ESR Spectroscopy and Logistic Regression for Malignancy Localization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for detecting indicators of malignancy in extracellular fluids, such as blood, suffer from poor sensitivity and a limited focus on specific metabolites, making them inadequate for comprehensive screening and localization of malignant growths.
Innovation Solution
The method involves using electron spin resonance spectroscopy (ESR) to analyze spectra from aliquots containing serum albumin, where the concentration of a spin probe and a polar reagent varies. Biophysical parameters are determined from these spectra and input into a trained logistic regression model to predict the probability of disease indicators related to malignancy and its localization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing techniques are used to detect metabolites in blood samples, then detection of specific metabolites is achieved, but sensitivity is poor and coverage is limited to a narrow set of metabolites
Solution Approach 1:
The patent applies universality by using ESR spectroscopy to detect multiple types of metabolites and molecular species simultaneously in a single analysis, rather than being limited to detecting a narrow set of specific metabolites. The method can identify various metabolic indicators including but not limited to amino acids, organic acids, and other small molecules, providing comprehensive coverage across different metabolite classes while maintaining high sensitivity for each type.
2Measurement precision
If techniques focused on one localization are used, then detection for that specific location is achieved, but ability to detect other malignant growths is limited
Solution Approach 1:
The patent implements multi-functionality by developing a comprehensive detection system that can identify malignant growths at multiple different locations and types simultaneously. The method analyzes blood metabolite profiles to detect indicators of malignancy regardless of their anatomical location, enabling the system to screen for various cancer types and localizations in a single test, thereby eliminating the limitation of techniques that focus on only one specific location.
3Adaptability or versatility
If comprehensive screening for all malignant indicators is implemented, then detection coverage is improved, but analysis complexity and time increase
Solution Approach 1:
The patent replaces complex multi-step analytical procedures with a unified ESR spectroscopy-based method. Instead of requiring multiple separate detection techniques for different metabolite classes, the system uses a single spectroscopic approach that simultaneously measures various metabolic parameters. This substitution of mechanical/chemical analysis methods with spectroscopic measurement simplifies the overall analysis process while maintaining comprehensive detection coverage.
Solution Approach 2:
The patent applies parameter changes by transforming the detection approach from measuring individual metabolite concentrations to measuring ESR spectral parameters that reflect the overall metabolic state. By changing the measurement parameters to ESR frequency and intensity values, the system can comprehensively screen for multiple types of malignancy indicators simultaneously without increasing analytical complexity, as the ESR method provides a unified parameter space for detecting diverse metabolic alterations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables reliable identification and localization of malignant processes with diagnostic sensitivity and specificity between 80 and 90% for certain types of cancers, such as lymphoma and pancreatic cancer, facilitating targeted treatment.
Implementation Method 1
analysing the carrier protein to detect indicators of a malignancy and its localisation within the human body... using electron spin resonance spectroscopy (ESR)
Data Source
AI summary
Provided herein are methods for identifying and treating a malignancy in a patient. Aspects of the described methods are performed through use of a computing device. The method comprises receiving at the computing device a plurality of spectra acquired from a corresponding plurality of aliquots containing a biophysiological carrier protein. At least one of a concentration of a spin probe and a concentration of a polar reagent varies between the aliquots. The computing device then determines biophysical parameters based on the received spectra and applies at least parts of the received spectra and the biophysical parameters as an input to a trained logistic regression model. The logistic regression model trained to determine a probability of applied input parameters relating to one or more of a plurality of predetermined diseases and/or disease localisations. The trained model is used to determine a probability of the input parameters relating to one or more of said predetermined diseases and/or disease localisations and outputs a result of the determination, which can be used to determine and then provide proper therapeutic treatments.