Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D015179', 'term': 'Colorectal Neoplasms'}], 'ancestors': [{'id': 'D007414', 'term': 'Intestinal Neoplasms'}, {'id': 'D005770', 'term': 'Gastrointestinal Neoplasms'}, {'id': 'D004067', 'term': 'Digestive System Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D004066', 'term': 'Digestive System Diseases'}, {'id': 'D005767', 'term': 'Gastrointestinal Diseases'}, {'id': 'D003108', 'term': 'Colonic Diseases'}, {'id': 'D007410', 'term': 'Intestinal Diseases'}, {'id': 'D012002', 'term': 'Rectal Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'OTHER', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 100}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-03-24', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-04', 'completionDateStruct': {'date': '2028-03-24', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-05-05', 'studyFirstSubmitDate': '2024-12-23', 'studyFirstSubmitQcDate': '2024-12-23', 'lastUpdatePostDateStruct': {'date': '2025-05-09', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-12-31', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2028-03-24', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'PCD-CT predictor of response to treatment in patients candidate to chemotherapy', 'timeFrame': '3 years'}, {'measure': 'The non-inferiority of PCD-CT compared to MRI in identifying liver metastases from colorectal cancer', 'timeFrame': '3 years'}], 'secondaryOutcomes': [{'measure': 'the utility of machine learning-driven texture analysis in detecting prognostic imaging biomarkers for liver metastasis survival, with predictive performance measured by the concordance index.', 'timeFrame': '3 years'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Colorectal Cancer']}, 'referencesModule': {'references': [{'pmid': '38230766', 'type': 'BACKGROUND', 'citation': 'Siegel RL, Giaquinto AN, Jemal A. Cancer statistics, 2024. CA Cancer J Clin. 2024 Jan-Feb;74(1):12-49. doi: 10.3322/caac.21820. Epub 2024 Jan 17.'}, {'pmid': '33200074', 'type': 'BACKGROUND', 'citation': 'Martin J, Petrillo A, Smyth EC, Shaida N, Khwaja S, Cheow HK, Duckworth A, Heister P, Praseedom R, Jah A, Balakrishnan A, Harper S, Liau S, Kosmoliaptsis V, Huguet E. Colorectal liver metastases: Current management and future perspectives. World J Clin Oncol. 2020 Oct 24;11(10):761-808. doi: 10.5306/wjco.v11.i10.761.'}, {'pmid': '15044747', 'type': 'BACKGROUND', 'citation': 'Soyer P, Poccard M, Boudiaf M, Abitbol M, Hamzi L, Panis Y, Valleur P, Rymer R. Detection of hypovascular hepatic metastases at triple-phase helical CT: sensitivity of phases and comparison with surgical and histopathologic findings. Radiology. 2004 May;231(2):413-20. doi: 10.1148/radiol.2312021639. Epub 2004 Mar 24.'}, {'pmid': '24509207', 'type': 'BACKGROUND', 'citation': 'Sahani DV, Bajwa MA, Andrabi Y, Bajpai S, Cusack JC. Current status of imaging and emerging techniques to evaluate liver metastases from colorectal carcinoma. Ann Surg. 2014 May;259(5):861-72. doi: 10.1097/SLA.0000000000000525.'}, {'pmid': '26883327', 'type': 'BACKGROUND', 'citation': 'Vilgrain V, Esvan M, Ronot M, Caumont-Prim A, Aube C, Chatellier G. A meta-analysis of diffusion-weighted and gadoxetic acid-enhanced MR imaging for the detection of liver metastases. Eur Radiol. 2016 Dec;26(12):4595-4615. doi: 10.1007/s00330-016-4250-5. Epub 2016 Feb 16.'}, {'pmid': '25088350', 'type': 'BACKGROUND', 'citation': 'Wang Q, Shi G, Qi X, Fan X, Wang L. Quantitative analysis of the dual-energy CT virtual spectral curve for focal liver lesions characterization. Eur J Radiol. 2014 Oct;83(10):1759-64. doi: 10.1016/j.ejrad.2014.07.009. Epub 2014 Jul 22.'}]}, 'descriptionModule': {'briefSummary': 'Colorectal cancer is the first leading cause of cancer death in men and second in women. Its incidence rates also increased by 1%-2% annually in young adults (ages \\<55 years). The liver is the most common site of colorectal cancer metastasis, with approximately 25% 50% of patients developing liver metastases during the disease. Maximising resection of liver metastasis using all available techniques remains a key objective and provides the best chance of long-term survival and cure. For unresectable patients, optimal systemic and locoregional chemotherapeutic, biological and radiotherapeutic treatments improve survival, and may convert initially unresectable patients to operability. Computed Tomography is currently the modality of choice for patients staging and restaging for high spatial resolution providing accurate delineation of lesion, vascular structure and relation with surrounding structure. The portal venous phase (approximately 60-70 s after administration of contrast agent) is the most reliable phase for detection of liver metastasis with a detection rate of 85% with lower performance for lesion \\<1 cm which are interpreted as too small to characterize. Compared to computed tomography, MRI has superior soft tissue contrast and the possibly of a multiparametric characterization of lesion thanks to the evaluation of diffusivity and the uptake of hepatospecific contrast media, resulting in higher accuracy also for lesion smaller than \\< 10 mm. Photon-counting detector computed tomography (PCD-CT), used as standard clinical practice, by employing a reduced radiation dose, allows the acquisition of ultra-high resolution images (up to 169 microns) and spectral information, with a high detection rate of liver metastases and their characterization.\n\nTherefore, aim of the present study is to evaluate the value of PCD-CT in the detection of liver metastasis from colorectal cancer in comparison to MRI as reference standard.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '100 Years', 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': '100 patients with colorectal cancer and liver metastasis', 'eligibilityCriteria': 'Inclusion Criteria:\n\n* adult (\\>18 years)\n* non- biopsy-proven colon/colorectal carcinoma\n* CT performed on a PCD-CT\n* MRI with multiparametric protocol and hepatospecific contrast media\n\nExclusion Criteria:\n\n* pregnancy and breastfeeding\n* CT exam performed on a scan different from PCD-CT\n* absence of multiparametric MRI\n* MRI with non hepatospecific contrast agent\n* Absent informed consent signed'}, 'identificationModule': {'nctId': 'NCT06753903', 'acronym': 'PCDCRC-D34H', 'briefTitle': 'Role of Photon Counting CT in Detecting Liver Metastatis From Colorectal Cancer', 'organization': {'class': 'OTHER', 'fullName': 'IRCCS San Raffaele'}, 'officialTitle': 'Role of Photon Counting CT in Detecting Liver Metastatis From Colorectal Cancer', 'orgStudyIdInfo': {'id': 'PCDCRC-D34H'}}, 'armsInterventionsModule': {'interventions': [{'name': 'PCD-CT', 'type': 'PROCEDURE', 'description': 'Photon-counting detector computed tomography'}]}, 'contactsLocationsModule': {'locations': [{'zip': '20132', 'city': 'Milan', 'status': 'RECRUITING', 'country': 'Italy', 'contacts': [{'name': 'Antonio Esposito', 'role': 'CONTACT', 'phone': '02 2643 6102'}], 'facility': 'IRCCS San Raffaele', 'geoPoint': {'lat': 45.46427, 'lon': 9.18951}}], 'centralContacts': [{'name': 'Antonio Esposito, MD', 'role': 'CONTACT', 'email': 'esposito.antonio@hsr.it', 'phone': '0226436102'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'IRCCS San Raffaele', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Professor', 'investigatorFullName': 'Antonio Esposito', 'investigatorAffiliation': 'IRCCS San Raffaele'}}}}