Advanced Tissue Ablation and Assessment System with Real-time Analytics
Legal Citation
Summary of the Inventive Concept
A next-generation tissue ablation system integrating real-time analytics, machine learning, and multi-modal imaging to optimize lesion progression and tissue-electrode contact during ablation procedures, enabling personalized medicine and paradigm-shifting advancements in medical treatment.
Background and Problem Solved
The original patent disclosed a system for tissue ablation and assessment, but it had limitations in real-time monitoring and optimization. The new inventive concept addresses these limitations by introducing advanced analytics, machine learning, and imaging modalities to provide real-time feedback on lesion progression and tissue-electrode contact, enabling more effective and personalized ablation treatments.
Detailed Description of the Inventive Concept
The advanced tissue ablation system comprises a machine learning model trained on a dataset of S parameter measurements and corresponding lesion sizes, a processing unit configured to receive S parameter measurements and output a predicted lesion size, and an RF ablation catheter with an antenna electrode connected to a vector network analyzer. The system transmits assessment signals having frequencies of at least 1 MHz to biological tissue, receives reflected assessment signals, and analyzes them to determine tissue-electrode contact and lesion progression. The system adjusts the ablation energy delivery in real-time based on the analysis, providing optimal ablation parameters for personalized medicine. Additionally, the system integrates with imaging modalities such as MRI or CT to provide real-time feedback on lesion progression and tissue-electrode contact.
Novelty and Inventive Step
The new claims introduce the novel concept of integrating machine learning, real-time analytics, and multi-modal imaging into a tissue ablation system, enabling personalized medicine and real-time optimization of ablation procedures. The inventive step lies in the combination of these advanced technologies to provide a paradigm-shifting approach to tissue ablation and assessment.
Alternative Embodiments and Variations
Alternative embodiments may include the use of different machine learning algorithms, varying antenna electrode designs, or integration with other imaging modalities such as ultrasound or optical coherence tomography. Variations may include the application of the inventive concept to different medical treatments, such as cancer therapy or cardiovascular procedures.
Potential Commercial Applications and Market
The advanced tissue ablation system has significant commercial potential in the medical device industry, particularly in the areas of oncology, cardiology, and neurology. The system's ability to provide personalized medicine and real-time optimization of ablation procedures can revolutionize the treatment of various diseases and conditions, offering a significant market opportunity.
CPC Classifications
| Section | Class | Group |
|---|---|---|
| A | A61 | A61B18/1815 |
| A | A61 | A61B5/0093 |
| A | A61 | A61B5/05 |
| A | A61 | A61B5/0507 |
| A | A61 | A61B5/0538 |
| A | A61 | A61B18/1492 |
| A | A61 | A61B2017/00026 |
| A | A61 | A61B2017/00039 |
| A | A61 | A61B2017/00084 |
| A | A61 | A61B2017/00106 |
| A | A61 | A61B2018/00023 |
| A | A61 | A61B2018/00029 |
| A | A61 | A61B2018/00351 |
| A | A61 | A61B2018/00577 |
| A | A61 | A61B2018/00636 |
| A | A61 | A61B2018/00702 |
| A | A61 | A61B2018/00773 |
| A | A61 | A61B2018/00785 |
| A | A61 | A61B2018/00791 |
| A | A61 | A61B2018/00827 |
| A | A61 | A61B2018/00875 |
| A | A61 | A61B2018/1435 |
| A | A61 | A61B2018/183 |
| A | A61 | A61B2018/1823 |
| A | A61 | A61B2018/1838 |
| A | A61 | A61B2018/1846 |
| A | A61 | A61B2018/1853 |
| A | A61 | A61B2018/1861 |
| A | A61 | A61B2018/1892 |
| A | A61 | A61B2090/065 |
| A | A61 | A61B2218/002 |
| A | A61 | A61B2576/023 |
Original Patent Information
| Patent Number | US 11,857,253 |
|---|---|
| Title | Tissue ablation and assessment system and method of use thereof |
| Assignee(s) | The Johns Hopkins University |