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| Name | Class |
|---|---|
| University of California, San Francisco | OTHER |
| Stanford University | OTHER |
| Erasmus Medical Center | OTHER |
| Memorial Sloan Kettering Cancer Center |
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More than 200,000 new cases of renal cancer are diagnosed in the world each year, with more than 63,000 new cases in Europe alone. Of those, renal cell carcinoma (RCC) is the most common type in adults, making up more than 90% of the cases. Deciding on the benign or malignant nature of some RCC on the basis of medical images (CT, MRI, US) is an issue, which often leads to unnecessary surgery, morbidity and costs.
A categorization for renal cysts was introduced in the late 1980s known as the Bosniak classification. The Bosniak classification system classifies them into groups that are benign (I and II) and those that need surgical resection (III and IV), based on specific imaging features. However, defining the malignancy of category III lesions still remains a challenge. Though Bosniak classification for renal cysts is used worldwide and underwent a number of modifications, Bosniak III cysts still have almost a 1:1 chance of being malignant. So the problem is that approximately half of the Bosniak category III cystic lesions prove to be benign after surgery.
The proposed project aims to develop a quantitative image analysis (QIA) based multifactorial decision support system (mDSS) capable of classifying renal cysts with high accuracy into benign or malignant status, thus reducing the amount of unnecessary surgeries performed. Using standard-of-care CT images and clinical parameters, the customized DSS will then guide experts in planning a safe and effective diagnostic and treatment strategy for all RCC patients.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Radiomics | Diagnostic Test | The high-throughput extraction of large amounts of quantitative image features from radiographic medical images |
| Measure | Description | Time Frame |
|---|---|---|
| malignancy classifier | Machine learning algorithm that can differentiate between malignant and beingn bosniak 3 renal cysts. | 1 year |
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Inclusion Criteria:
Exclusion Criteria:
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Patients with renal cysts classified as bosniak 3 in one of the collaborating institutes.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Maastricht University Medical Center | Maastricht | Limburg | 6200 MD | Netherlands |
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| ID | Term |
|---|---|
| D002292 | Carcinoma, Renal Cell |
| ID | Term |
|---|---|
| D000230 | Adenocarcinoma |
| D002277 | Carcinoma |
| D009375 | Neoplasms, Glandular and Epithelial |
| D009370 | Neoplasms by Histologic Type |
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| ID | Term |
|---|---|
| D000097188 | Radiomics |
| ID | Term |
|---|---|
| D003952 | Diagnostic Imaging |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
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| OTHER |
| University of Sao Paulo General Hospital | OTHER |
| University Hospital, Aachen | OTHER |
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| D009369 | Neoplasms |
| D007680 | Kidney Neoplasms |
| D014571 | Urologic Neoplasms |
| D014565 | Urogenital Neoplasms |
| D009371 | Neoplasms by Site |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D007674 | Kidney Diseases |
| D014570 | Urologic Diseases |
| D052801 | Male Urogenital Diseases |