Ignite Creation Date:
2025-12-26 @ 10:59 AM
Ignite Modification Date:
2025-12-31 @ 8:37 PM
Study NCT ID:
NCT05252806
Status:
UNKNOWN
Last Update Posted:
2022-06-22
First Post:
2022-02-08
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Quantitative mpMRI to Predict Metastatic Potential of Prostate Cancer
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D011471', 'term': 'Prostatic Neoplasms'}, {'id': 'D008207', 'term': 'Lymphatic Metastasis'}], 'ancestors': [{'id': 'D005834', 'term': 'Genital Neoplasms, Male'}, {'id': 'D014565', 'term': 'Urogenital Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D005832', 'term': 'Genital Diseases, Male'}, {'id': 'D000091662', 'term': 'Genital Diseases'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D011469', 'term': 'Prostatic Diseases'}, {'id': 'D052801', 'term': 'Male Urogenital Diseases'}, {'id': 'D009362', 'term': 'Neoplasm Metastasis'}, {'id': 'D009385', 'term': 'Neoplastic Processes'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'CASE_ONLY'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 30}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2022-07', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-02', 'completionDateStruct': {'date': '2023-03', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2022-06-18', 'studyFirstSubmitDate': '2022-02-08', 'studyFirstSubmitQcDate': '2022-02-22', 'lastUpdatePostDateStruct': {'date': '2022-06-22', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-02-23', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2022-12', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'optimal combination of quantitative MRI parameters that best correlates to the presence of (lymph node) metastases in prostate cancer as seen on PSMA-PET/CT.', 'timeFrame': 'within 14 days of PSMA-PET/CT scan, before any therapy', 'description': 'To find the optimal combination of quantitative parameters for discriminating between positive and negative PSMA-PET/CT, logistic regression modelling will be used. The performance of the model will be evaluated using receiver operating characteristic curve analysis.'}], 'secondaryOutcomes': [{'measure': 'the performance of individual quantitative MRI parameters discriminating localized from (oligo-)metastatic disease', 'timeFrame': 'within 14 days of PSMA-PET/CT scan, before any therapy', 'description': 'To test the individual quantitative MRI parameters for a significant difference between localized and (oligo-)metastatic disease, non-parametric tests for independent groups (Mann-Whitney U test) will be used. The ability of each parameter to discriminate between positive and negative PSMA-PET/CT is assessed using receiver operating characteristic curve analysis, which allows comparison to the logistic regression model performance.'}, {'measure': 'MR parameters that correlate to the amount of metastases as found on PSMA-PET/CT', 'timeFrame': 'within 14 days of PSMA-PET/CT scan, before any therapy', 'description': 'Participants with a positive PET/CT scan result will be divided in groups according to the number of positive lymph nodes detected (if variance within participants allows). To test for significant differences between these groups for each of the quantitative parameters, the non-parametric tests for multiple independent groups (Kruskal Wallis) will be used.'}, {'measure': 'MR parameters that correlate to local prostate PSMA-PET intensity', 'timeFrame': 'within 14 days of PSMA-PET/CT scan, before any therapy', 'description': 'To test for a correlation between the quantitative parameters and the local prostate PSMA-PET intensity, a spearmans rho test for correlation between two continuous variables will be used.'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Multiparametric Magnetic Resonance Imaging', 'Lymphatic Metastasis'], 'conditions': ['Prostate Cancer']}, 'descriptionModule': {'briefSummary': 'The primary aim of this study is to assess the potential of quantitative MRI measurements to predict localized prostate cancer T-stage and disease spread to nodes (N-stage) by correlating quantitative MRI measurements of the local prostate to the presence of metastases as seen on PSMA-PET/CT.', 'detailedDescription': 'Patients diagnosed with prostate cancer will likely not die from the primary tumor, but from (extended) metastatic disease. One of the first steps towards extended metastatic disease is the presence of lymph node metastases, which is an important factor in determining therapy and prognosis. Although historically all patients with lymph node metastases are considered incurable, research has shown that patients with only a limited number of small (\\<8 mm) nodal metastases have a better prognosis as compared to patients with more extensive involvement. In patients with only a limited number of small nodal metastases (oligo-metastatic), therapy with curative intent might be pursued, e.g. by surgical resection or loco-regional radiotherapy. With continuously improving opportunities to very selectively treat small numbers of metastatic sites it is of utmost importance to accurately diagnose the first signs of oligo-metastatic disease and to define its extent.\n\nIt is hypothesized that magnetic resonance imaging (MRI) can obtain more information from the local prostate than what is now used in the clinic to stage localized prostate cancer and oligo-metastatic disease. In recent years positron emission tomography (PET) in combination with computerized tomography (CT) and Prostate Specific Membrane Antigen (PSMA) tracers (PSMA-PET/CT) has emerged as an imaging modality to visualize (early) metastatic disease, but its accuracy in detecting oligo-metastatic spread is unknown, as small nodal metastases can be missed. In this study, the correlation is assessed between functional, quantitative and metabolic local tumor characteristics with PSMA-PET/CT-proven nodal involvement, to be able to predict metastatic potential from quantitative MRI parameters of the localized tumor. If the study shows potential for predicting presence of metastatic disease, future patients will benefit from improved nodal staging, potentially leading to more accurate and personalized treatment of the correct disease stage.'}, 'eligibilityModule': {'sex': 'MALE', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '50 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients, diagnosed with prostate cancer by prostate biopsy and having a high risk of nodal metastases, will be recruited at the Radboudumc in Nijmegen. This research population will be a suitable reflection of the potential patient group who will eventually benefit from this new diagnostic mpMRI approach, in case the results match the hypothesis. Characteristics of this group will comprise all men with an expected age in the range of 50-75 years.\n\nPatients will be informed about the ongoing study by their treating physician. Patients will receive the patient information folder and will be contacted by one of the researchers. Upon approval, informed consent paperwork will be handed.', 'healthyVolunteers': False, 'eligibilityCriteria': "Inclusion Criteria:\n\n* Histologically proven primary cancer of the prostate, based on prostate biopsy-core analysis.\n* Patient is scheduled and fit for PSMA-PET/CT\n* Ageā„50 years. Ability to give voluntary written informed consent to participate in this study.\n\nExclusion Criteria:\n\n* Contraindication for MRI-scanning, i.e. claustrophobia, intracranial metal clips, metallic bodies in the eye, implanted electric and electronic devices not eligible for MRI (pacemakers, insulin pumps, cochlear implants, neurostimulators).\n* Prior prostate cancer treatment.\n* Prior pelvic surgery, associated with pelvic lymphadenopathy\n* Presence of any medical condition that in the opinion of the investigator/treating physician will affect patients' clinical status by participating in this trial.\n* Inability to lie still for 45 minutes or comply with imaging.\n* The patient is already enrolled in one or more concurrent studies, which could confound the results of this study, according to the investigators."}, 'identificationModule': {'nctId': 'NCT05252806', 'acronym': 'QmpMRI', 'briefTitle': 'Quantitative mpMRI to Predict Metastatic Potential of Prostate Cancer', 'organization': {'class': 'OTHER', 'fullName': 'Radboud University Medical Center'}, 'officialTitle': 'Quantitative mpMRI to Predict Metastatic Potential of Prostate Cancer', 'orgStudyIdInfo': {'id': 'NL77789.091.21'}}, 'armsInterventionsModule': {'interventions': [{'name': 'MRI examination of the prostate', 'type': 'DIAGNOSTIC_TEST', 'description': 'Participants will undergo one MRI examination of approximately 45 minutes including an intramuscular injection with an antispasmodic agent to minimize bowel movement'}]}, 'contactsLocationsModule': {'locations': [{'city': 'Nijmegen', 'country': 'Netherlands', 'contacts': [{'name': 'Carlijn Tenbergen', 'role': 'CONTACT', 'email': 'carlijn.tenbergen@radboudumc.nl'}], 'facility': 'Radboud university medical centre', 'geoPoint': {'lat': 51.8425, 'lon': 5.85278}}], 'centralContacts': [{'name': 'Carlijn Tenbergen', 'role': 'CONTACT', 'email': 'carlijn.tenbergen@radboudumc.nl', 'phone': '+31 24 36 52285'}, {'name': 'Tom Scheenen, Prof. Dr.', 'role': 'CONTACT', 'email': 'tom.scheenen@radboudumc.nl', 'phone': '+31 24 36 13157'}], 'overallOfficials': [{'name': 'Tom Scheenen', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Radboud University Medical Center'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Radboud University Medical Center', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}