Surgeon accuracy and interrater reliability when interpreting CT scans after ventral hernia repair

Parnell, Kaela E.; Beffa, Lucas; Petro, Clayton C.; Krpata, David M.; Prabhu, Ajita S.; Rosen, Michael J.

doi:10.1007/s10029-022-02710-x

Cited by 2 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[35][36][37][38] Moreover, visually inspecting or manually assessing hemoperitoneum CT scans is vulnerable to intra-and interrater disparities, arbitrary imprecisions, and misinterpretations, all while consuming valuable time. [39][40][41][42] In light of these limitations, there is a clear need for more advanced and accurate approaches to address the complexities of hemoperitoneum diagnosis and segmentation.…”

Section: Existing Solutions and Challenges To Hemoperitoneum Diagnosismentioning

confidence: 99%

Hemoperitoneum Quantification in Non-contrast CT: Evaluating Feasibility with the Novel HUVAO Segmentation Algorithm

Bhagawati,

Hazarika,

Gupta

et al. 2024

Journal of Gastrointestinal and Abdominal Radiology

View full text Add to dashboard Cite

Background Injuries involving substantial bleeding, frequently encountered in victims of road traffic accidents, pose a significant risk to mortality. For abdominal trauma cases, accurately assessing internal bleeding and hematomas becomes crucial. Detecting hemoperitoneum, which indicates both blood loss and organ damage in the abdominal cavity, requires precise evaluation. Timely diagnosis and quantification of hemoperitoneum following road accidents are crucial during the critical golden hour, enabling prioritized medical intervention and potentially saving lives while enhancing overall patient care. However, achieving precise hemoperitoneum quantification in abdominal trauma faces challenges due to the intricate nature of overlapping Hounsfield unit (HU) regions. Methods In this feasibility study, we sought to assess the efficacy of the novel HUVAO (Hounsfield Unit-based Volume quantification of Asymmetrical Objects) segmentation algorithm for quantifying hemoperitoneum in thoracoabdominal non-contrast computed tomography (CT) images. Using 28 retrospective non-contrast CT scans of thoracoabdominal regions from trauma patients, we analyzed crucial imaging data without necessitating additional scans or contrast-enhanced procedures. The study aimed to compare HUVAO against classical algorithms and visual estimations by trained radiologists for hemoperitoneum segmentation in thoracoabdominal non-contrast CT images. Results Our findings revealed that although the technical feasibility of employing HUVAO and other segmentation algorithms for hemoperitoneum quantification is evident, the outcomes derived from these algorithms display notable discrepancies. Conclusion In assessing technical feasibility, we introduced the HUVAO segmentation algorithm for hemoperitoneum quantification, comparing its performance against classical segmentation algorithms and visual estimations from trained radiologists. While our results affirm the technical feasibility of HUVAO for this purpose, the observed variations underscore the task's inherent complexity. This emphasizes the limitations of relying solely on HU-based detection, advocating for integration with clinical data. This insight urges exploration of advanced techniques to boost accuracy and elevate patient care standards.

show abstract

Section: Existing Solutions and Challenges To Hemoperitoneum Diagnosismentioning

confidence: 99%

Hemoperitoneum Quantification in Non-contrast CT: Evaluating Feasibility with the Novel HUVAO Segmentation Algorithm

Bhagawati,

Hazarika,

Gupta

et al. 2024

Journal of Gastrointestinal and Abdominal Radiology

View full text Add to dashboard Cite

show abstract

Can surgeons accurately identify mesh type when interpreting computed tomography scans after ventral hernia repair?

Messer,

Melland,

Miller

et al. 2024

Hernia

View full text Add to dashboard Cite

Surgeon accuracy and interrater reliability when interpreting CT scans after ventral hernia repair

Cited by 2 publications

References 9 publications

Hemoperitoneum Quantification in Non-contrast CT: Evaluating Feasibility with the Novel HUVAO Segmentation Algorithm

Hemoperitoneum Quantification in Non-contrast CT: Evaluating Feasibility with the Novel HUVAO Segmentation Algorithm

Can surgeons accurately identify mesh type when interpreting computed tomography scans after ventral hernia repair?

Contact Info

Product

Resources

About