Clinical trial NCT06126172: Radiomics of Treatment-naive Prostate Cancer Patients on Multiparametric MRI for Risk Stratification and Treatment Outcomes Predictions
Official title: Radiomics of Treatment-naive Prostate Cancer Patients on Multiparametric MRI for Risk Stratification and Treatment Outcomes Predictions
Study type: INTERVENTIONAL
Overall status: ACTIVE_NOT_RECRUITING
Phase: NA
Conditions: Prostate Cancer
Keywords: Prostate cancer
Multiparametric MRI
Radiomics
Risk stratification
Recurrence
Prediction
Lead sponsor: Chang Gung Memorial Hospital
Sponsor class: OTHER
First posted: 2023-11-13
Enrollment: 125
Sex: MALE
Minimum age (years): 20
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: OTHER

Brief summary: Prostate cancers (PCA) are a heterogeneous group which include indolent tumors that has no clinical significance to very aggressive cancer that could result in morbidities and mortality. Thus, an accurate risk stratification at the time of PCA diagnosis is crucial. The histological examination of PCA biopsy specimens could not accurately predict the final tumor aggressiveness shown on radical prostatectomy specimens because of heterogeneous distributions of the most malignant tumor cells. Prostate multiparametric magnetic resonance imaging (mpMRI) has been generally accepted to be the best imaging modality for detecting and localizing prostate cancers themselves. Furthermore, the rapid development of radiomics provide comprehensive quantitative information of all tumor data which could be used for risk stratification and prognosis prediction. Thus, this study plans to enroll 200 eligible patients who undergo prostate mpMRI first, followed by radical prostatectomy for prostate cancers. We use radiomics extracted from prostate mpMRI for risk stratification patients of histological aggressiveness as well as to predict very early recurrence of PCA patients within 6 months after radical prostatectomy.

Detailed description: Prostate cancer is the 2nd most common malignancy in the world as well as the leading cancer in male population in Taiwan. The treatment selections of prostate cancer are limited by the uncertainty of its aggressiveness (i.e.: histological graded) and staging before treatment. Although prostate mpMRI has much better ability for detection and localization of prostate cancers than other imaging modalities and diagnostic tests, there is still gap for risk stratifications and treatment selection based on prostate mpMRI findings. Thus, a robust radiomics prediction models based on imaging biomarkers on prostate mpMRI with high prediction accuracy could fill the gap of misclassification of risk stratifications of prostate cancers, guides treatment selections and providing monitoring schedules for treated patients as well as early timely additional treatments (i.e.: target therapy or immunotherapy) for patients with high risk of early recurrence. Furthermore, radiomics could provide consistent information which help in decreasing interobserver and intra-observer variability of interpretating prostate cancer even in the use of PIRADS. In this way, this would save the fee of inappropriate or ineffective treatment and avoid unnecessary time and cost of monitoring low risk patients as well as improve patients' survivals and possibly life-quality as well.

Eligibility criteria: Inclusion Criteria:

1. Aged over 20 years old.
2. Suspected or confirmed prostate cancer.
3. Undergoing prostate mpMRI before clinical treatment.
4. Normal renal function(i.e.: estimated GFR ≧60).
5. No allergy history to gadolinium based contrast agent.
6. Agree to participate this study and sign informed consent.

Exclusion Criteria:

1. mpMRI photography not completed.
2. mpMRI images are damaged or poor in quality and cannot be interpreted.
3. Without pathological examination confirmed prostate cancer.
4. Patient withdraw informed consent.

Primary outcomes:
measure: MR characteristics assessment-T2WI
timeFrame: 1.5 year
measure: MR characteristics assessment- DWI
timeFrame: 1.5 year
measure: MR characteristics assessment- ADC
timeFrame: 1.5 year
Secondary outcomes:
Other outcomes:
Locations:
city: Taoyuan
country: Taiwan
facility: Li-Jen Wang
Study officials:
affiliation: Chang Gung Memorial Hospital
name: Li-Jen Wang, M.D., M.P.H.
role: PRINCIPAL_INVESTIGATOR
References: