University of Pittsburgh

Shikhar Uttam Fnu

Yang Liu

Srinivas C Chennubhotla

Douglass L Taylor

Randall E Brand

Hoa V Pham

Hoa Vinh Pham

Pin Wang

A method of predicting cancer recurrence risk for an individual includes receiving patient spatial multi-parameter cellular and sub-cellular imaging data for a tumor of the individual, and analyzing the patient spatial multi-parameter cellular and sub-cellular imaging data using a prognostic model for predicting cancer recurrence risk to determine a predicted cancer recurrence risk for the individual, wherein the joint prognostic model is based on spatial correlation statistics among features derived for a plurality of intra-tumor spatial domains from spatial multi-parameter cellular and sub-cellular imaging data obtained from a plurality of cancer patients.

Predicting cancer recurrence from spatial multi-parameter cellular and subcellular imaging data

Due to potential sampling errors (due to small tissue samples not necessarily directly from the developing tumor) and limited optical resolution (&#x2dc;1 micron), cancer may be missed or detected too late for optimal treatment, or conservative interpretation of indeterminate findings could lead to unnecessary surgery. The novel technology herein&#x2014;Spatial-domain Low-coherence Quantitative Phase Microscopy (SL-QPM)&#x2014;can detect structural alterations within cell nuclei with nanoscale sensitivity (0.9 nm) (or nuclear nano-morphology) for 'nano-pathological diagnosis' of cancer. SL-QPM uses original, unmodified cytology and histology specimens prepared with standard clinical protocols and stains. SL-QPM can easily integrate in existing clinical pathology laboratories. Results quantified the spatial distribution of optical path length or refractive index in individual nuclei with nanoscale sensitivity, which could be applied to studying nuclear nano-morphology as cancer progresses. The nuclear nano-morphology derived from SL-QPM offers significant diagnostic value in clinical care and subcellular mechanistic insights for basic and translational research.

Spatial-domain low-coherence quantitative phase microscopy

Systems, methods and other embodiments associated with spatial-domain Low-coherence Quantitative Phase Microscopy (SL-QPM) are described herein. SL-QPM can detect structural alterations within cell nuclei with nanoscale sensitivity (0.9 nm) (or nuclear nano-morphology) for 'nano-pathological diagnosis' of cancer. SL-QPM uses original, unmodified cytology and histology specimens prepared with standard clinical protocols and stains. SL-QPM can easily integrate in existing clinical pathology laboratories. Results quantified the spatial distribution of optical path length or refractive index in individual nuclei with nanoscale sensitivity, which could be applied to studying nuclear nano-morphology as cancer progresses. The nuclear nano-morphology derived from SL-QPM offers significant diagnostic value in clinical care and subcellular mechanistic insights for basic and translational research. Techniques that provide for depth selective investigation of nuclear and other cellular features are disclosed.

Provided are systems, methods, and other embodiments associated with depth-resolved spatial-domain low-coherence quantitative phase microscopy for high-throughput analysis of 3D nanoscale architectural alterations in unstained tissue and cells. A spatial-domain low-coherence quantitative phase microscopy apparatus includes a drOPD mapping module, a transmission phase imaging module, and a bright-field and transmission phase imaging module. The drOPD mapping module includes a reflection-mode low-coherence spectral interferometry for drOPD mapping of unstained tissue. The transmission phase imaging module includes transmission quantitative phase imaging of unstained and stained tissue and produce an image registration reference. The bright-field and transmission phase imaging module includes bright-field imaging of H&E-stained tissue for nuclei identification and pathology correlation.

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Pittsburgh, PA, United States of America

Shikhar Uttam Fnu