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Computerized characterization of prostate cancer by fractal analysis in MR images

โœ Scribed by Dongjiao Lv; Xuemei Guo; Xiaoying Wang; Jue Zhang; Jing Fang


Publisher
John Wiley and Sons
Year
2009
Tongue
English
Weight
639 KB
Volume
30
Category
Article
ISSN
1053-1807

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โœฆ Synopsis


Abstract

Purpose

To explore the potential of computerized characterization of prostate MR images by extracting the fractal features of texture and intensity distributions as indices in the differential diagnosis of prostate cancer.

Materials and Methods

MR T2โ€weighted images (T2WI) of 55 patients with pathologic results detected by ultrasound guided biopsy were collected and then divided in two groups, 27 with prostate cancer (PCa) and 28 with no histological abnormality. Texture fractal dimension (TFD) and histogram fractal dimension (HFD) were calculated to analyze complexity features of regions of Interest (ROIs) selected from the peripheral zone. Twoโ€sample tโ€tests were performed to evaluate group differences for both parameters. Receiver operating characteristic (ROC) analysis was used to estimate the performance of TFD and HFD for discriminating PCa.

Results

Significant differences were found in both TFD and HFD between the two patient groups. The areas under the ROC curves of TFD and HFD were 0.691 and 0.966, respectively, in distinguishing prostatic carcinoma from normal peripheral zone. As characterized by the fractal indices, cancerous prostatic tissue exhibited smoother texture and lower variation in intensity distribution than normal prostatic tissue.

Conclusion

The study suggests that TFD and HFD depict the changes in texture and intensity distribution associated with prostate cancer on T2WI. Both TFD and HFDprovide promising quantitative indices for cancer identification. HFD performs better than TFD offering a more robust MRโ€based indicator in the diagnosis of prostatic carcinoma. J. Magn. Reson. Imaging 2009;30:161โ€“168. ยฉ 2009 Wileyโ€Liss, Inc.


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