Insights

PROCESS & SCALABILITY

Insights

Cireca delivers new insights into tumor and tissue composition by utilizing the interaction of mid-IR radiation with the biochemical components of tissue, including proteins, lipids, metabolites, and nucleic acids. The spatial variations of these tissue components are detected qualitatively and quantitatively and allow identification of tissue type, disease state, tumor heterogeneity and tissue microenvironment.

Discovery

Our Process

Microenvironment

Visualize microenvironmental changes reported by spatially resolve biochemical signatures.

Gold Standard Annotation

Establish new independent variables through biochemical signatures detected and by SHP CIRECA and mapped 1:1 to reference gold standard annotations and regions of interest in control samples (e.g. H&E, IHC, CISH, FISH).

Cell Type & Biomarker Dx

Study cohorts, TMAs, whole samples, serial and consecutive samples slices from specimen blocks are characterized by biochemical signatures, molecular variance images and composition prediction models to point researchers to areas of insight & discovery in tissue samples.

View Examples

Small Cell Lung Cancer (SCLC), Molecular Variance Images, Model Prediction

Small Cell Lung Cancer (SCLC)
SCLC Molecular Variance Image, 3 Clusters
SCLC Molecular Variance Image, 5 Clusters
Small Cell Lung Cancer (SCLC), SHP CIRECA model prediction image
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Small Cell Lung Cancer (SCLC)

Small Cell Lung Cancer (SCLC)

SCLC sample stained by H&E

SCLC Molecular Variance Image, 3 Clusters

SCLC Molecular Variance Image, 3 Clusters

Small cell lung cancer (SCLC) molecular variance image showing molecular heterogeneity at 3 levels using 3 clusters.

SCLC Molecular Variance Image, 5 Clusters

SCLC Molecular Variance Image, 5 Clusters

Small cell lung cancer (SCLC) sample molecular variance image showing 5 levels of heterogeneity in 5 clusters.

Small Cell Lung Cancer (SCLC), SHP CIRECA model prediction image

Small Cell Lung Cancer (SCLC), SHP CIRECA model prediction image

Lung cancer tissue types, subtypes and subclass prediction model image rendered by SHP CIRECA pseudo color contrast image algorithm. Colors show tissue type classification with pixel level predictions aggregated and reported in a full sample prediction image.

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Lung Adenocarcinoma (ADC)

Adenocarcinoma (ADC)
ADC Molecular Variance Image, 2 Clusters
Adenocarcinoma (ADC) molecular variance image, 5 clusters
Adenocarcinoma (ADC) annotations used to develop prediction models
Adenocarcinoma (ADC), SHP CIRECA model prediction image
Adenocarcinoma (ADC)

Adenocarcinoma (ADC)

Adenocarcinoma (ADC) sample stained with H&E.

ADC Molecular Variance Image, 2 Clusters

ADC Molecular Variance Image, 2 Clusters

NSCLC, adenocarcinoma (ADC) molecular variance image showing molecular heterogeneity at 2 levels using 2 clusters.

Adenocarcinoma (ADC) molecular variance image, 5 clusters

Adenocarcinoma (ADC) molecular variance image, 5 clusters

Lung adenocarcinoma (ADC) sample molecular variance image showing 5 levels of heterogeneity in 5 clusters.

Adenocarcinoma (ADC) annotations used to develop prediction models

Adenocarcinoma (ADC) annotations used to develop prediction models

User interaction results in gold standard pathology annotation developed in H&E and projected onto SHP CIRECA IR images and pixels by image registration.

Adenocarcinoma (ADC), SHP CIRECA model prediction image

Adenocarcinoma (ADC), SHP CIRECA model prediction image

Lung cancer tissue types, subtypes and subclass prediction model image rendered by SHP CIRECA pseudo color contrast image algorithm. Colors show tissue type classification with pixel level predictions aggregated and reported in a full sample prediction image (magenta is ADC).

Lung Normal

Lung Normal
Lung normal molecular variance Image, 2 clusters
Lung normal molecular variance Image, 5 clusters
Lung normal TRUE prediction image
Lung normal whole sample prediction image
Lung Normal

Lung Normal

Lung resection normal tissue sample

Lung normal molecular variance Image, 2 clusters

Lung normal molecular variance Image, 2 clusters

Lung normal molecular variance Image, 2 levels of heterogeneity shown using 2 clusters

Lung normal molecular variance Image, 5 clusters

Lung normal molecular variance Image, 5 clusters

Lung normal molecular variance Image, 5 levels of heterogeneity shown using 5 clusters

Lung normal TRUE prediction image

Lung normal TRUE prediction image

Lung normal TRUE prediction image generated by SHP CIRECA™ lung tissue type model. Annotation regions used to verify model performance are shown as predicted.

Lung normal whole sample prediction image

Lung normal whole sample prediction image

Lung normal, whole sample prediction image generated by SHP CIRECA™ lung tissue type model. RED prediction indicated normal tissue is detected by the model.

Lung Squamous Cell Carcinoma (SqCC)

Lung Squamous Cell Carcinoma (SqCC)
Lung Squamous Cell Carcinoma (SqCC) Molecular Variance Image, 3 clusters
Lung squamous cell carcinoma (SqCC) molecular variance Image, 5 clusters
Lung squamous cell carcinoma (SqCC) TRUE prediction image
Lung squamous cell carcinoma (SqCC) whole sample prediction image
Lung Squamous Cell Carcinoma (SqCC)

Lung Squamous Cell Carcinoma (SqCC)

Lung squamous cell carcinoma (SqCC) stained by H&E

Lung Squamous Cell Carcinoma (SqCC) Molecular Variance Image, 3 clusters

Lung Squamous Cell Carcinoma (SqCC) Molecular Variance Image, 3 clusters

Lung Squamous Cell Carcinoma (SqCC) Molecular Variance Image showing heterogeneity at 3 levels using 3 clusters

Lung squamous cell carcinoma (SqCC) molecular variance Image, 5 clusters

Lung squamous cell carcinoma (SqCC) molecular variance Image, 5 clusters

Lung squamous cell carcinoma (SqCC) molecular variance Image, 5 levels of heterogeneity shown using 5 clusters

Lung squamous cell carcinoma (SqCC) TRUE prediction image

Lung squamous cell carcinoma (SqCC) TRUE prediction image

Lung squamous cell carcinoma TRUE prediction image generated by SHP CIRECA™ lung tissue type model. Annotation regions used to verify model performance are shown as predicted (Cyan is SqCC).

Lung squamous cell carcinoma (SqCC) whole sample prediction image

Lung squamous cell carcinoma (SqCC) whole sample prediction image

Lung squamous cell carcinoma whole sample prediction image generated by SHP CIRECA™ lung tissue type model. Annotation regions used to verify model performance are shown as predicted (Cyan is SqCC, Grey is necrosis).

Mechanism of Action

HIGHLY SENSITIVE AND SPECIFIC DETECTION OF BIOCHEMICAL VARIANCE WITHOUT WET CHEMISTRY

Mechanism of Action

Microenvironment is detected by biochemical variances characterized by Pixel1 and Pixel2 signatures

Contact Us

Contacting Cireca

Connect with our team for more information, business opportunities

discovery@cireca.com

19 Blackstone Street, Suite 26 Cambridge, MA 02139