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Published prognostic scores have limitations in prediction of long term survival after stereotactic radiotherapy for brain metastases. Moreover, no validated tools are available for prediction of local failure. The value of radiomics is evaluated in this perspective.
Sensitivity is low for prediction of long term survival of currently available prognostic scores for brain metastases. First the current clinical models will be optimized with a new prognostic model and nomogram. Radiomics is a tool to analyze tumor characteristics based on CT and MR images. These tumor characteristics may reflect tumor biology and outcome. Therefore it is investigated if radiomics improves prediction of long term survival after stereotactic radiotherapy for brain metastases. Moreover, the predictive value of radiomics for local failure is investigated.
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| Measure | Description | Time Frame |
|---|---|---|
| Sensitive value of 12 months survival after stereotactic radiotherapy for brain metastases with radiomics | Sensitivity of 12 months survival after stereotactic radiotherapy for brain metastases with radiomics. Radiomics is a tool to analyze tumor characteristics based on CT and MR images. | 1 year |
| Sensitive value of 12 months local failure after stereotactic radiotherapy for brain metastases with radiomics | Sensitivity of 12 months local failure after stereotactic radiotherapy for brain metastases with radiomics. Radiomics is a tool to analyze tumor characteristics based on CT and MR images. | 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Specificity of 12 months survival and local failure after stereotactic radiotherapy for brain metastases with radiomics. | Specificity of 12 months survival and local failure after stereotactic radiotherapy for brain metastases with radiomics. | 1 year |
| Positive predictive value of 12 months survival and local failure after stereotactic radiotherapy for brain metastases with radiomics. |
| Measure | Description | Time Frame |
|---|---|---|
| Area under the curve of published prognostic scores | Area under the curve published prognostic scores | 1 year |
| Mismatch rate of published prognostic scores | Mismatch rate of published prognostic scores |
Inclusion Criteria:
Exclusion Criteria:
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Patients with 1 upto 4 brain metastases treated with SRT
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Maastro Clinic | Maastricht | 6229 ET | Netherlands |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 23522151 | Result | Zindler JD, Rodrigues G, Haasbeek CJ, De Haan PF, Meijer OW, Slotman BJ, Lagerwaard FJ. The clinical utility of prognostic scoring systems in patients with brain metastases treated with radiosurgery. Radiother Oncol. 2013 Mar;106(3):370-4. doi: 10.1016/j.radonc.2013.01.015. Epub 2013 Mar 20. | |
| 23429647 | Result |
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| ID | Term |
|---|---|
| D009362 | Neoplasm Metastasis |
| D009369 | Neoplasms |
| ID | Term |
|---|---|
| D009385 | Neoplastic Processes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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Positive predictive value of 12 months survival and local failure after stereotactic radiotherapy for brain metastases with radiomics. |
| 1 year |
| Negative predictive value of 12 months survival and local failure after stereotactic radiotherapy for brain metastases with radiomics. | Negative predictive value of 12 months survival and local failure after stereotactic radiotherapy for brain metastases with radiomics. | 1 year |
| 1 year |
| Rodrigues G, Zindler J, Warner A, Lagerwaard F. Recursive partitioning analysis for the prediction of stereotactic radiosurgery brain metastases lesion control. Oncologist. 2013;18(3):330-5. doi: 10.1634/theoncologist.2012-0316. Epub 2013 Feb 19. |
| 24892406 | Result | Aerts HJ, Velazquez ER, Leijenaar RT, Parmar C, Grossmann P, Carvalho S, Bussink J, Monshouwer R, Haibe-Kains B, Rietveld D, Hoebers F, Rietbergen MM, Leemans CR, Dekker A, Quackenbush J, Gillies RJ, Lambin P. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014 Jun 3;5:4006. doi: 10.1038/ncomms5006. |