Radiomics features from multiparametric MRI exams can predict prostate cancer metastases: Study

Written By :  Medha Baranwal
Medically Reviewed By :  Dr. Kamal Kant Kohli
Published On 2022-06-02 14:30 GMT   |   Update On 2022-06-02 14:30 GMT

USA: A recent study revealed that radiomics features extracted from multiparametric MRI exams can help to predict prostate cancer metastatic risk. The study findings, presented at the International Society for Magnetic Resonance in Medicine (ISMRM) meeting held in London, U.K. imply how prostate cancer circulating tumor cells negatively affect patient outcomes. 

"Circulating tumor cells are cancer cells detectable in the peripheral blood released by the tumor," , presenter Mohammad Alhusseini, PhD, of the University of Miami Miller School of Medicine in Florida said. "[They] constitute seeds for subsequent growth of additional tumor metastases, triggering a mechanism that is responsible for many cancer-related deaths."

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The team explained that the number of circulating tumor cells (CTCs) is an indicator of metastatic risk in prostate cancer and is a meaningful biomarker. "Quantitative multiparametric MRI features in prostate cancer are associated with tumor aggressiveness," Alhusseini said.

The researchers aimed to explore any links between radiomic features from multiparametric MRI of the prostate and circulating tumor cell counts in 73 prostate cancer patients. They developed and trained a neural network algorithm to predict circulating tumor cell counts (with a threshold of five or more CTCs indicating risk of metastatic disease). 100 training and testing runs of five-fold cross-validation were conducted by the team, measuring results using the area under the receiver operating curve (AUC). 

The following radiomics features were used to train the algorithm:

  • T-onset -- time of onset of the contrast wash-in
  • T2 intensity, 50%
  • Higher tumor volume, measured by a tool the group developed for the algorithm called the Habitat Risk Score 6 (HRS6), which is based on a one to 10 scale.
  • Apparent diffusion coefficient (ADC) intensity skewness
  • ADC contrast mean
  • ADC contrast kurtosis
  • B-value intensity

Blood collection was done from study participants enrolled in two trials: one an "active surveillance" trial and another a randomized radiotherapy trial that investigated the effects of an MRI-guided prostate radiotherapy treatment. The patients underwent multiparametric MRI (including axial T2-weighted MRI, diffusion-weighted imaging [DWI] and dynamic contrast-enhanced [DCE]-MRI exams) and MRI-ultrasound fusion biopsy. Blood draws was used to assess the amount of circulating tumor cells. 

The findings of the study were as follows:

  • In the active surveillance trial arm, the mean circulating tumor count per 7.5 mL of blood was 19. In the radiotherapy trial arm, the median circulating tumor count in 7.5 mL of blood was 74.
  • Using the seven features, the team found an average AUC of 0.769 for a connection with higher CTC counts and adverse effects; of the seven, HRS6, lower T2 intensity measurements, and time of onset were the top three, with an AUC of 0.834.

The group conclude, "this is the first study to the best of our knowledge to model CTC counts with in vivo multiparametric MRI radiomics. Magnetic resonance imaging radiomics features are promising markers of prostate cancer metastatic risk." 


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Article Source : ISMRM meeting

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