This study shows that the described commercial machine learning algorithm can reliably execute a routine pathologic assessment, however, in some instances, human expertise is essential. The time of AI was significantly longer (568 h) than that of the pathologist (32 h). Results revealed: (i) substantial interrater agreement between AI and PA for dichotomized evaluation (Cohen’s kappa = 0.61) (ii) strong correlation between AI and PA H-scores (Spearman r = 0.85, p < 0.001) (iii) a small constant error and a significant proportional error (Passing–Bablok regression y = 0.51 × X + 29.9, p < 0.001) (iv) discrepancies in H-score in cases of extreme (strongest/weakest) or heterogeneous FGFR2 expression and poor tissue quality.
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was compared to the manual pathologic assessment in digital slides (PA).
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Expression of FGFR2 in BC (n = 315) measured using a certified 3DHistech CaseViewer/QuantCenter software 2.3.0. [Color figure can be viewed in the online issue, which is available at We present here an assessment of a ‘real-life’ value of automated machine learning algorithm (AI) for examination of immunohistochemistry for fibroblast growth factor receptor-2 (FGFR2) in breast cancer (BC). L, mirror M, condenser N, optics for transmitted Köhler illumination O, halogen light source for transmitted illumination P, fluorescent filter cube Q, additional optics for epifluorescent illumination R, fluorescent light source S, tube lens T, AxioCam MRm. The same letters are used as in (B) where applicable. (C) The schematic light path of the system. (B) Components inside the microscope: A, preview camera B, LED-based slide background illumination for preview camera C, LED-based illumination for label area D, objective E, fluorescent illumination unit F, slide holder and slide G, slide holder tray H, slide loader I, slide loader stepper motor J, Y lead screw and rails of slide stage K, halogen lamp-based transmitted light illumination unit. Left to the system, HXP-120 fluorescent light source is shown. (A) The MIRAX MIDI system with the AxioCam MRm mounted on the top and a slide tray inserted on the right. Automated fluorescent WSI with stable LED illumination and high-quality homogeneous fluorescent slides can be used conveniently for SBC. The measured integrated fluorescence showed linearity with exposure time and staining intensity. Fluorescent samples can be reliably detected, focused, and scanned. The data was displayed by the histogram, scatter plot, and gallery functions of the same program. The HistoQuant software package of the MIRAX viewer was used for image segmentation and quantitative analysis. Fluorescent calibration beads were used to verify the linearity of the system. The MIRAX control software was further developed for fluorescent sample detection, autofocusing, multichannel digitization, and signal correction due to nonuniform illumination. A MIRAX MIDI automated whole slide imager was used with metal-halide and light emitting diode (LED)-based fluorescent illumination, filter block changer, and a cooled monochrome charge coupled device camera. Fully automated microscopes became affordable with the advent of whole slide imaging (WSI) and they can be transformed into a cytometer. Slide-based image cytometry (SBC) has several advantages over flow cytometry but it is not widely used because of its low throughput, complicated workflow, and high price.
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