Feasibility study of MIM auto-contouring for head and neck patients that have dental artifact using a metal artifact reduction scan

Introduction Accurate contouring of organs at risk (OARs) is essential in the treatment of head and neck cancer, particularly in patients with metal dental artifacts that can obscure critical structures. The ability to precisely define these OARs is crucial for minimizing radiation exposure to healthy tissues and improving patient outcomes. To address the challenges posed by metal artifacts, Metal Artifact Reduction (MAR) technology, including iterative MAR (IMAR) scanning, has been widely adopted in radiation oncology. Methods This retrospective study evaluated the impact of IMAR scanning and Medical Image Merge (MIM) auto-contouring software on the accuracy and efficiency of contouring OARs in twelve head and neck cancer patients with dental artifacts. Each patient underwent both IMAR and non-IMAR CT scans. Comparisons were made between manually and automatically contoured OARs, focusing on the time required and the dice similarity coefficients. Results Statistical analysis revealed significant differences in dice coefficients among various OARs, with the mandible achieving the highest accuracy and the lips the lowest. However, no significant difference was observed between IMAR and non-IMAR scans regarding contouring accuracy. The use of auto-contouring significantly reduced contouring time across all structures, regardless of the scan type. Conclusion While IMAR scanning effectively reduces metal artifacts, it does not significantly enhance contouring accuracy compared to non-IMAR scans. The study demonstrates that auto-contouring significantly improves efficiency, though contouring accuracy remains dependent on the operator’s skill. Further investigation into optimizing the integration of IMAR scanning with auto-contouring systems is warranted.

Publication Details

Journal
Language arts journal of Michigan
Published
2024-08-14
Primary Topic
Dental Radiography and Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Feasibility study of MIM auto-contouring for head and neck patients that have dental artifact using a metal artifact reduction scan

Language arts journal of Michigan
Dental Radiography and Imaging
article

Feasibility study of MIM auto-contouring for head and neck patients that have dental artifact using a metal artifact reduction scan

article en

Abstract

Introduction Accurate contouring of organs at risk (OARs) is essential in the treatment of head and neck cancer, particularly in patients with metal dental artifacts that can obscure critical structures. The ability to precisely define these OARs is crucial for minimizing radiation exposure to healthy tissues and improving patient outcomes. To address the challenges posed by metal artifacts, Metal Artifact Reduction (MAR) technology, including iterative MAR (IMAR) scanning, has been widely adopted in radiation oncology. Methods This retrospective study evaluated the impact of IMAR scanning and Medical Image Merge (MIM) auto-contouring software on the accuracy and efficiency of contouring OARs in twelve head and neck cancer patients with dental artifacts. Each patient underwent both IMAR and non-IMAR CT scans. Comparisons were made between manually and automatically contoured OARs, focusing on the time required and the dice similarity coefficients. Results Statistical analysis revealed significant differences in dice coefficients among various OARs, with the mandible achieving the highest accuracy and the lips the lowest. However, no significant difference was observed between IMAR and non-IMAR scans regarding contouring accuracy. The use of auto-contouring significantly reduced contouring time across all structures, regardless of the scan type. Conclusion While IMAR scanning effectively reduces metal artifacts, it does not significantly enhance contouring accuracy compared to non-IMAR scans. The study demonstrates that auto-contouring significantly improves efficiency, though contouring accuracy remains dependent on the operator’s skill. Further investigation into optimizing the integration of IMAR scanning with auto-contouring systems is warranted.

Language arts journal of Michigan
Openalex Percentile: Top 48%
Dental Radiography and Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.