Tissue Impedance Diagnosis Using Layer Segmentation and PCA
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Solution Overview
Problem
Conventional methods for diagnosing skin cancer, particularly malignant melanoma, face challenges in accurately and efficiently processing multivariate impedance data to detect small-sized abnormalities and provide sufficient tissue resolution, leading to difficulties in early detection and differentiation between diseased and healthy tissue.
Innovation Solution
A medical apparatus and method that utilizes a trained evaluation system to process impedance data from multiple tissue layers with high resolution, reduces noise content, and applies dimensionality reduction techniques such as PCA or Cole-Cole equivalent circuit modeling, combined with additional clinical data like ABCDE characteristics, to enhance diagnostic accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional impedance measurement methods are used, then the measurement process is simple, but the measurement precision is insufficient to detect small-sized abnormalities
Solution Approach 1:
The patent segments the tissue into multiple discrete layers (epidermis, dermis, subcutaneous tissue) and measures impedance at multiple depths within each layer. This segmentation enables detection of small abnormalities by analyzing impedance variations at different tissue levels, transforming a single complex measurement into multiple targeted measurements that can identify localized diseased regions.
Solution Approach 2:
The patent adds the depth dimension to impedance measurements by obtaining data from multiple tissue layers. This transforms conventional two-dimensional surface impedance maps into three-dimensional impedance distributions, enabling detection of small abnormalities that extend vertically through tissue layers and providing better spatial resolution for locating diseased regions.
2Measurement precision
If multivariate impedance data is measured to improve diagnostic accuracy, then the diagnostic precision improves, but the difficulty of analyzing the data increases
Solution Approach 1:
The patent applies different analysis methods to different tissue layers based on their specific characteristics. Each layer (epidermis, dermis, subcutaneous tissue) is analyzed with layer-appropriate parameters and comparison methods, allowing diagnostic precision to be optimized for each tissue type while managing overall data complexity through localized analysis strategies.
Solution Approach 2:
The patent transforms complex multivariate impedance data into simplified diagnostic parameters by comparing impedance values across layers and identifying patterns. This parameter transformation converts difficult-to-analyze raw impedance measurements into interpretable diagnostic indicators that maintain diagnostic accuracy while reducing analysis complexity.
3Manufacturing precision
If impedance measurements are taken at multiple tissue layers to improve structural resolution, then the tissue resolution improves, but the quantity of data increases
Solution Approach 1:
The patent extracts diagnostically relevant information from the large volume of multi-layer impedance data by comparing measurements across layers and identifying patterns specific to diseased tissue. This extraction process isolates key diagnostic features from the full dataset, maintaining high tissue resolution while reducing the effective data volume that requires detailed analysis.
Solution Approach 2:
The patent performs preliminary processing of impedance data by organizing measurements from multiple layers into structured formats and pre-identifying patterns before final diagnosis. This preliminary action prepares the data in advance, making subsequent analysis more efficient and reducing the computational burden of handling large datasets.
4Reliability
If early detection of small tumors is pursued to improve patient outcomes, then the reliability of diagnosis improves, but the measurement precision required increases
Solution Approach 1:
The patent implements a nested measurement approach where impedance measurements at different tissue layers are combined hierarchically. Surface measurements provide context, intermediate layers provide transitional data, and deep layers provide information about underlying structures. This nesting of measurement levels enhances reliability for detecting small tumors by providing multiple lines of evidence from different depths.
Solution Approach 2:
The patent uses the depth dimension to enhance detection of small tumors by measuring impedance variations vertically through tissue layers. This three-dimensional measurement approach increases measurement precision for small lesions by capturing their vertical extent and impedance characteristics at different depths, improving early detection reliability.
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
The solution enables accurate and efficient detection of small anomalies in tissue, improving diagnostic accuracy and structural resolution for skin cancer, allowing for early identification of malignant conditions.
Implementation Method 1
electrical impedance constitutes a very sensitive indicator of changes in organic and biological material, especially in tissues such as mucous membranes, skin and integuments of organs
Data Source
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AI summary
The present invention relates to a method and a medical device for diagnosing a diseased condition in tissue of a human or animal subject, wherein tissue electrical impedance measurements are employed. At least one set of data pre-processing rules are applied to impedance of a target tissue region and impedance of a reference tissue region, wherein the reference tissue region is located in close proximity to the target tissue region. The impedance data of the target tissue region and the impedance data of the reference tissue region comprises a plurality of impedance values measured in the target tissue region and the reference tissue region, respectively, wherein the tissue measurements in the two tissue regions are performed substantially concurrently or immediately consecutively. On the basis of the pre-processed data, a trained evaluation system algorithm diagnoses the diseased condition in the target tissue region.