Method of characterization and differentiation of tissue
First Claim
1. A method of soft tissue characterization and soft tissue differentiation comprising the steps of:
- (a) detecting a lesion in said tissue;
(b) applying an increasing compression force over said lesion and collecting a sequence of stress patterns as a function of said increasing compression force;
(c) calculating from said sequence of stress patterns at least three elasticity features characterizing said lesion, said elasticity features selected from a group consisting of strain hardening, loading curve average slope, lesion peak signal under a predetermined load, tissue heterogeneity, lesion shape and lesion mobility;
(d) inputting said at least three calculated elasticity features into a statistical classifier to calculate probabilities of possible diagnostic outcomes, said statistical classifier created in advance using a dataset of previously collected samples with known clinical status, said samples having been collected from several patients and including data on elasticity features that are the same as said at least three calculated elasticity features; and
(e) selecting a diagnostic outcome with prevailing calculated probability for providing a diagnosis of said soft tissue.
1 Assignment
0 Petitions
Accused Products
Abstract
A novel method for soft tissue characterization includes obtaining a sequence of surface stress patterns as a function of an increasing compression force when a probe is pressed against the tissue over the location of the lesion of interest. A number of elasticity features are then calculated to characterize the tissue and the lesion located therein including strain hardening, loading curve average slope, lesion peak signal under a predetermined load, tissue heterogeneity, lesion shape and lesion mobility. At least three elasticity features are provided as an input to a statistical Bayesian classifier trained on a clinical database to calculate the probability of the lesion being benign or malignant. Additional patient-related parameters may be further provided as inputs to the classifier to increase the accuracy of differentiation between benign and malignant lesions. These parameters include a family history of cancer disease, a patient-inherited genetic factor, a history of said tissue related diseases, patient'"'"'s age, patient'"'"'s weight, and patient'"'"'s lifestyle and dietary factors. The method of the invention along with other non-invasive examinations of lesions may help in reducing the rate of biopsies, specifically breast tissue biopsies.
17 Citations
24 Claims
-
1. A method of soft tissue characterization and soft tissue differentiation comprising the steps of:
-
(a) detecting a lesion in said tissue; (b) applying an increasing compression force over said lesion and collecting a sequence of stress patterns as a function of said increasing compression force; (c) calculating from said sequence of stress patterns at least three elasticity features characterizing said lesion, said elasticity features selected from a group consisting of strain hardening, loading curve average slope, lesion peak signal under a predetermined load, tissue heterogeneity, lesion shape and lesion mobility; (d) inputting said at least three calculated elasticity features into a statistical classifier to calculate probabilities of possible diagnostic outcomes, said statistical classifier created in advance using a dataset of previously collected samples with known clinical status, said samples having been collected from several patients and including data on elasticity features that are the same as said at least three calculated elasticity features; and (e) selecting a diagnostic outcome with prevailing calculated probability for providing a diagnosis of said soft tissue. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 23)
-
-
11. A method of soft tissue characterization and soft tissue differentiation comprising the steps of:
-
(a) detecting a lesion and a lesion location in said tissue; (b) applying an increasing compression force over said lesion location and collecting a sequence of stress patterns, said sequence of stress patterns being a function of said increasing compression force; (c) calculating from said sequence at least three elasticity features characterizing said lesion; (d) generating a probability distribution for possible diagnostic outcomes for said lesion by inputting said at least three elasticity features into a statistical classifier created using a clinical database of cases from several patients (i) having known diagnoses and (ii) including data on elasticity features that are the same as said at least three calculated elasticity features; and (e) providing a diagnosis of said soft tissue based on the diagnostic outcome with prevailing calculated probability. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22)
-
-
24. A method of soft tissue characterization and soft tissue differentiation comprising the steps of:
-
(a) detecting a lesion in said tissue; (b) compressing said tissue over said lesion with an increasing compression force and collecting a sequence of stress patterns as a function of said increasing compression force; (c) calculating from said sequence of stress patterns at least three elasticity features characterizing said lesion; (d) generating a probability distribution for possible diagnostic outcomes for said lesion by inputting said at least three elasticity features into a statistical classifier created using a clinical database of cases from several patients (i) having known diagnoses and (ii) including data on elasticity features that are the same as said at least three calculated elasticity features; and (e) providing a diagnosis of said soft tissue based on said probability distribution.
-
Specification