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AB092. Imaging the histopathology subtypes of the growth hormone-secreting pituitary neuroendocrine tumor.
Chinese Clinical Oncology 2024 August
BACKGROUND: Sparsely granulated (SG) growth hormone-secreting pituitary neuroendocrine tumors (GH-PitNETs) often present with a more aggressive clinical course compared to densely granulated (DG) tumors. These subtypes exhibit distinct biological and imaging characteristics. Thus, this study aims to differentiate between the histopathological subtypes of GH-PitNETs using pre-operative magnetic resonance imaging (MRI).
METHODS: A retrospective analysis was conducted on 83 acromegalic patients treated at our institution between 2000 and 2010. Tumor volumes were segmented from preoperative MRIs, including T1-weighted, T2-weighted, T1 with contrast, and T2 fluid attenuated inversion recovery (FLAIR) sequences. Reference regions of interest (ROIs) were delineated using gray and white matter from the same sequences. Two pathologists reviewed pathology specimens for anti-cytokeratin (CAM 5.2) and Pit-1 expression. Clinical and radiological biomarkers were compared between SG and DG patients.
RESULTS: A total of 83 patients with complete histopathology and 51 patients with complete MRIs were included in the analysis. SG PitNETs exhibited higher rates of supra-sellar invasion (61.5%, P<0.001), larger tumor sizes, lower pre-operative GH levels, and increased post-operative residual tumor (65.4%, P<0.001) compared to DG PitNETs. Additionally, SG PitNETs showed greater hyperintensity on T2-weighted images and enhanced contrast, whereas DG PitNETs exhibited less contrast enhancement. Utilization of these imaging biomarkers demonstrated an 94.1% accuracy in T2 FLAIR and overall of 78.7% predicting the histopathological subtypes of GH-PitNETs.
CONCLUSIONS: Distinct histopathological subtypes of GH-PitNETs represent crucial prognostic factors. Utilizing multimodal pre-operative MRIs, clinicians can accurately identify sparsely granulated GH-PitNETs, facilitating improved treatment planning strategies.
METHODS: A retrospective analysis was conducted on 83 acromegalic patients treated at our institution between 2000 and 2010. Tumor volumes were segmented from preoperative MRIs, including T1-weighted, T2-weighted, T1 with contrast, and T2 fluid attenuated inversion recovery (FLAIR) sequences. Reference regions of interest (ROIs) were delineated using gray and white matter from the same sequences. Two pathologists reviewed pathology specimens for anti-cytokeratin (CAM 5.2) and Pit-1 expression. Clinical and radiological biomarkers were compared between SG and DG patients.
RESULTS: A total of 83 patients with complete histopathology and 51 patients with complete MRIs were included in the analysis. SG PitNETs exhibited higher rates of supra-sellar invasion (61.5%, P<0.001), larger tumor sizes, lower pre-operative GH levels, and increased post-operative residual tumor (65.4%, P<0.001) compared to DG PitNETs. Additionally, SG PitNETs showed greater hyperintensity on T2-weighted images and enhanced contrast, whereas DG PitNETs exhibited less contrast enhancement. Utilization of these imaging biomarkers demonstrated an 94.1% accuracy in T2 FLAIR and overall of 78.7% predicting the histopathological subtypes of GH-PitNETs.
CONCLUSIONS: Distinct histopathological subtypes of GH-PitNETs represent crucial prognostic factors. Utilizing multimodal pre-operative MRIs, clinicians can accurately identify sparsely granulated GH-PitNETs, facilitating improved treatment planning strategies.
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