Texture Analysis of Fractional Water Content Images Acquired during PET/MRI: Initial Evidence for an Association with Total Lesion Glycolysis, Survival and Gene Mutation Profile in Primary Colorectal Cancer.

Published on May 31, 2021in Cancers6.126
· DOI :10.3390/CANCERS13112715
Balaji Ganeshan32
Estimated H-index: 32
(UCL: University College London),
Kenneth A. Miles56
Estimated H-index: 56
(UCL: University College London)
+ 17 AuthorsAshley M. Groves48
Estimated H-index: 48
(UCL: University College London)
To assess the capability of fractional water content (FWC) texture analysis (TA) to generate biologically relevant information from routine PET/MRI acquisitions for colorectal cancer (CRC) patients. Thirty consecutive primary CRC patients (mean age 63.9, range 42-83 years) prospectively underwent FDG-PET/MRI. FWC tumor parametric images generated from Dixon MR sequences underwent TA using commercially available research software (TexRAD). Data analysis comprised (1) identification of functional imaging correlates for texture features (TF) with low inter-observer variability (intraclass correlation coefficient: ICC > 0.75), (2) evaluation of prognostic performance for FWC-TF, and (3) correlation of prognostic imaging signatures with gene mutation (GM) profile. Of 32 FWC-TF with ICC > 0.75, 18 correlated with total lesion glycolysis (TLG, highest: rs = -0.547, p = 0.002). Using optimized cut-off values, five MR FWC-TF identified a good prognostic group with zero mortality (lowest: p = 0.017). For the most statistically significant prognostic marker, favorable prognosis was significantly associated with a higher number of GM per patient (medians: 7 vs. 1.5, p = 0.009). FWC-TA derived from routine PET/MRI Dixon acquisitions shows good inter-operator agreement, generates biological relevant information related to TLG, GM count, and provides prognostic information that can unlock new clinical applications for CRC patients.
#1Francesco Alessandrino (Harvard University)H-Index: 13
#2Rahul Gujrathi (Harvard University)H-Index: 4
Last. Atul B. Shinagare (Harvard University)H-Index: 28
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#1Paul Riviere (University of California, Berkeley)H-Index: 1
#1Paul Riviere (UCSD: University of California, San Diego)H-Index: 1
Last. Razelle Kurzrock (UCSD: University of California, San Diego)H-Index: 133
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#2Giorgio Maria Agazzi (University of Brescia)H-Index: 6
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#1J. Ferlay (IARC: International Agency for Research on Cancer)H-Index: 18
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#1Martin Lewis (UCL: University College London)H-Index: 3
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#1Takeshi Fukuda (SBU: Stony Brook University)H-Index: 4
#2Mingqian Huang (SBU: Stony Brook University)H-Index: 6
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#1Courtney Tate (Royal Brisbane and Women's Hospital)H-Index: 2
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#1Carole Durot (Reims University)H-Index: 5
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#1Burak KocakH-Index: 13
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