Paradigm Shifts and Disruptive Technologies

Understanding the history to predict the future!

‘How things changed, following certain events, wrt Radiology as a field.’

What’s a paradigm shift?

Thomas Kuhn, the Harvard-based philosopher of science, in his classic book “The Structure of Scientific Revolutions” [1] coined the phrase “paradigm shift” to describe how major changes (revolutions) arise in science.

He conceived that “normal” science progresses steadily, within an accepted set of rules and assumptions (the paradigm), but may fundamentally change direction when some radical new idea or technology arises that disrupts the prevailing status.

For, e.g. – within a few weeks of the discovery of X-rays, it was being applied for clinical purposes. Also, with the discovery of the magnetic properties of electrons due to their spinning movement around their own axis, it was employed to develop NMR (nuclear magnetic resonance), and this became the basis for new-world MRI scans.

With new discoveries in physics and technical improvements, these imaging modalities are being enhanced.

(More on the history of imaging modalities, from then to now, will be discussed in the next week’s post – Thanks For Returning😊)

What is a disruptive technology?

The term “disruptive technologies” was coined by Joseph Bower and Clayton Christensen in a 1995 article published in the Harvard Business Review [2].

Examples of disruptive technologies include smartphones, digital cameras, and (many years ago) the motorcar.

Examples in the realm of radiology include -

1. Digital Radiography (DR) – it has replaced traditional film-based radiology, offering image acquisition, improved image quality, and the ability to share images instantly. Also, it reduced radiation exposure.
2. Augmented Reality(AR) and Virtual reality (VR) – immersive and interactive experiences for image-guided interventions, surgical procedures, and medical education.
3. Contrast Enhanced Imaging – improved visualization, enhanced diagnostic capabilities, and reduced the need for invasive procedures.
4. Telemedicine and Teleradiology – enabled remote access to consultations and diagnostics during emergency conditions.
5. Picture archiving and communication systems(PACS) – enables storage, retrieval, and distribution of medical images digitally.

AI has the potential to cause paradigm shift in medical imaging.

~Timeline~

Paradigm shift Disruptive technology Year

1st –X-rays discovery 1895

2nd – CT Computers 1970

3rd – MRI Magnetic property of electron 1980

Upcoming AI ~present~

Some remarkable uses of AI in radiology so far –

1. Image analysis and segmentation – quickly analyze medical images with segmentation of anatomical structures, as in CT & MRI, of lesions, tumors, etc.
2. Computer-aided diagnosis (CAD) – AI models have been used for second opinions in case of abnormality detection that radiologists might have overlooked.
3. Early detection and screening – early detection of Ca using thermal images fed into an AI model to look for early temperature changes in the cancerous transformation of normal cells.
4. Quantitative image analysis – AI models to extract quantitative data from medical images, which can be used in creating treatment plans and monitoring disease progression.
5. Data integration and knowledge sharing – like AI chatbots answering medical queries of patients
6. Remote and Point-of-care diagnostics – AI incorporated into mobile devices or integrated into telemedicine.
7. Predictive analytics – AI models to predict risk for future development of diseases after analyzing the patient’s medical records. E.g., Apollo Diagnostics in India has recently used AI for predicting CAD risk based on full-body medical evaluation, including ECHO images.
8. Qualitative control and standardization – Implementing standardized protocols can maintain a consistent quality of medical image interpretation. However, this has its own limitations.
9. Personalized medicine
10. Workflow optimization

- As disruptive technologies continue to revolutionize the field of radiology, embracing these paradigm shifts will not only empower healthcare professionals with unprecedented capabilities but also significantly enhance patient outcomes, ultimately shaping a brighter and more efficient future for medical imaging.

For further read👇🏻

[1] – Kuhn, TS. The Structure of Scientific Revolutions, University of Chicago Press; 1962

[2] – Bower, JL and Christensen, CM. Disruptive technologies: catching the wave, Harvard Business Review 1995; 73:43–53.