2022
DOI: 10.1007/s12022-022-09718-0
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Grading of Medullary Thyroid Carcinoma: an Interobserver Reproducibility Study

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Cited by 16 publications
(6 citation statements)
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“…3 and Table 2) [53]. The IMTCGS system has been validated in other series [54] and appears well reproducible [55]. In conclusion, recent findings have demonstrated that Ki67 labelling index plays a prognostic role in MTC, although the better prognostic stratification of patients is obtained combining Ki67 index with necrosis (IMTCGS system).…”
Section: Medullary Thyroid Carcinomamentioning
confidence: 64%
“…3 and Table 2) [53]. The IMTCGS system has been validated in other series [54] and appears well reproducible [55]. In conclusion, recent findings have demonstrated that Ki67 labelling index plays a prognostic role in MTC, although the better prognostic stratification of patients is obtained combining Ki67 index with necrosis (IMTCGS system).…”
Section: Medullary Thyroid Carcinomamentioning
confidence: 64%
“…A reproducible and reliable grading system is necessary to correlate histologic findings with prognosis in both human medicine [12][13][14][15][16][17] and veterinary medicine. [18][19][20][21] The reproducibility of the human meningioma grading system applied to canine meningioma was previously investigated to lay the groundwork for studies on the prognostic significance of histologic grade in canine meningiomas.…”
Section: Introductionmentioning
confidence: 99%
“…Williams et al . recently demonstrated excellent intraobserver agreement of manual assessment of the Ki67 proliferation index with a kappa value of 0.86 in a cohort of 44 MTC 4 . However, manual Ki67 count is known to be tedious and time‐consuming.…”
Section: Introductionmentioning
confidence: 98%
“…Williams et al recently demonstrated excellent intraobserver agreement of manual assessment of the Ki67 proliferation index with a kappa value of 0.86 in a cohort of 44 MTC. 4 However, manual Ki67 count is known to be tedious and time-consuming. Various digital image analysis platforms and machine learning (ML)-based algorithms have shown to be highly sensitive and specific to obtain an automatic reading of the Ki67 index in pancreatic neuroendocrine neoplasms and breast carcinomas.…”
Section: Introductionmentioning
confidence: 99%