Intellisite pathology solution

Manufactured by Philips

Sourced in Netherlands

The IntelliSite Pathology Solution is a digital pathology platform developed by Philips. It enables the capture, management, and analysis of digital images of tissue samples. The system includes slide scanners, software for digitizing and managing pathology slides, and tools for collaboration and remote viewing of digital pathology images.

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Lab products found in correlation

Ultrafast scanner, by Philips (2 mentions) Anti cd3, by Agilent Technologies (1 mentions) Anti cytokeratinae1 ae3, by Agilent Technologies (1 mentions) Anti cd8, by Agilent Technologies (1 mentions) Pd l1 immunohistochemistry 22c3 pharmdx assay, by Agilent Technologies (1 mentions) Benchmark ultra system, by Roche (1 mentions) Anhydrous methanol, by Merck Group (1 mentions) Hematoxylin, by Avantor (1 mentions) Artisan link pro special staining system, by Agilent Technologies (1 mentions) Rotary microtome microm hm 340e, by Thermo Fisher Scientific (1 mentions) Chloroform, by Merck Group (1 mentions) Glacial acetic acid, by Merck Group (1 mentions) Reliaprep ffpe total rna miniprep system, by Promega (1 mentions)

5 protocols using intellisite pathology solution

Automated Pathology Slide Digitization

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A study coordinator compiled all cases selected by the enrollment pathologists and submitted them for digital scanning at participating sites using the Philips IntelliSite Pathology Solution (Philips, the Netherlands), which includes a scanner, an image management system and a display. A study technician was trained to scan slides using appropriate calibration and quality control measures. All slides were scanned as WSI for digital review using the Philips IntelliSite Pathology Solution.
Of the 2000 cases submitted for scanning, 8 (0.4%) were excluded for the following reasons: slide size did not meet scanner specifications (4 cases), no tissue was detected by scanner on any one of the slides selected for the case (2 cases), more than one case was selected for the patient (1 case), or slides were broken or damaged (1 case). This process yielded a “full analysis set” of 1992 cases (99.6% of enrolled cases).

Mukhopadhyay S., Feldman M.D., Abels E., Ashfaq R., Beltaifa S., Cacciabeve N.G., Cathro H.P., Cheng L., Cooper K., Dickey G.E., Gill R.M., Heaton RP J.r., Kerstens R., Lindberg G.M., Malhotra R.K., Mandell J.W., Manlucu E.D., Mills A.M., Mills S.E., Moskaluk C.A., Nelis M., Patil D.T., Przybycin C.G., Reynolds J.P., Rubin B.P., Saboorian M.H., Salicru M., Samols M.A., Sturgis C.D., Turner K.O., Wick M.R., Yoon J.Y., Zhao P, & Taylor C.R. (2017). Whole Slide Imaging Versus Microscopy for Primary Diagnosis in Surgical Pathology: A Multicenter Blinded Randomized Noninferiority Study of 1992 Cases (Pivotal Study). The American Journal of Surgical Pathology, 42(1), 39-52.

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Immunohistochemical Analysis of Tumor Invasion

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After reviewing every slide, one key block containing the deepest point of invasion was selected for each case. The key blocks were sectioned for further immunohistochemical staining with the following antibodies: anti‐cytokeratin AE1/AE3 (DAKO, Agilent, Santa Clara, CA; M3515 monoclonal mouse antibody; dilution 1:400), anti‐CD3 (DAKO, Agilent; A0452 polyclonal rabbit antibody; dilution 1:100), and anti‐CD8 (DAKO, Agilent; FLEX monoclonal mouse antibody, clone C8/144B, ready‐to‐use). Whole slide images of each case consisting of H&E‐, pan‐cytokeratin‐, CD3‐, and CD8‐stained slides were generated by scanning at 40× magnification with Philips IntelliSite Pathology Solution on an UltraFast Scanner (Philips, the Netherlands).

Sung Y.E., Kim M, & Lee Y.S. (2021). Proposal of a scoring system for predicting pathological risk based on a semiautomated analysis of whole slide images in oral squamous cell carcinoma. Head & Neck, 43(5), 1581-1591.

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Immune Profiling of Advanced Cancers

Cited 1 time

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In a clinical study, one patient showed disease progression. Four-micrometer-thick slides were cut from the formalin-fixed paraffin-embedded (FFPE) blocks with the patient’s biopsies before treatment on day 0 and at the end of the treatment on day 350 (following three single-dose vaccine injections and four booster vaccinations for long-term maintenance). PD-L1 immunohistochemical (IHC) staining was carried out using a Dako PD-L1 immunohistochemistry 22C3 pharmDx assay (Dako, Carpinteria, CA, USA), including appropriate controls, according to the manufacturer’s instructions. PD-L1 assessment was based on CPS, which had been similarly applied in two recent phase III trials evaluating the effect of nivolumab [46 (link)] and pembrolizumab [47 (link)] in patients with advanced GC and esophageal adenocarcinoma, respectively. IHC staining for Her-2/neu was performed using a 4B5 mAb (Ventana, Tucson, AZ, USA) for the BenchMarkULTRA system (Ventana). Images of Her-2/neu- and PD-L1-stained lung sections were obtained using a Philips IntelliSite Pathology Solution with an Ultra-Fast Scanner. Fluorescence in situ hybridization (FISH) for the evaluation of Her-2/neu gene amplification was performed as described previously [10 (link)].

Tobias J., Högler S., Raigel M., Lin D.S., Chao Y., Kenner L., Garner-Spitzer E., Yavrom S., Ede N.J., Zielinski C.C., Kundi M, & Wiedermann U. (2023). Preclinical and Clinical Observations Implying Combination Therapy to Enhance the Efficacy of the Her-2/neu B-Cell Peptide-Based Vaccine HER-Vaxx and to Prevent Immune Evasion. International Journal of Molecular Sciences, 25(1), 287.

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Histological analysis of mouse colons

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For histological analysis of mouse colons, distal colons containing fecal content were isolated at day 12 p.i. and fixed for 3 hr at room temperature (RT) in freshly prepared Carnoy’s fixative [60% anhydrous methanol (Sigma-Aldrich), 30% chloroform (Sigma-Aldrich), 10% glacial acetic acid (Sigma-Aldrich)]. Fixed colons were transferred to fresh Carnoy’s fixative and fixed again overnight. Fixed samples were washed in anhydrous methanol for 2 hr followed by transfer to fresh methanol and storage at 4°C until further use. Using a Tissue-Tek VIP processor (SAKURA), samples were subjected to consecutive washes with 100% denatured ethanol (VWR), treatment with the clearing agent toluene (VWR), and paraffin embedment (Leica). Sections (3µm) were cut using a Rotary Microtome Microm HM 340E (Thermo Fisher Scientific). Paraffin-embedded sections were either stained with hematoxylin (Medite) plus eosin (VWR) (H&E), or Alcian Blue (Dako). Alcian Blue staining was performed using an Artisan Link Pro Special Staining System (Dako). Slides were scanned with an automated digital slide creation and viewing system (Philips IntelliSite Pathology Solution; 760001).

Bonetti L., Horkova V., Longworth J., Guerra L., Kurniawan H., Franchina D.G., Soriano-Baguet L., Grusdat M., Spath S., Koncina E., Ewen A., Binsfeld C., Verschueren C., Gérardy J.J., Kobayashi T., Dostert C., Farinelle S., Härm J., Chen Y., Harris I.S., Lang P.A., Vasiliou V., Waisman A., Letellier E., Becher B., Mittelbronn M, & Brenner D. (2023). A Th17 cell-intrinsic glutathione/mitochondrial-IL-22 axis protects against intestinal inflammation. bioRxiv.

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Evaluating AI Correlation with Renal Cancer Histology

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To evaluate whether our AI model correlated with the histological features assessed by a pathologist and gene signatures, 95 samples consisting of clear (n = 30), mixed (n = 48), and eosinophilic (n = 17) phenotypes were extracted from ccRCC patients who underwent nephrectomy at the Kansai Medical University Hospital [4] . We explored the RNA expression corresponding to the histological phenotype from tissue microarrays (TMAs) from two-millimeter cores of formalin-xed, para n-embedded (FFPE) blocks.
After removing three-micrometer slices from FFPE-TMA blocks for histological assessment of H&Estained slides, the TMA cores were used for mRNA isolation using ReliaPrep FFPE Total RNA Mini-prep System (Promega, Madison, Wisconsin, USA) as previously described [4] . A custom NanoString panel from the IMmotion 150 [2] and ClearCode34 [12] panels were used as previously described [4] . H&Estained TMA slides were scanned by a Philips IntelliSite Pathology Solution (Philips, Best, the Netherlands) to verify our AI model. This study was approved by the Institutional Review Board (No. 2018109 and No. 2020222).

Ohe C., Yoshida T., Amin M.B., Uno R., Atsumi N., Yasukochi Y., Ikeda J., Nakamoto T., Noda Y., Kinoshita H., Tsuta K, & Higasa K. (2023). Deep learning-based predictions of clear and eosinophilic phenotypes in clear cell renal cell carcinoma. Human pathology, 131.

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