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Related Experiment Video

Updated: Sep 27, 2025

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
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Quantifying Tumor Heterogeneity from Multiparametric Magnetic Resonance Imaging of Prostate Using Texture Analysis.

Saleh T Alanezi1,2, Frank Sullivan3,4, Christoph Kleefeld2

  • 1Physics Department, Faculty of Science, Northern Border University, Arar 1321, Saudi Arabia.

Cancers
|April 12, 2022
PubMed
Summary
This summary is machine-generated.

Texture analysis of multiparametric MRI (mp-MRI) can identify prostate cancer (PCa) heterogeneity. ADC skewness with a 6x6 px filter effectively distinguishes significant PCa, offering a non-invasive diagnostic approach.

Keywords:
heterogeneitymultiparametric MRI (mp-MRI)prostate cancerprostatectomytexture analysis

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Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Multiparametric MRI (mp-MRI) is crucial for prostate cancer (PCa) management.
  • Current methods like biopsy have limitations in detecting tumor heterogeneity.
  • A non-invasive technique for assessing tumor heterogeneity is needed.

Purpose of the Study:

  • To identify tumor heterogeneity in PCa using texture analysis (TA) on mp-MRI.
  • To evaluate the diagnostic accuracy of TA in distinguishing tumor from non-tumor regions.

Main Methods:

  • Eighteen PCa patients underwent pre-prostatectomy mp-MRI.
  • Regions of interest (ROIs) were defined by matching histopathology to MRI slices.
  • First-order statistics (skewness, kurtosis, entropy) were calculated for TA.
  • The Mann-Whitney U test and ROC-AUC analysis were used for comparisons.

Main Results:

  • ADC skewness with a 6x6 px filter showed significant diagnostic accuracy (ROC-AUC = 0.82, p=0.001).
  • ADC skewness with a 9x9 px filter had lower accuracy (ROC-AUC = 0.66, p=0.08).
  • Entropy and kurtosis analyses did not show significant diagnostic performance.

Conclusions:

  • Texture analysis of ADC skewness with a 6x6 px filter can distinguish significant prostate cancer.
  • Entropy and kurtosis are not effective for PCa diagnosis using this method.
  • ADC skewness offers a promising non-invasive approach for assessing PCa heterogeneity.