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1.
IEEE Trans Biomed Eng ; 71(6): 1901-1912, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38231822

RESUMO

OBJECTIVE: Pathologists rely on histochemical stains to impart contrast in thin translucent tissue samples, revealing tissue features necessary for identifying pathological conditions. However, the chemical labeling process is destructive and often irreversible or challenging to undo, imposing practical limits on the number of stains that can be applied to the same tissue section. Here we present an automated label-free whole slide scanner using a PARS microscope designed for imaging thin, transmissible samples. METHODS: Peak SNR and in-focus acquisitions are achieved across entire tissue sections using the scattering signal from the PARS detection beam to measure the optimal focal plane. Whole slide images (WSI) are seamlessly stitched together using a custom contrast leveling algorithm. Identical tissue sections are subsequently H&E stained and brightfield imaged. The one-to-one WSIs from both modalities are visually and quantitatively compared. RESULTS: PARS WSIs are presented at standard 40x magnification in malignant human breast and skin samples. We show correspondence of subcellular diagnostic details in both PARS and H&E WSIs and demonstrate virtual H&E staining of an entire PARS WSI. The one-to-one WSI from both modalities show quantitative similarity in nuclear features and structural information. CONCLUSION: PARS WSIs are compatible with existing digital pathology tools, and samples remain suitable for histochemical, immunohistochemical, and other staining techniques. SIGNIFICANCE: This work is a critical advance for integrating label-free optical methods into standard histopathology workflows.


Assuntos
Neoplasias da Mama , Microscopia , Humanos , Microscopia/métodos , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/patologia , Tecnologia de Sensoriamento Remoto/métodos , Algoritmos , Feminino , Processamento de Imagem Assistida por Computador/métodos , Neoplasias Cutâneas/patologia , Neoplasias Cutâneas/diagnóstico por imagem , Pele/diagnóstico por imagem , Pele/química , Pele/citologia , Fótons , Desenho de Equipamento , Interpretação de Imagem Assistida por Computador/métodos
2.
Curr Oncol ; 30(11): 9760-9771, 2023 Nov 06.
Artigo em Inglês | MEDLINE | ID: mdl-37999128

RESUMO

Photon absorption remote sensing (PARS) is a new laser-based microscope technique that permits cellular-level resolution of unstained fresh, frozen, and fixed tissues. Our objective was to determine whether PARS could provide an image quality sufficient for the diagnostic assessment of breast cancer needle core biopsies (NCB). We PARS imaged and virtually H&E stained seven independent unstained formalin-fixed paraffin-embedded breast NCB sections. These identical tissue sections were subsequently stained with standard H&E and digitally scanned. Both the 40× PARS and H&E whole-slide images were assessed by seven breast cancer pathologists, masked to the origin of the images. A concordance analysis was performed to quantify the diagnostic performances of standard H&E and PARS virtual H&E. The PARS images were deemed to be of diagnostic quality, and pathologists were unable to distinguish the image origin, above that expected by chance. The diagnostic concordance on cancer vs. benign was high between PARS and conventional H&E (98% agreement) and there was complete agreement for within-PARS images. Similarly, agreement was substantial (kappa > 0.6) for specific cancer subtypes. PARS virtual H&E inter-rater reliability was broadly consistent with the published literature on diagnostic performance of conventional histology NCBs across all tested histologic features. PARS was able to image unstained tissues slides that were diagnostically equivalent to conventional H&E. Due to its ability to non-destructively image fixed and fresh tissues, and the suitability of the PARS output for artificial intelligence assistance in diagnosis, this technology has the potential to improve the speed and accuracy of breast cancer diagnosis.


Assuntos
Inteligência Artificial , Neoplasias da Mama , Humanos , Feminino , Reprodutibilidade dos Testes , Tecnologia de Sensoriamento Remoto , Neoplasias da Mama/patologia , Biópsia
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