It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
Purpose
Diffusion-weighted MRI is a promising technique to monitor response to treatment in pediatric rhabdomyosarcoma. However, its validation in clinical practice remains challenging. This study aims to investigate how the tumor segmentation strategy can affect the apparent diffusion coefficient (ADC) measured in pediatric rhabdomyosarcoma.
Materials and methods
A literature review was performed in PubMed using search terms relating to MRI and sarcomas to identify commonly applied segmentation strategies. Seventy-six articles were included, and their presented segmentation methods were evaluated. Commonly reported segmentation strategies were then evaluated on diffusion-weighted imaging of five pediatric rhabdomyosarcoma patients to assess their impact on ADC.
Results
We found that studies applied different segmentation strategies to define the shape of the region of interest (ROI)(outline 60%, circular ROI 27%), to define the segmentation volume (2D 44%, multislice 9%, 3D 21%), and to define the segmentation area (excludes edge 7%, excludes other region 19%, specific area 27%, whole tumor 48%). In addition, details of the segmentation strategy are often unreported. When implementing and comparing these strategies on in-house data, we found that excluding necrotic, cystic, and hemorrhagic areas from segmentations resulted in on average 5.6% lower mean ADC. Additionally, the slice location used in 2D segmentation methods could affect ADC by as much as 66%.
Conclusion
Diffusion-weighted MRI studies in pediatric sarcoma currently employ a variety of segmentation methods. Our study shows that different segmentation strategies can result in vastly different ADC measurements, highlighting the importance to further investigate and standardize segmentation.
Key points
Strategies for segmenting sarcoma tumors vary widely throughout literature.
Details of the segmentation strategy are often not reported.
Including necrotic or cystic areas in the segmentation affects diffusion measurements.
Varying the slice of a single-slice segmentation can drastically impact diffusion measurements.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details

1 UMC Utrecht, Image Sciences Institute, Utrecht, The Netherlands (GRID:grid.7692.a) (ISNI:0000000090126352); Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands (GRID:grid.487647.e)
2 Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands (GRID:grid.487647.e)
3 Amsterdam UMC Location University of Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands (GRID:grid.7177.6) (ISNI:0000000084992262)
4 Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands (GRID:grid.487647.e); Wilhelmina Children’s Hospital UMC Utrecht, Department of Radiology and Nuclear Medicine, Utrecht, The Netherlands (GRID:grid.417100.3) (ISNI:0000 0004 0620 3132)
5 UMC Utrecht, Image Sciences Institute, Utrecht, The Netherlands (GRID:grid.7692.a) (ISNI:0000000090126352)
6 UMC Utrecht, Image Sciences Institute, Utrecht, The Netherlands (GRID:grid.7692.a) (ISNI:0000000090126352); UMC Utrecht Brain Center, UMCUtrecht, Department of Neurology, Utrecht, The Netherlands (GRID:grid.7692.a) (ISNI:0000000090126352)