The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Prostate Cancer Aggressiveness: Assessment with Whole-Lesion Histogram Analysis of the Apparent Diffusion Coefficient
Abstract
PURPOSE: To evaluate the relationship between prostate cancer aggressiveness and histogram-derived apparent diffusion coefficient (ADC) parameters obtained from whole-lesion assessment of diffusion-weighted magnetic resonance (MR) imaging of the prostate and to determine which ADC metric may help best differentiate low-grade from intermediate- or high-grade prostate cancer lesions. MATERIALS AND METHODS: The institutional review board approved this retrospective HIPAA-compliant study of 131 men (median age, 60 years) who underwent diffusion-weighted MR imaging before prostatectomy for prostate cancer. Clinically significant tumors (tumor volume > 0.5 mL) were identified at whole-mount step-section histopathologic examination, and Gleason scores of the tumors were recorded. A volume of interest was drawn around each significant tumor on ADC maps. The mean, median, and 10th and 25th percentile ADCs were determined from the whole-lesion histogram and correlated with the Gleason score by using the Spearman correlation coefficient (ρ). The ability of each parameter to help differentiate tumors with a Gleason score of 6 from those with a Gleason score of at least 7 was assessed by using the area under the receiver operating characteristic curve (Az). RESULTS: In total, 116 clinically significant lesions (89 in the peripheral zone, 27 in the transition zone) were identified in 85 of the 131 patients (65%). Forty-six patients did not have a clinically significant lesion. For mean ADC, median ADC, 10th percentile ADC, and 25th percentile ADC, the Spearman ρ values for correlation with Gleason score were -0.31, -0.30, -0.36, and -0.35, respectively, whereas the Az values for differentiating lesions with a Gleason score of 6 from those with a Gleason score of at least 7 were 0.704, 0.692, 0.758, and 0.723, respectively. The Az of 10th percentile ADC was significantly higher than that of the mean ADC for all lesions and peripheral zone lesions (P = .0001). CONCLUSION: When whole-lesion histograms were used to derive ADC parameters, 10th percentile ADC correlated with Gleason score better than did other ADC parameters, suggesting that 10th percentile ADC may prove to be optimal for differentiating low-grade from intermediate- or high-grade prostate cancer with diffusion-weighted MR imaging.
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Cites
ESUR prostate MR guidelines 2012
Barentsz, J. O., Richenberg, J., Clements, R., Choyke, P., Verma, S., Villeirs, G., Rouviere, O., Logager, V., & Fütterer, J. J. (2012) · European Radiology · doi:10.1007/s00330-011-2377-y · Cited by 2,438
McNeal, J. E., Redwine, E. A., Freiha, F. S., & Stamey, T. A. (1988) · The American Journal of Surgical Pathology · doi:10.1097/00000478-198812000-00001 · Cited by 1,182
Calculating correlation coefficients with repeated observations: Part 2—correlation between subjects
Bland, J. M., & Altman, D. G. (1995) · BMJ · doi:10.1136/bmj.310.6980.633 · Cited by 1,082
Hambrock, T., Somford, D. M., Huisman, H. J., van Oort, I. M., Witjes, J. A., Hulsbergen-van de Kaa, C. A., Scheenen, T., & Barentsz, J. O. (2011) · Radiology · doi:10.1148/radiol.11091409 · Cited by 572
Vargas, H. A., Akin, O., Franiel, T., Mazaheri, Y., Zheng, J., Moskowitz, C., Udo, K., Eastham, J., & Hricak, H. (2011) · Radiology · doi:10.1148/radiol.11102066 · Cited by 402
Self-citationFocal therapy for localised unifocal and multifocal prostate cancer: a prospective development study
Ahmed, H. U., Hindley, R. G., Dickinson, L., Freeman, A., Kirkham, A. P., Sahu, M., Scott, R., Allen, C., Van der Meulen, J., & Emberton, M. (2012) · The Lancet Oncology · doi:10.1016/s1470-2045(12)70121-3 · Cited by 397
Turkbey, B., Shah, V. P., Pang, Y., Bernardo, M., Xu, S., Kruecker, J., Locklin, J., Baccala, A. A., Rastinehad, A. R., Merino, M. J., et al. (2011) · Radiology · doi:10.1148/radiol.10100667 · Cited by 389
Walsh, P. C., DeWeese, T. L., & Eisenberger, M. A. (2007) · New England Journal of Medicine · doi:10.1056/nejmcp0706784 · Cited by 321
Peng, Y., Jiang, Y., Yang, C., Brown, J. B., Antic, T., Sethi, I., Schmid-Tannwald, C., Giger, M. L., Eggener, S. E., & Oto, A. (2013) · Radiology · doi:10.1148/radiol.13121454 · Cited by 250
Oto, A., Yang, C., Kayhan, A., Tretiakova, M., Antic, T., Schmid-Tannwald, C., Eggener, S., Karczmar, G. S., & Stadler, W. M. (2011) · American Journal of Roentgenology · doi:10.2214/ajr.11.6861 · Cited by 242
Cited by
Fütterer, J. J., Briganti, A., De Visschere, P., Emberton, M., Giannarini, G., Kirkham, A., Taneja, S. S., Thoeny, H., Villeirs, G., & Villers, A. (2015) · European Urology · doi:10.1016/j.eururo.2015.01.013 · Cited by 785
Wibmer, A., Hricak, H., Gondo, T., Matsumoto, K., Veeraraghavan, H., Fehr, D., Zheng, J., Goldman, D., Moskowitz, C., Fine, S. W., et al. (2015) · European Radiology · doi:10.1007/s00330-015-3701-8 · Cited by 391
Self-citationShukla‐Dave, A., Obuchowski, N. A., Chenevert, T. L., Jambawalikar, S., Schwartz, L. H., Malyarenko, D., Huang, W., Noworolski, S. M., Young, R. J., Shiroishi, M. S., et al. (2019) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.26518 · Cited by 389
Vignati, A., Mazzetti, S., Giannini, V, Russo, F., Bollito, E., Porpiglia, F., Stasi, M., & Regge, D. (2015) · Physics in Medicine & Biology · doi:10.1088/0031-9155/60/7/2685 · Cited by 122
Metadata
- Authors
- Donati, O. F., Mazaheri, Y., Afaq, A., Vargas, H. A., Zheng, J., Moskowitz, C. S., Hricak, H., & Akin, O.
- Venue
- Radiology
- Published
- 2014-04
- Volume
- 271
- Issue
- 1
- Pages
- 143-152
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- OpenAlex
- W2121642414
- Cited by
- 295
- References
- 11
- FWCI
- 27.90
- Type
- journal article
- Language
- en
- Open access
- closed
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- Donati, O. F., Mazaheri, Y., Afaq, A., Vargas, H. A., Zheng, J., Moskowitz, C. S., Hricak, H., & Akin, O. (2014). Prostate Cancer Aggressiveness: Assessment with Whole-Lesion Histogram Analysis of the Apparent Diffusion Coefficient. Radiology. https://doi.org/10.1148/radiol.13130973
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