of the 1.5T/DLR images was significantly higher (5.89 ± 1.30 vs. 4.34 ± 0.87, P < 0.001), and also the contrast between medial meniscus and articular cartilage of the 1.5T/DLR images was significantly higher (5.12 ± 0.93 vs. 3.87 ± 0.56, P < 0.001). Similar image quality improvement by DLR was observed for the normal resolution images. CONCLUSION: The 1.5T/DLR images can achieve less noise, more precise visualization of the meniscus and ligaments, and higher overall image quality compared with the 3T images acquired using a similar protocol.

Temporal Arteritis Caused by Tertiary Syphilis.

A 77-year-old man arrived at our hospital with bilateral shoulder pain persisting for several months and headache for 1 month. Giant cell arteritis with polymyalgia rheumatica was suspected. However, considering his medical history of testing positive for syphilis, we submitted a sample for a syphilis serology test, which yielded positive results. The Treponema pallidum hemagglutination assay of cerebrospinal fluid was positive, and a temporal artery biopsy revealed vasculitis, confirming the diagnosis of tertiary syphilis. He was successfully treated for two weeks with penicillin G infusions. Symptoms reminiscent of giant cell arteritis and polymyalgia rheumatica may reveal syphilis, which is called the "great imitator."

Radiation Protection of the Eye Lens in Fluoroscopy-guided Interventional Procedures.

The medical staff involved in fluoroscopy-guided procedures are at potential risks of radiation-induced cataract. Therefore, proper monitoring of the lens doses is critical, and radiation protection should be provided to the maximum extent that is reasonably achievable. The collar dosimeter is necessary to avoid underestimation of the lens dose, and the third dosimeter behind the protective eyewear would be helpful for those who are likely to exceed the dose limit. The reduction of the patient doses will correspondingly reduce the staff doses. Proper placement of the ceiling-mounted shields and minimization of the face-to-glass gap are the keys to effective shielding. The optimization of procedures and devices that help maintain a distance from the irradiated area and to prevent the looking-up posture will substantially reduce the lens dose.

Feasibility of accelerated whole-body diffusion-weighted imaging using a deep learning-based noise-reduction technique in patients with prostate cancer.

PURPOSE: To assess the possibility of reducing the image acquisition time for diffusion-weighted whole-body imaging with background body signal suppression (DWIBS) by denoising with deep learning-based reconstruction (dDLR). METHODS: Seventeen patients with prostate cancer who underwent DWIBS by 1.5 T magnetic resonance imaging with a number of excitations of 2 (NEX2) and 8 (NEX8) were prospectively enrolled. The NEX2 image data were processed by dDLR (dDLR-NEX2), and the NEX2, dDLR-NEX2, and NEX8 image data were analyzed. In qualitative analysis, two radiologists rated the perceived coarseness, conspicuity of metastatic lesions (lymph nodes and bone), and overall image quality. The contrast-to-noise ratios (CNRs), contrast ratios, and mean apparent diffusion coefficients (ADCs) of metastatic lesions were calculated in a quantitative analysis. RESULTS: The image acquisition time of NEX2 was 2.8 times shorter than that of NEX8 (3 min 30 s vs 9 min 48 s). The perceived coarseness and overall image quality scores reported by both readers were significantly higher for dDLR-NEX2 than for NEX2 (P = 0.005-0.040). There was no significant difference between dDLR-NEX2 and NEX8 in the qualitative analysis. The CNR of bone metastasis was significantly greater for dDLR-NEX2 than for NEX2 and NEX8 (P = 0.012 for both comparisons). The contrast ratios and mean ADCs were not significantly different among the three image types. CONCLUSIONS: dDLR improved the image quality of DWIBS with NEX2. In the context of lymph node and bone metastasis evaluation with DWIBS in patients with prostate cancer, dDLR-NEX2 has potential to be an alternative to NEX8 and reduce the image acquisition time.

Clinical feasibility of an abdominal thin-slice breath-hold single-shot fast spin echo sequence processed using a deep learning-based noise-reduction approach.

BACKGROUND: T2-weighted imaging (T2WI) is a key sequence of MRI studies of the pancreas. The single-shot fast spin echo (single-shot FSE) sequence is an accelerated form of T2WI. We hypothesized that denoising approach with deep learning-based reconstruction (dDLR) could facilitate accelerated breath-hold thin-slice single-shot FSE MRI, and reveal the pancreatic anatomy in detail. PURPOSE: To assess the image quality of thin-slice (3 mm) respiratory-triggered FSE T2WI (Resp-FSE) and breath-hold fast advanced spin echo with and without dDLR (BH-dDLR-FASE and BH-FASE, respectively) at 1.5 T. MATERIALS AND METHODS: MR images of 42 prospectively enrolled patients with suspected pancreaticobiliary disease were obtained at 1.5 T. We qualitatively and quantitatively evaluated image quality of BH-dDLR-FASE related to BH-FASE and Resp-FSE. RESULTS: The scan time of BH-FASE was significantly shorter than that of Resp-FSE (30 ± 4 s and 122 ± 25 s, p < 0.001). Qualitatively, dDLR significantly improved BH-FASE image quality, and the image quality of BH-dDLR-FASE was significantly better than that of Resp-FSE; as quantitative parameters, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of BH-dDLR-FASE were also significantly better than those of Resp-FSE. The BH-dDLR-FASE sequence covered the entire pancreas and liver and provided overall image quality rated close to excellent. CONCLUSIONS: The dDLR technique enables accelerated thin-slice single-shot FSE, and BH-dDLR-FASE seems to be clinically feasible.

[Scientific Research Group Report: Nationwide Survey on Radiation Exposure of Pediatric CT Examination in Japan (2018)].

PURPOSE: To understand the latest pediatric computed tomography (CT) exposure required for the revision of national DRLs. METHODS: A questionnaire was sent to 409 facilities where the members of the Japanese Society of Radiological Technology and the Japanese Society of Pediatric Radiology are enrolled. We investigated the imaging conditions, CTDIvol, and DLP of the pediatric head, chest, and abdominal CT examinations. RESULTS: In all, 43 facilities (11%) responded to our survey. multi detector-row CT (MDCT) systems were available in all surveyed facilities. More than 98% of the MDCT systems had more than 64 detector rows. The CTDIvol of all CT protocols was lower than the NDRL due to the progress of updating to MDCTs with radiation exposure reduction functions such as an iterative reconstruction, but the DLP of head and abdominal CT protocols of some age group were higher than NDRL. CONCLUSION: It is necessary to review the imaging protocol with the attending physician and radiologist and consider further optimization of medical exposure.

Impact of deep learning reconstruction on intracranial 1.5 T magnetic resonance angiography.

PURPOSE: The purpose of this study was to evaluate whether deep learning reconstruction (DLR) improves the image quality of intracranial magnetic resonance angiography (MRA) at 1.5 T. MATERIALS AND METHODS: In this retrospective study, MRA images of 40 patients (21 males and 19 females; mean age, 65.8 ± 13.2 years) were reconstructed with and without the DLR technique (DLR image and non-DLR image, respectively). Quantitative image analysis was performed by placing regions of interest on the basilar artery and cerebrospinal fluid in the prepontine cistern. We calculated the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) for analyses of the basilar artery. Two experienced radiologists evaluated the depiction of structures (the right internal carotid artery, right ophthalmic artery, basilar artery, and right superior cerebellar artery), artifacts, subjective noise and overall image quality in a qualitative image analysis. Scores were compared in the quantitative and qualitative image analyses between the DLR and non-DLR images using Wilcoxon signed-rank tests. RESULTS: The SNR and CNR for the basilar artery were significantly higher for the DLR images than for the non-DLR images (p < 0.001). Qualitative image analysis scores (p < 0.003 and p < 0.005 for readers 1 and 2, respectively), excluding those for artifacts (p = 0.072-0.565), were also significantly higher for the DLR images than for the non-DLR images. CONCLUSION: DLR enables the production of higher quality 1.5 T intracranial MRA images with improved visualization of arteries.

Breath-hold 3D magnetic resonance cholangiopancreatography at 1.5 T using a deep learning-based noise-reduction approach: Comparison with the conventional respiratory-triggered technique.

OBJECTIVES: To assess the image quality of conventional respiratory-triggered 3-dimentional (3D) magnetic resonance cholangiopancreatography (Resp-MRCP) and breath-hold 3D MRCP (BH-MRCP) with and without denoising procedure using deep learning-based reconstruction (dDLR) at 1.5 T. METHODS: Forty-two patients underwent MRCP at 1.5 T MRI. The following imaging sequences were performed: Resp-MRCP and BH-MRCP. We applied the dDLR method to the BH-MRCP data (BH-dDLR-MRCP). As a qualitative analysis, two radiologists rated the visibility of the proximal common bile duct (CBD), pancreaticobiliary junction, distal main pancreatic duct, cystic duct, and right and left hepatic ducts. Artifacts and overall image quality were also rated. The signal-to-noise ratios (SNRs), contrast ratios, and contrast-to-noise ratios (CNRs) of the CBD images were calculated for quantitative analysis. RESULTS: BH-MRCP was successfully performed in a single BH. The qualitative and quantitative measurements for BH-dDLR-MRCP were significantly higher than for BH-MRCP (P < 0.02 and P < 0.001, respectively), and the qualitative measurements for BH-dDLR-MRCP were equivalent to or higher than for Resp-MRCP (P = 0.048-1.000). The SNRs and CNRs for BH-dDLR-MRCP were significantly higher than for Resp-MRCP (P < 0.001 and P = 0.001, respectively). CONCLUSION: dDLR is useful and clinically feasible for BH-MRCP at 1.5 T MRI, and enables rapid imaging without loss of image quality compared to conventional Resp-MRCP.

Primary aortoduodenal fistula in testicular cancer: A fatal complication associated with retroperitoneal lymph node metastasis.

A primary aortoduodenal fistula (PADF) has rarely been reported as a complication of testicular cancer. A 48-year-old Japanese male with relapsed retroperitoneal lymph node metastases received four courses of paclitaxel, ifosfamide, and cisplatin (TIP). On day 19 of the fourth cycle of TIP, he developed hematochezia and hypovolemic shock. Angiography confirmed the presence of a PADF, and we then deployed an endovascular stent graft in the aorta. Although the bleeding improved, the patient died of re-bleeding that developed 18 days later. It is important to recognize this severe complication in order to achieve its early diagnosis and optimal surgical intervention.

Recognizing Radiation-induced Changes in the Central Nervous System: Where to Look and What to Look For.

Radiation therapy (RT) continues to play a central role as an effective therapeutic modality for a variety of tumors and vascular malformations in the central nervous system. Although the planning and delivery techniques of RT have evolved substantially during the past few decades, the structures surrounding the target lesion are inevitably exposed to radiation. A wide variety of radiation-induced changes may be observed at posttreatment imaging, which may be confusing when interpreting images. Histopathologically, radiation can have deleterious effects on the vascular endothelial cells as well as on neuroglial cells and their precursors. In addition, radiation induces oxidative stress and inflammation, leading to a cycle of further cellular toxic effects and tissue damage. On the basis of the time of expression, radiation-induced injury can be divided into three phases: acute, early delayed, and late delayed. Acute and early delayed injuries are usually transient and reversible, whereas late delayed injuries are generally irreversible. The authors provide a comprehensive review of the timeline and expected imaging appearances after RT, including the characteristic imaging features after RT with concomitant chemotherapy. Specific topics discussed are imaging features that help distinguish expected posttreatment changes from recurrent disease, followed by a discussion on the role of advanced imaging techniques. Knowledge of the RT plan, the amount of normal structures included, the location of the target lesion, and the amount of time elapsed since RT is highly important at follow-up imaging, and the reporting radiologist should be able to recognize the characteristic imaging features after RT and differentiate these findings from tumor recurrence. ©RSNA, 2020.

[Examination of Effectiveness Verification and Additional Items in Angiography and IVR of DRLs 2015].

Japanese Diagnostic Reference Levels (DRLs) were released as "Japan DRLs 2015" from Japan Network for Research and Information on Medical Exposure (J-RIME) in June 2015. In "Japan DRLs 2015", DRLs in angiography and interventional procedures are set at a fluoroscopic dose rate of 20 mGy/min at the interventional reference point using a phantom. In order to achieve optimization with DRLs, then it need to be revised regularly. Therefore, we (research group to examine the effect of Japan DRLs 2015 and the necessity of additional items in angiography and vascular interventions) examined the effects of "Japan DRLs 2015" on angiography and interventional procedures. And we also investigated for DRLs revision in the future. As a result, it turned out that it is important to create DRLs in medical procedures that can be effectively used in clinical settings.

Utility of hepatic vein waveform and transient elastography in patients with Budd-Chiari syndrome who require angioplasty: Two case reports.

RATIONALE: Budd-Chiari syndrome (BCS), which causes congestive hepatopathy and aggravates cirrhosis, is typically treated by interventional angioplasty to ameliorate blood flow. X-ray venography is useful for the evaluation of inferior vena cava (IVC) stenosis and determination of treatment timing, but it is invasive and thus unsuitable for repeated examinations. The development of a simple method for the prediction of IVC stenosis would reduce the burden on patients with BCS. PATIENT CONCERNS: We report here our experience of 2 patients with BCS who underwent percutaneous transluminal angioplasty (PTA). The first patient was a 39-year-old male who underwent PTA to expand his stenotic IVC. The second patient was a 19-year-old male who underwent PTA 3 times due to restenosis of his IVC. DIAGNOSES: Both patients were diagnosed with BCS with severe obstruction of the IVC. INTERVENTIONS: We evaluated the hepatic vein (HV) waveform by Doppler ultrasonography and measured liver stiffness (LS) using transient elastography (TE) before and after PTA. OUTCOMES: In case 1, the phasic oscillation of the HV waveform recovered and the LS value decreased after PTA. Both improvements were maintained for ∼3 years, reflecting the long-term patency of the IVC. In case 2, the HV waveform and the LS value improved temporarily after PTA, but then deteriorated gradually. Monitoring of the HV waveform and LS value allowed retreatment prior to total occlusion of the IVC and abrogated the risk of intravascular needle puncture. LESSONS: Monitoring of the HV waveform and the LS value enables safe management of patients with BCS who may require PTA.