Percutaneous ultrasound gastrostomy (PUG): first prospective clinical trial.

GRAPHICAL ABSTARCT: PURPOSE: To report the results of the first-in-human trial evaluating the safety and efficacy of the percutaneous ultrasound gastrostomy (PUG) technique. METHODS: A prospective, industry-sponsored single-arm clinical trial of PUG insertion was performed in 25 adult patients under investigational device exemption (mean age 64 ± 15 years, 92% men, 80% inpatients, mean BMI 24.5 ± 2.7 kg/m2). A propensity score-matched retrospective cohort of 25 patients who received percutaneous radiologic gastrostomy (PRG) was generated as an institutional control (mean age 66 ± 14 years, 92% men, 80% inpatients, mean BMI 24.0 ± 2.7 kg/m2). Primary outcomes included successful insertion and 30-day procedure-related adverse events (AE's). Secondary outcomes included procedural duration, sedation requirements, and hospital length of stay. RESULTS: All PUG procedures were successful, including 3/25 [12%] performed bedside within the ICU. There was no significant difference between PUG and PRG in rates of mild AE's (3/25 [12%] for PUG and 7/25 [28%] for PRG, p = 0.16) or moderate AE's (1/25 [4%] for PUG and 0/25 for PRG, p = 0.31). There were no severe AE's or 30-day procedure-related mortality in either group. Procedural room time was longer for PUG (56.5 ± 14.1 min) than PRG (39.3 ± 15.0 min, p < 0.001). PUG procedure time was significantly shorter after a procedural enhancement, the incorporation of a Gauss meter to facilitate successful magnetic gastropexy. Length of stay for outpatients did not significantly differ (2.4 ± 0.5 days for PUG and 2.6 ± 1.0 days for PRG, p = 0.70). CONCLUSION: PUG appears effective with a safety profile similar to PRG. Bedside point-of-care gastrostomy tube insertion using the PUG technique shows promise. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov ID NCT03575754.

United adversarial learning for liver tumor segmentation and detection of multi-modality non-contrast MRI.

Simultaneous segmentation and detection of liver tumors (hemangioma and hepatocellular carcinoma (HCC)) by using multi-modality non-contrast magnetic resonance imaging (NCMRI) are crucial for the clinical diagnosis. However, it is still a challenging task due to: (1) the HCC information on NCMRI is insufficient makes extraction of liver tumors feature difficult; (2) diverse imaging characteristics in multi-modality NCMRI causes feature fusion and selection difficult; (3) no specific information between hemangioma and HCC on NCMRI cause liver tumors detection difficult. In this study, we propose a united adversarial learning framework (UAL) for simultaneous liver tumors segmentation and detection using multi-modality NCMRI. The UAL first utilizes a multi-view aware encoder to extract multi-modality NCMRI information for liver tumor segmentation and detection. In this encoder, a novel edge dissimilarity feature pyramid module is designed to facilitate the complementary multi-modality feature extraction. Secondly, the newly designed fusion and selection channel is used to fuse the multi-modality feature and make the decision of the feature selection. Then, the proposed mechanism of coordinate sharing with padding integrates the multi-task of segmentation and detection so that it enables multi-task to perform united adversarial learning in one discriminator. Lastly, an innovative multi-phase radiomics guided discriminator exploits the clear and specific tumor information to improve the multi-task performance via the adversarial learning strategy. The UAL is validated in corresponding multi-modality NCMRI (i.e. T1FS pre-contrast MRI, T2FS MRI, and DWI) and three phases contrast-enhanced MRI of 255 clinical subjects. The experiments show that UAL gains high performance with the dice similarity coefficient of 83.63%, the pixel accuracy of 97.75%, the intersection-over-union of 81.30%, the sensitivity of 92.13%, the specificity of 93.75%, and the detection accuracy of 92.94%, which demonstrate that UAL has great potential in the clinical diagnosis of liver tumors.

MB-FSGAN: Joint segmentation and quantification of kidney tumor on CT by the multi-branch feature sharing generative adversarial network.

The segmentation of the kidney tumor and the quantification of its tumor indices (i.e., the center point coordinates, diameter, circumference, and cross-sectional area of the tumor) are important steps in tumor therapy. These quantifies the tumor morphometrical details to monitor disease progression and accurately compare decisions regarding the kidney tumor treatment. However, manual segmentation and quantification is a challenging and time-consuming process in practice and exhibit a high degree of variability within and between operators. In this paper, MB-FSGAN (multi-branch feature sharing generative adversarial network) is proposed for simultaneous segmentation and quantification of kidney tumor on CT. MB-FSGAN consists of multi-scale feature extractor (MSFE), locator of the area of interest (LROI), and feature sharing generative adversarial network (FSGAN). MSFE makes strong semantic information on different scale feature maps, which is particularly effective in detecting small tumor targets. The LROI extracts the region of interest of the tumor, greatly reducing the time complexity of the network. FSGAN correctly segments and quantifies kidney tumors through joint learning and adversarial learning, which effectively exploited the commonalities and differences between the two related tasks. Experiments are performed on CT of 113 kidney tumor patients. For segmentation, MB-FSGAN achieves a pixel accuracy of 95.7%. For the quantification of five tumor indices, the R2 coefficient of tumor circumference is 0.9465. The results show that the network has reliable performance and shows its effectiveness and potential as a clinical tool.

Endoclip Magnetic Resonance Imaging Screening: A Local Practice Review.

PURPOSE: Not all endoscopically placed clips (endoclips) are magnetic resonance imaging (MRI) compatible. At many institutions, endoclip screening is part of the pre-MRI screening process. Our objective is to determine the contribution of each step of this endoclip screening protocol in determining a patient's endoclip status at our institution. METHODS: A retrospective review of patients' endoscopic histories on general MRI screening forms for patients scanned during a 40-day period was performed to assess the percentage of patients that require endoclip screening at our institution. Following this, a prospective evaluation of 614 patients' endoclip screening determined the percentage of these patients ultimately exposed to each step in the protocol (exposure), and the percentage of patients whose endoclip status was determined with reasonable certainty by each step (determination). RESULTS: Exposure and determination values for each step were calculated as follows (exposure, determination): verbal interview (100%, 86%), review of past available imaging (14%, 36%), review of endoscopy report (9%, 57%), and new abdominal radiograph (4%, 96%), or CT (0.2%, 100%) for evaluation of potential endoclips. Only 1 patient did not receive MRI because of screening (in situ gastrointestinal endoclip identified). CONCLUSIONS: Verbal interview is invaluable to endoclip screening, clearing 86% of patients with minimal monetary and time investment. Conversely, the limited availability of endoscopy reports and relevant past imaging somewhat restricts the determination rates of these. New imaging (radiograph or computed tomography) is required <5% of the time, and although costly and associated with patient irradiation, has excellent determination rates (above 96%) when needed.

Endoscopic Clip MRI Screening: A Canada-Wide Policy Survey.

OBJECTIVE: Not all endoscopically placed clips are MRI compatible, so screening for endoscopic clips before MRI is recommended. The purpose of this study was to assess endoscopic clip screening practices at Canadian MRI centers, including number of centers that screen, specific screening methods, perceived safety of endoscopic clip models, and practices for dealing with confirmed gastrointestinal endoscopic clips. MATERIALS AND METHODS: A bilingual online survey was distributed to Canadian MRI centers to assess site demographics, endoscopic clip screening practices, safety considerations for different endoscopic clip models, protocols for dealing with patients with endoscopic clips, and the perceived value of screening. One year later, a secondary survey was distributed to the original participants to assess for changes made to screening policy after the initial survey and to assess awareness of any complications arising from the presence of endoscopic clips during MRI. RESULTS: Sixty-seven MRI centers completed the survey (55% response rate). Sixteen centers (24%) did not specifically screen for endoscopic clips, five because they were not aware that endoscopic clips may not be safe for MRI. Fifty-one centers (76%) did screen for endoscopic clips. At least 23% of screeners misclassified the safety of one or more MRI-unsafe clips. As many as 36% of screeners may perform MRI on patients with confirmed gastrointestinal endoscopic clips; 16% reschedule for more than 6 weeks after endoscopy; and 18% limit the field strength to 1.5 T, the safety of which is uncertain. CONCLUSION: Many Canadians are undergoing MRI without screening for endoscopic clips. Although the risks of MRI to patients with endoscopic clips is unclear, the misclassification of some endoscopic clip models and inconsistent protocols for dealing with confirmed endoscopic clips call for further research and unified evidence-based endoscopic clip screening standards.