Evaluating the Use of rCBV as a Tumor Grade and Treatment Response Classifier Across NCI Quantitative Imaging Network Sites: Part II of the DSC-MRI Digital Reference Object (DRO) Challenge

被引：10

作者：

Bell, Laura C. ^{[1
]}

Semmineh, Natenael ^{[1
]}

An, Hongyu ^{[2
]}

Eldeniz, Cihat ^{[2
]}

Wahl, Richard ^{[2
]}

Schmainda, Kathleen M. ^{[3
,4
]}

Prah, Melissa A. ^{[4
]}

Erickson, Bradley J. ^{[5
]}

Korfiatis, Panagiotis ^{[5
]}

Wu, Chengyue ^{[6
,7
]}

Sorace, Anna G. ^{[8
]}

Yankeelov, Thomas E. ^{[6
,7
]}

Rutledge, Neal ^{[6
,7
]}

Chenevert, Thomas L. ^{[9
]}

Malyarenko, Dariya ^{[9
]}

Liu, Yichu ^{[10
]}

Brenner, Andrew ^{[10
]}

Hu, Leland S. ^{[11
]}

Zhou, Yuxiang ^{[11
]}

Boxerman, Jerrold L. ^{[12
,13
]}

Yen, Yi-Fen ^{[14
]}

Kalpathy-Cramer, Jayashree ^{[14
]}

Beers, Andrew L. ^{[14
]}

Muzi, Mark ^{[15
]}

Madhuranthakam, Ananth J. ^{[16
]}

Pinho, Marco ^{[16
]}

Johnson, Brian ^{[16
,17
]}

Quarles, C. Chad ^{[1
]}

机构：

[1] Barrow Neurol Inst, Div Neuroimaging Res, Phoenix, AZ 85013 USA

[2] Washington Univ, Mallinckrodt Inst Radiol, St Louis, MO 63110 USA

[3] Med Coll Wisconsin, Dept Radiol, 8700 W Wisconsin Ave, Milwaukee, WI 53226 USA

[4] Med Coll Wisconsin, Dept Biophys, Milwaukee, WI 53226 USA

[5] Mayo Clin, Dept Radiol, Rochester, MN USA

[6] Univ Texas Austin, Oden Inst Computat Engn & Sci, Dept Diagnost Med, Livestrong Canc Inst, Austin, TX 78712 USA

[7] Univ Texas Austin, Oden Inst Computat Engn & Sci, Dept Oncol, Livestrong Canc Inst, Austin, TX 78712 USA

[8] Univ Alabama Birmingham, Dept Radiol, Birmingham, AL USA

[9] Univ Michigan, Dept Radiol, Ann Arbor, MI 48109 USA

[10] UT Hlth San Antonio, San Antonio, TX USA

[11] Mayo Clin, Dept Radiol, Scottsdale, AZ USA

[12] Brown Univ, Dept Diagnost Imaging, Rhode Isl Hosp, Providence, RI 02912 USA

[13] Brown Univ, Alpert Med Sch, Providence, RI 02912 USA

[14] MGH Martinos Ctr Biomed Imaging, Dept Radiol, Boston, MA USA

[15] Univ Washington, Radiol, Seattle, WA 98195 USA

[16] UT Southwestern Med Ctr, Dept Radiol, Dallas, TX USA

[17] Philips Healthcare, Gainesville, FL USA

来源：

TOMOGRAPHY | 2020年 / 6卷 / 02期

关键词：

DSC-MRI; digital reference object; relative cerebral blood volume; standardization; multisite consistency; tumor grading; treatment response; PROGNOSTIC MARKER; CONTRAST; SURVIVAL;

D O I：

10.18383/j.tom.2020.00012

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

We have previously characterized the reproducibility of brain tumor relative cerebral blood volume (rCBV) using a dynamic susceptibility contrast magnetic resonance imaging digital reference object across 12 sites using a range of imaging protocols and software platforms. As expected, reproducibility was highest when imaging protocols and software were consistent, but decreased when they were variable. Our goal in this study was to determine the impact of rCBV reproducibility for tumor grade and treatment response classification. We found that varying imaging protocols and software platforms produced a range of optimal thresholds for both tumor grading and treatment response, but the performance of these thresholds was similar. These findings further underscore the importance of standardizing acquisition and analysis protocols across sites and software benchmarking.

引用

页码：203 / 208

页数：6

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