Subtotal cholecystectomy with omental pedicle plug for the challenging gallbladder: A case report and review of the literature.

If patient anatomy or disease does not allow for a traditional or partial cholecystectomy, an omental pedicle plug may be a viable option to limit the risk of postoperative uncontrolled bile leak from the cystic duct and to control patient symptoms.

Artificial intelligence tool detection of intravenous contrast enhancement using spleen attenuation.

PURPOSE: To assess the ability of an automated AI tool to detect intravenous contrast material (IVCM) in abdominal CT examinations using spleen attenuation. METHODS: A previously validated automated AI tool measuring the attenuation of the spleen was deployed on a sample of 32,994 adult (age ≥ 18) patients (mean age, 61.9 ± 14.7 years; 13,869 men, 19,125 women) undergoing 65,449 supine position CT examinations (41,020 with and 24,429 without IVCM by DICOM header) from January 1, 2000 to December 31, 2021. After exclusions, receiver operating characteristic (ROC) curve analysis was performed to determine the optimal threshold for binary classification of IVCM status (non-contrast vs IVCM enhanced), which was then applied to the sample. Discordant examinations (i.e., IVCM status determined by AI tool did not match DICOM header) were manually reviewed to establish ground truth. Repeat ROC curve and contingency table analysis were performed to assess AI tool performance. RESULTS: ROC analysis of the initial study sample of 61,783 CT examinations yielded AUC of 0.970 with Youden index suggesting an optimal spleen attenuation threshold of 65 Hounsfield units (HU). Manual review of 2094 discordant CT examinations revealed discordance due to DICOM header error in 1278 (61.0%) and AI tool misclassification in 410 (19.6%), with 406 (9.4%) meeting exclusion criteria. Analysis of 61,377 CT examinations in the final study sample yielded AUC of 0.999 with accuracy of 99.3% at the 65 HU threshold. Error rate for DICOM header information was 2.1% (1278/61,377) versus 0.7% (410/61,377) for the AI tool. CONCLUSION: The automated spleen attenuation AI tool was highly accurate for detection of IVCM at a threshold of 65 HU.

Effectiveness of Three-Dimensionally Printed Models in Anatomy Education for Medical Students and Resident Physicians: Systematic Review and Meta-Analysis.

INTRODUCTION: Despite a surge in the use of three-dimensional printing (3DP) in medical education, a comprehensive evaluation of randomized trials in its effectiveness is lacking. Radiologic studies play an integral role in affording educators the ability to create customized realistic anatomic models. This systematic review and meta-analysis sought to assess the effect of 3DP versus traditional 2-D methods for anatomy education. METHODS: PubMed, Scopus, Cochrane Library, ERIC, and IEEE Xplore were queried to identify randomized controlled trials that quantitatively investigated anatomy education via postintervention assessments of medical students or resident physicians who were exposed to 3DP versus traditional methods. Criteria for the meta-analysis required that studies additionally included a pre-intervention assessment. RESULTS: A total of 804 articles were reviewed, identifying 8 and 7 studies for systematic reviews of medical students and resident physicians, respectively, of which 4 and 7 were included in the meta-analyses. 3DP models were associated with higher anatomy examination scores for medical students (P < .0001), but for resident physicians were statistically not significant (P = .53). DISCUSSION: The 3DP models are shown to positively impact medical students especially given their limited fund of knowledge in anatomy. It is postulated that the lack of a statistically significant result for the resident physicians was multifactorial, in part because of the small test group sizes introducing noise and nonrepresentative samples, as well as relative simplicity of the 3DP models used with resident physicians, which were below their level of training. More trials are required to evaluate the usefulness of highly customized 3DP models.

Using 3D-Printed Mesh-Like Brain Cortex with Deep Structures for Planning Intracranial EEG Electrode Placement.

Surgical evaluation of medically refractory epilepsy frequently necessitates implantation of multiple intracranial electrodes for the identification of the seizure focus. Knowledge of the individual brain's surface anatomy and deep structures is crucial for planning the electrode implantation. We present a novel method of 3D printing a brain that allows for the simulation of placement of all types of intracranial electrodes. We used a DICOM dataset of a T1-weighted 3D-FSPGR brain MRI from one subject. The segmentation tools of Materialise Mimics 21.0 were used to remove the osseous anatomy from brain parenchyma. Materialise 3-matic 13.0 was then utilized in order to transform the cortex of the segmented brain parenchyma into a mesh-like surface. Using 3-matic tools, the model was modified to incorporate deep brain structures and create an opening in the medial aspect. The final model was then 3D printed as a cerebral hemisphere with nylon material using selective laser sintering technology. The final model was light and durable and reflected accurate details of the surface anatomy and some deep structures. Additionally, standard surgical depth electrodes could be passed through the model to reach deep structures without damaging the model. This novel 3D-printed brain model provides a unique combination of visualizing both the surface anatomy and deep structures through the mesh-like surface while allowing repeated needle insertions. This relatively low-cost technique can be implemented for interdisciplinary preprocedural planning in patients requiring intracranial EEG monitoring and for any intervention that requires needle insertion into a solid organ with unique anatomy and internal targets.