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Machine Learning Uncovers Novel Predictors of Peptide Receptor Radionuclide Therapy Eligibility in Neuroendocrine
Gábor Sipka1, István Farkas1, Annamária Bakos1
1Department of Nuclear Medicine, University of Szeged, 6720 Szeged, Hungary.
Abstract:
Background: Neuroendocrine neoplasms (NENs) are a diverse group of malignancies in which somatostatin receptor expression can be crucial in guiding therapy. We aimed to evaluate the effectiveness of [99mTc]Tc-EDDA/HYNIC-TOC SPECT/CT in differentiating neuroendocrine tumor histology, selecting candidates for radioligand therapy, and identifying correlations between somatostatin receptor expression and non-imaging parameters in metastatic NENs. Methods: This retrospective study included 65 patients (29 women, 36 men, mean age 61) with metastatic neuroendocrine neoplasms confirmed by histology, follow-up, or imaging, comprising 14 poorly differentiated carcinomas and 51 well-differentiated tumors. Somatostatin receptor SPECT/CT results were assessed visually and semiquantitatively, with mathematical models incorporating histological, oncological, immunohistochemical, and laboratory parameters, followed by biostatistical analysis. Results: Of 392 lesions evaluated, the majority were metastases in the liver, lymph nodes, and bones. Mathematical models estimated somatostatin receptor expression accurately (70-83%) based on clinical parameters alone. Key factors included tumor origin, oncological treatments, and the immunohistochemical marker CK7. Associations were found between age, grade, disease extent, and markers (CEA, CA19-9, AFP). Conclusions: Our findings suggest that [99mTc]Tc-EDDA/HYNIC-TOC SPECT/CT effectively evaluates somatostatin receptor expression in NENs. Certain immunohistochemical and laboratory parameters, beyond recognized factors, show potential prognostic value, supporting individualized treatment strategies.
Insights
[99mTc]Tc-EDDA/HYNIC-TOC SPECT/CT effectively assesses somatostatin receptor expression in neuroendocrine neoplasms (NENs). Clinical and non-imaging markers correlate with receptor levels, aiding personalized treatment for metastatic NENs.
Area of Science:
- Nuclear medicine
- Oncology
- Radiopharmacology
Background:
- Neuroendocrine neoplasms (NENs) are diverse malignancies where somatostatin receptor (SSTR) expression is key for therapy selection.
- Evaluating SSTR expression is crucial for diagnosing NENs and guiding treatment, including radioligand therapy.
- Current methods for assessing SSTR expression in metastatic NENs require further refinement for accurate patient stratification.
Purpose of the Study:
- To assess the efficacy of [99mTc]Tc-EDDA/HYNIC-TOC SPECT/CT in differentiating NEN histology.
- To identify suitable candidates for radioligand therapy based on SSTR expression.
- To explore correlations between SSTR expression and non-imaging parameters in metastatic NENs.
Main Methods:
- Retrospective analysis of 65 patients with metastatic NENs.
- Visual and semiquantitative assessment of somatostatin receptor SPECT/CT results.
- Biostatistical analysis incorporating histological, oncological, immunohistochemical, and laboratory data.
Main Results:
- [99mTc]Tc-EDDA/HYNIC-TOC SPECT/CT accurately estimated SSTR expression (70-83%) using mathematical models based on clinical parameters.
- Tumor origin, prior treatments, and CK7 were key predictors of SSTR expression.
- Significant associations were observed between patient age, tumor grade, disease extent, and tumor markers (CEA, CA19-9, AFP).
Conclusions:
- [99mTc]Tc-EDDA/HYNIC-TOC SPECT/CT is effective for evaluating SSTR expression in NENs.
- Specific immunohistochemical and laboratory markers offer prognostic value beyond established factors.
- These findings support the development of individualized treatment strategies for NEN patients.
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