fitting routine fmincon  (MathWorks Inc)

Journal: Cancer Science

Article Title: Risk Stratification Prediction of Endometrial Cancer Using Microstructural Mapping Based on Time‐Dependent Diffusion MRI

doi: 10.1111/cas.70036

Figure Lengend Snippet: Representative images of microstructural mapping and correlation between the microstructural mapping results and histopathologic findings. (a) Representative images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case, including diameter, V in , D ex , cellularity fitted from IMPULSED and the ADC maps. Red arrows and white dashed lines indicate tumor ROI. Corresponding diffusion‐weighted images ( b = 1000 s/mm 2 ) at the similar axial locations are shown in the first column. (b) Correlation between t d ‐dMRI‐based cellularity and nuclei counting. Nuclei counting images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case quantified with QuPath in H&E‐stained slices (original magnification: ×400, scale bar: 50 μm). Graph demonstrating satisfactory positive correlation between cellularity and histopathology‐based nuclei counting in representative participants ( n = 13). ADC, Apparent diffusion coefficient; ΔADC1 and ΔADC2, ratios of change in ADC values between OGSE and PGSE sequences; ADC N1 , ADC N2 , ADC PGSE , ADC from OGSE N1 , OGSE N2 and PGSE, respectively; ROI, regions of interest; H&E, hematoxylin and eosin.

Article Snippet: The MATLAB routine for IMPULSED fitting is provided at https://github.com/wjgxw/ogse .

Techniques: Diffusion-based Assay, Staining, Histopathology