Alexey Surov1, Gordian Hamerla2, Hans Jonas Meyer2, Karsten Winter3, Stefan Schob2, Eckhard Fiedler4. 1. Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany; Department of Radiology, Martin-Luther-university Halle-Wittenberg, Germany. Electronic address: alex.surow@medizin.uni-halle.de. 2. Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany. 3. Institute of Neuroanatomy, University of Leipzig, Germany; Institute of Biometry, University of Leipzig, Germany. 4. Department of Dermatology, Martin-Luther-university Halle-Wittenberg, Germany.
Abstract
PURPOSE: To analyze several histopathological features and their possible correlations with whole lesion histogram analysis derived from ADC maps in meningioma. MATERIALS AND METHODS: The retrospective study involved 36 patients with primary meningiomas. For every tumor, the following histogram analysis parameters of apparent diffusion coefficient (ADC) were calculated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, ADC percentiles: P10, P25, P75, P90, as well kurtosis, skewness, and entropy. All measures were performed by two radiologists. Proliferation index KI 67, minimal, maximal and mean cell count, total nucleic area, and expression of water channel aquaporin 4 (AQP4) were estimated. Spearman's correlation coefficient was used to analyze associations between investigated parameters. RESULTS: A perfect interobserver agreement for all ADC values (0.84-0.97) was identified. All ADC values correlated inversely with tumor cellularity with the strongest correlation between P10, P25 and mean cell count (-0.558). KI 67 correlated inversely with all ADC values except ADCmin. ADC parameters did not correlate with total nucleic area. All ADC values correlated statistically significant with expression of AQP4. CONCLUSIONS: ADC histogram analysis is a valid method with an excellent interobserver agreement. Cellularity parameters and proliferation potential are associated with different ADC values. Membrane permeability may play a greater role for water diffusion than cell count and proliferation activity.
PURPOSE: To analyze several histopathological features and their possible correlations with whole lesion histogram analysis derived from ADC maps in meningioma. MATERIALS AND METHODS: The retrospective study involved 36 patients with primary meningiomas. For every tumor, the following histogram analysis parameters of apparent diffusion coefficient (ADC) were calculated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, ADC percentiles: P10, P25, P75, P90, as well kurtosis, skewness, and entropy. All measures were performed by two radiologists. Proliferation index KI 67, minimal, maximal and mean cell count, total nucleic area, and expression of water channel aquaporin 4 (AQP4) were estimated. Spearman's correlation coefficient was used to analyze associations between investigated parameters. RESULTS: A perfect interobserver agreement for all ADC values (0.84-0.97) was identified. All ADC values correlated inversely with tumor cellularity with the strongest correlation between P10, P25 and mean cell count (-0.558). KI 67 correlated inversely with all ADC values except ADCmin. ADC parameters did not correlate with total nucleic area. All ADC values correlated statistically significant with expression of AQP4. CONCLUSIONS: ADC histogram analysis is a valid method with an excellent interobserver agreement. Cellularity parameters and proliferation potential are associated with different ADC values. Membrane permeability may play a greater role for water diffusion than cell count and proliferation activity.
Authors: Shun Zhang; Gloria Chia-Yi Chiang; Jacquelyn Marion Knapp; Christina M Zecca; Diana He; Rohan Ramakrishna; Rajiv S Magge; David J Pisapia; Howard Alan Fine; Apostolos John Tsiouris; Yize Zhao; Linda A Heier; Yi Wang; Ilhami Kovanlikaya Journal: J Neuroradiol Date: 2019-05-25 Impact factor: 3.447
Authors: Alexey Surov; Lisa Paul; Hans Jonas Meyer; Stefan Schob; Cornelius Engelmann; Andreas Wienke Journal: J Clin Med Date: 2018-10-15 Impact factor: 4.241
Authors: Alexey Surov; Yun-Woo Chang; Lihua Li; Laura Martincich; Savannah C Partridge; Jin You Kim; Andreas Wienke Journal: BMC Cancer Date: 2019-11-05 Impact factor: 4.430