Published Technical Disclosure Archive

Next-Generation Hollow Organ Imaging System

Publication ID: 24-11857145_0010_PTD
Published: November 07, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Next-Generation Hollow Organ Imaging System,” Published Technical Disclosure No. 24-11857145_0010_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857145_0010_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,145.

Summary of the Inventive Concept

The present inventive concept envisions a future evolution of hollow organ imaging, integrating advanced multi-spectral imaging, machine learning, and digital twin technologies to provide real-time, personalized, and predictive insights into hollow organ function and health.

Background and Problem Solved

The original patent, 'Method for providing image data of a hollow organ,' addressed the challenge of assessing vitality and integrity of organs using computed tomography (CT) images. However, the current invention recognizes the limitations of this approach and seeks to revolutionize hollow organ imaging by leveraging cutting-edge technologies to provide more accurate, comprehensive, and personalized diagnoses.

Detailed Description of the Inventive Concept

The next-generation hollow organ imaging system comprises a multi-energy CT scanner, a contrast agent injection system, and a machine learning-based image analysis module. This integrated system enables real-time, multi-spectral imaging of hollow organs, allowing for the detection of abnormalities and the generation of personalized, predictive models of hollow organ function. The system can also incorporate targeted, molecular imaging agents for non-invasive, functional imaging of hollow organs. Furthermore, the system can create digital twins of hollow organs, enabling simulations of hollow organ function and predicting potential outcomes.

Novelty and Inventive Step

The present inventive concept introduces a paradigm shift in hollow organ imaging by combining advanced imaging modalities, machine learning algorithms, and digital twin technologies. The integration of these components enables real-time, personalized, and predictive insights into hollow organ function, which is not possible with the original patent's method.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different imaging modalities, such as MRI or ultrasound, or the incorporation of additional machine learning algorithms for more accurate predictions. The system could also be adapted for use in various medical specialties, such as cardiology or oncology.

Potential Commercial Applications and Market

The next-generation hollow organ imaging system has significant commercial potential in the medical imaging and healthcare industries. The system's ability to provide real-time, personalized, and predictive insights into hollow organ function could revolutionize the diagnosis and treatment of various diseases, such as cancer, cardiovascular disease, and gastrointestinal disorders.

CPC Classifications

SectionClassGroup
A A61 A61B6/481
A A61 A61B6/032
A A61 A61B6/4241
A A61 A61B6/469
A A61 A61B6/50
A A61 A61B6/5205
A A61 A61M5/007

Field of Art

Medical imaging technologies, specifically computed tomography (CT) scanning and contrast agent-based diagnostic imaging of hollow organs, requiring advanced knowledge of medical imaging physics, contrast agent chemistry, and diagnostic imaging techniques

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical imaging specialist with expertise in CT scanning technologies, spectral imaging techniques, contrast agent design, and image processing algorithms, holding advanced degrees in biomedical engineering, medical physics, or related disciplines

Obviousness Rationale

A person having ordinary skill in the art would recognize that the published technical disclosure represents a predictable extension of the source patent's core imaging methodology by integrating emerging technologies like machine learning and digital twin modeling, which are well-established approaches for enhancing medical imaging diagnostic capabilities. The PTD's variations systematically apply known computational and imaging techniques to the foundational spectral CT imaging method disclosed in the source patent. These extensions would be considered obvious improvements that leverage standard technological progression in medical imaging research.

Obvious Combinations & Variations

Source Patent Element
Spectrally resolved computed tomography data with multiple contrast agents
PTD Variation
Multi-energy CT scanner with machine learning-based image analysis module
Obviousness Reasoning
Predictable application of machine learning to enhance spectral imaging analysis, representing a known technique for improving diagnostic image interpretation
Source Patent Element
Contrast agent filling of a hollow organ's lumen
PTD Variation
Targeted molecular imaging agents for functional imaging
Obviousness Reasoning
Logical extension of contrast agent technology to provide more sophisticated diagnostic capabilities, utilizing known molecular imaging principles
Source Patent Element
Image data generation of hollow organ structures
PTD Variation
Digital twin generation and simulation of organ function
Obviousness Reasoning
Predictable computational approach to transform imaging data into predictive models, representing a standard technique in advanced medical imaging research
Source Patent Element
Computed tomography imaging of hollow organs
PTD Variation
Real-time, personalized predictive modeling of organ function
Obviousness Reasoning
Obvious combination of existing imaging technologies with emerging machine learning techniques to enhance diagnostic capabilities
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857145 and the published technical disclosure, a person having ordinary skill in the art would find the claimed variations obvious, as they represent predictable technological extensions utilizing standard medical imaging research methodologies. The disclosed innovations constitute prima facie obvious combinations of known imaging techniques, machine learning algorithms, and computational modeling approaches that would be readily apparent to a skilled practitioner in the field of medical imaging technologies.

Original Patent Information

Patent NumberUS 11,857,145
TitleMethod for providing image data of a hollow organ
Assignee(s)Siemens Healthcare Limited