Adrenal Cancer
Conditions
Brief summary
Retrospective study based on data already available at each Center. Pseudonymized CT images of each patient in DICOM format will be sent from each center to the Coordinating Center to perform radiomics analysis.
Detailed description
Retrospective study based on data already available at each Center. Participating Centers will identify patients based on shared inclusion/exclusion criteria. Pseudonymized CT images of each patient in DICOM format will be sent from each center to the Coordinating Center to perform radiomics analysis. Images will be transferred via File Transfer Protocol while respecting the anonymity of enrolled patients. Images will be deposited in a dedicated study folder created by the AOUBO ICT Service. Images will be accessible only to the Investigator and Principal Investigator and/or their delegates via personalized credentials, which can be accessed only from IRCCS AOUBO computers and facilities. The folder to which the images will be transferred will be accessible only to the Principal Investigator and his/her Collaborators through customized private credentials usable only through IRCCS AOUBO networks, computers and facilities. Radiomics, which will be applied to existing CT images, will in no way affect the care pathway of patients
Interventions
None listed
Sponsors
IRCCS Azienda Ospedaliero-Universitaria di Bologna
Study design
Observational model
COHORT
Time perspective
OTHER
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Age ≥18 years * Patients with adrenal tumor who underwent adrenectomy surgery from 1-1-2000 to 30-5-2023, performed according to clinical necessity and indications of international guidelines,with availability of histologic diagnosis or adrenal tumor that did not undergo adrenectomy surgery with diagnosis of benignity confirmed by radiologic stability at 6-12 months after first finding(as indicated in guidelines) * Availability of radiological images in DICOM format of abdominal CT scan in which the adrenal tumor is first described, obtained on the date of first evaluation at the participating center (necessarily before surgery for patients undergoing adrenectomy) * Signature of informed consent
Exclusion criteria
* none
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic Accuracy of Radiomics-Derived Parameters for Differentiating Benign and Malignant Adrenal Masses | through study completion, an average of 1 year | This measure will assess the diagnostic ability of specific radiomics-derived parameters, including texture analysis and intensity features, in identifying the nature (benign or malignant) of adrenal masses. The diagnostic performance will be evaluated through sensitivity, specificity. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Association of Radiomics-Derived Parameters with Ki67 Values | through study completion, an average of 1 years | This measure evaluates the correlation between radiomics-derived imaging parameters and Ki67 proliferation index values. Ki67 values will be assessed as a percentage using immunohistochemical staining, and the correlation will be expressed as a Pearson or Spearman correlation coefficient, depending on data distribution. |
| Association of Radiomics-Derived Parameters with Weiss' Anatomopathologic Score | through study completion, an average of 1 year | This measure evaluates the correlation between radiomics-derived imaging parameters and the Weiss anatomopathologic score. The Weiss score will be determined based on pathological examination, and the association will be reported as a correlation coefficient. |
| Association of Radiomics-Derived Parameters with Occurrence of Distant Metastasis | through study completion, an average of 1 year | This measure evaluates the relationship between radiomics-derived imaging parameters and the occurrence of distant metastases in patients with adrenal tumors. The occurrence of metastases will be reported as a binary outcome (presence or absence), and the association will be analyzed using logistic regression models or similar statistical methods. |
Countries
Italy
Contacts
Primary ContactGuido Di Dalmazi, MD
Outcome results
None listed