Ignite Creation Date:
2024-05-06 @ 7:45 PM
Last Modification Date:
2024-10-26 @ 3:13 PM
Study NCT ID:
NCT06126172
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2023-11-13
First Post:
2023-11-06
Brief Title:
Radiomics of Treatment-naive Prostate Cancer Patients on Multiparametric MRI for Risk Stratification and Treatment Outcomes Predictions
Sponsor:
Chang Gung Memorial Hospital
Organization:
Chang Gung Memorial Hospital
Study Overview
Official Title:
Radiomics of Treatment-naive Prostate Cancer Patients on Multiparametric MRI for Risk Stratification and Treatment Outcomes Predictions
Status:
ACTIVE_NOT_RECRUITING
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
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 ie 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 ie 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
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None