US 12,433,488 B2
System and methods for real time raman spectroscopy for cancer detection
Rajeev Yadav, Laval (CA); Jean-Philippe Tremblay, Montreal (CA); and Rajeev Agarwal, Dollard-des-Ormeaux (CA)
Assigned to 14336186 CANADA CORP. (EXCLARO), Mont-Saint-Hilaire (CA)
Appl. No. 16/962,903
Filed by 14336186 CANADA CORP. (EXCLARO), Mont-Saint-Hilaire (CA)
PCT Filed Jan. 17, 2019, PCT No. PCT/IB2019/050409
§ 371(c)(1), (2) Date Jul. 17, 2020,
PCT Pub. No. WO2019/142136, PCT Pub. Date Jul. 25, 2019.
Claims priority of provisional application 62/618,607, filed on Jan. 17, 2018.
Prior Publication US 2023/0240538 A1, Aug. 3, 2023
Int. Cl. A61B 5/00 (2006.01); G01J 3/02 (2006.01); G01J 3/44 (2006.01); G01N 21/65 (2006.01)
CPC A61B 5/0075 (2013.01) [A61B 5/4064 (2013.01); A61B 5/7221 (2013.01); G01J 3/0218 (2013.01); G01J 3/44 (2013.01); G01N 21/65 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A method of detection of cancerous tissue using Raman spectroscopy comprising:
determining, for a tissue type of interest, an excitation power and/or an excitation exposure time of a laser light source to maximize a range of a charge-coupled device (CCD) detector based on real-time Raman measurements obtained when the laser light source operates at predetermined excitation power and/or excitation exposure time settings, the CCD detector for acquiring Raman data;
acquiring the Raman data in situ during surgery from the tissue type of interest when the laser light source operates according to the determined excitation power and/or excitation exposure time to excite the tissue type of interest;
assessing a quality of the Raman data and, on the basis of the quality assessment, excluding Raman data that does not meet predetermined quality standards;
for Raman data that has met the predetermined quality standards, computing signal-to-noise ratio and excluding Raman data with insufficient signal-to-noise ratio, wherein computing the signal-to-noise ratio comprises computing a corresponding signal quality at predetermined spectral locations, selected based on the tissue type of interest;
for Raman data that has sufficient signal-to-noise ratio, extracting Raman data features that have been determined to have high significance in separating cancerous from normal tissue in the tissue type of interest;
classifying the Raman data according to relative values of the extracted features; and
providing an answer as to whether the Raman data indicates that the tissue type of interest is cancerous; wherein the preceding steps are all carried out in real time during surgery.