Relationship between kurtosis and bi-exponential characterization of high b-value diffusion-weighted imaging: application to prostate cancer.

Autor:	Karunamuni RA; 1 Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA., Kuperman J; 2 Department of Radiology, University of California San Diego, La Jolla, CA, USA., Seibert TM; 1 Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA., Schenker N; 2 Department of Radiology, University of California San Diego, La Jolla, CA, USA., Rakow-Penner R; 2 Department of Radiology, University of California San Diego, La Jolla, CA, USA., Sundar VS; 2 Department of Radiology, University of California San Diego, La Jolla, CA, USA., Teruel JR; 2 Department of Radiology, University of California San Diego, La Jolla, CA, USA., Goa PE; 3 Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway., Karow DS; 2 Department of Radiology, University of California San Diego, La Jolla, CA, USA., Dale AM; 2 Department of Radiology, University of California San Diego, La Jolla, CA, USA., White NS; 2 Department of Radiology, University of California San Diego, La Jolla, CA, USA.
Jazyk:	angličtina
Zdroj:	Acta radiologica (Stockholm, Sweden : 1987) [Acta Radiol] 2018 Dec; Vol. 59 (12), pp. 1523-1529. Date of Electronic Publication: 2018 Apr 17.
DOI:	10.1177/0284185118770889
Abstrakt:	Background: High b-value diffusion-weighted imaging has application in the detection of cancerous tissue across multiple body sites. Diffusional kurtosis and bi-exponential modeling are two popular model-based techniques, whose performance in relation to each other has yet to be fully explored. Purpose: To determine the relationship between excess kurtosis and signal fractions derived from bi-exponential modeling in the detection of suspicious prostate lesions. Material and Methods: This retrospective study analyzed patients with normal prostate tissue (n = 12) or suspicious lesions (n = 13, one lesion per patient), as determined by a radiologist whose clinical care included a high b-value diffusion series. The observed signal intensity was modeled using a bi-exponential decay, from which the signal fraction of the slow-moving component was derived ( SFs). In addition, the excess kurtosis was calculated using the signal fractions and ADCs of the two exponentials ( KCOMP). As a comparison, the kurtosis was also calculated using the cumulant expansion for the diffusion signal ( KCE). Results: Both K and KCE were found to increase with SFs within the range of SFs commonly found within the prostate. Voxel-wise receiver operating characteristic performance of SFs, KCE, and KCOMP in discriminating between suspicious lesions and normal prostate tissue was 0.86 (95% confidence interval [CI] = 0.85 - 0.87), 0.69 (95% CI = 0.68-0.70), and 0.86 (95% CI = 0.86-0.87), respectively. Conclusion: In a two-component diffusion environment, KCOMP is a scaled value of SFs and is thus able to discriminate suspicious lesions with equal precision . KCE provides a computationally inexpensive approximation of kurtosis but does not provide the same discriminatory abilities as SFs and KCOMP.
Databáze:	MEDLINE
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