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| Name | Class |
|---|---|
| Danube University Krems | OTHER |
| Institut du Cancer de Montpellier - Val d'Aurelle | OTHER |
| Ente Ospedaliero Cantonale, Ticino, Switzerland | OTHER |
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To evaluate if CT features at diagnosis in patients with HGSOC can be used to build an Artificial Intelligence model capable of discerning the pathological involvement of the mesentery, assessing the potential impediments for an optimal debulking surgery and predicting the development of resistance to platinum based chemotherapeutic agents.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Retrospective cohort | Patients affected by High Grade Seruous Ovarian Cancer with mesenteric infiltration confirmed by diagnostic laparoscopy, from January 2021 to December 2023 |
| |
| Prospective cohort | Patients affected by High Grade Seruous Ovarian Cancer with mesenteric infiltration confirmed by diagnostic laparoscopy |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Computed Tomography | Diagnostic Test | Computed Tomography done according to Clinical Practice to assess mesenteric involvment |
|
| Measure | Description | Time Frame |
|---|---|---|
| Preoperative Artificial Intelligence assisted CT-based evaluation | Preoperative Artificial Intelligence assisted CT-based prediction of patients with suboptimal debulking at surgery due to diffuse mesenteric disease or mesenteric retraction. | 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Evaluation of the Radiologist Assessment of the CT | Identification of mesenteric infiltration from CT images using Artificial Intelligence at a comparable performance with human/radiologist assessment. | 1 year |
| Prediction of Platinum Resistance |
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Inclusion Criteria:
Exclusion Criteria:
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Women with confirmed HGSOC who exhibited mesenteric disease, including mesenteric retraction or diffuse mesenteric carcinomatosis, during diagnostic laparoscopy (or without mesenteric disease for the control cohort)
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Camilla Panico, Dr | Contact | +390630155701 | camilla.panico@policlinicogemelli.it |
| Name | Affiliation | Role |
|---|---|---|
| Camilla Panico, Dr | Fondazione Policlinico Universitario Agostino Gemelli IRCCS | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Advanced Radiology Center | Recruiting | Roma | 00168 | Italy |
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| ID | Term |
|---|---|
| D010051 | Ovarian Neoplasms |
| ID | Term |
|---|---|
| D004701 | Endocrine Gland Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D010049 | Ovarian Diseases |
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| ID | Term |
|---|---|
| D014057 | Tomography, X-Ray Computed |
| ID | Term |
|---|---|
| D007090 | Image Interpretation, Computer-Assisted |
| D003952 | Diagnostic Imaging |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
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AI-assisted CT-based prediction of patients who will develop platinum resistance
| 1 year |
| Prediction of Progression Free Survival (PFS) and Overall Survival (OS) | Prediction of Progression Free Survival (PFS) and Overall Survival (OS) with Artificial Intelligence | 2 years |
| D000291 |
| Adnexal Diseases |
| D005831 | Genital Diseases, Female |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D005833 | Genital Neoplasms, Female |
| D014565 | Urogenital Neoplasms |
| D000091662 | Genital Diseases |
| D004700 | Endocrine System Diseases |
| D006058 | Gonadal Disorders |
| D011856 | Radiographic Image Enhancement |
| D007089 | Image Enhancement |
| D010781 | Photography |
| D011859 | Radiography |
| D014056 | Tomography, X-Ray |
| D014054 | Tomography |