A Green Vision for Healthcare: Implementation of
RadioView.AI for Radiology Films Free Imaging

Executive Summary

  • Completed in 02 hospitals
  • Working under progress in 09 hospitals
  • Planned to be initiated soon in 04 hospitals

Why Fund?

Join us in reshaping healthcare’s future! Your support drives groundbreaking initiatives to democratize digital radiology, paving the way for a greener and sustainable healthcare.

Sponsorship Packages

Silver

We will provide:

  • Edge Device
  • Integration support
  • One year of Cloud expenses

$500/month

Gold

We will provide:

  • Edge Device
  • Integration support
  • One year of Cloud expenses

$750/month

Platinum

We will provide:

  • Edge Device
  • Integration support
  • One year of Cloud expenses

$1000/month

Large-Scale Sponsorship

 

Sponsorship starting from
$2 million, ensuring sustainable support and development for up to 5 years.

Goal

To transform radiological imaging by replacing films with the RadioView.AI application, maintaining accuracy while promoting environmental conservation.

Gap Analysis and Proposed Solution

Currently, 353 million tonnes of plastic waste is generated annually worldwide. Projections indicate that these figures are predicted to increase four times, reaching an estimated 1 billion tonnes of plastic waste by the year 2060 (Fleck A, 2022). Globally, approximately 2 billion radiographs are generated annually, encompassing CT scans, mammograms, and chest X-rays, with the medical field consuming 94–98% of these films (Hilal N et al., 2022).

Radiographic films employed in medical applications consist of a polyester sheet coated with a thin gelatin layer infused with silver grains. Traditionally, chemical processing and incineration have been the primary methods for disposing of X-ray films. However, incineration results in a significant loss of valuable silver, approximately 25–30%, and the emitted smoke is both illegal and highly toxic. Consequently, X-ray photographic films, which contain silver, are considered hazardous waste due to their toxicity (Hilal N et al., 2022; Thrall JH et al., 2023).

Plastic additives used in radiological films are recognized as endocrine disruptors and carcinogens (Veitch A, 2021). These chemicals pose a significant threat to human health primarily through skin contact (leading to dermatitis), ingestion, and inhalation (Aalto-Korto K et al., 2019). Microplastics, considered hazardous pollutants, can enter the food chain when ingested by various marine and freshwater organisms, causing a range of health issues. Consequently, when humans consume animals exposed to plastic additives and microplastics, they may face potential harm. Biomonitoring studies on human tissues have detected plastic components, highlighting the presence of these environmental contaminants in the human population (Adeniran AA & Shakantu W, 2022).

Figure 1: Only recycling is not enough to solve plastic waste generation and its impact on environment (Fleck A, 2022)

Statistics from Organization for Economic Co-operation and Development (OCED) show that a mere 9% of plastic waste is currently subjected to recycling efforts, leaving a staggering 91% to become a harmful presence in our environment. Even more worrisome is the prediction that even if we intensify our recycling endeavors, a substantial 83% of the world’s plastic waste would persist in the environment, continuing to inflict damage (OCED, 2019). This dire situation underscores the urgent need for comprehensive solutions that go beyond recycling and focus on reducing plastic consumption to address the prevalent issue of plastic pollution and its adverse impacts on our planet (Figure 1).

Report released by The Lancet Commission on Pollution and Health, Global Alliance for Health and Pollution states: “In 2015, diseases caused by air, water and soil pollution were responsible for 9 million premature deaths, that is 16% of all global death. Exposures to contaminated air, water and soil kill more people than smoking, hunger, natural disasters, war, AIDS, or malaria” (Cohen S, 2017). Approximately 92% of these deaths were reported from LMICs (The Lancet Commission on Pollution and Health, 2017). Therefore, this highlights the pressing need to mitigate pollution and its resultant health impacts on a global scale, with a heightened sense of urgency, particularly in LMICs (Figure 2).

Figure 2: A. Statistics for global mortality attributed to pollution, B. Statistics for distribution of pollution attributed mortality among low/middle income and high income countries.

Artificial Intelligence (AI) is revolutionizing numerous fields, including biomedical research, healthcare systems, and environmental conservation (Castiglioni I et al., 2021; Gore JC, 2020). In this project, we propose the integration of the digital technology “RadioView.AI Application” into clinical settings, offering the potential to eliminate the need for radiology imaging films. Our partner company, NeuroCareAI, has developed this groundbreaking model and is committed to offering it at no additional cost to Low- and Middle-Income Countries (LMICs).

By implementing RadioView.AI within healthcare settings, we can significantly reduce the waste generated from radiology films, consequently mitigating their environmental impact. Moreover, this technology will streamline the delivery of care, reducing treatment time and ultimately leading to improved patient outcomes for patients. Our cutting-edge solution has the power to disrupt traditional approaches, simultaneously benefiting the environment and healthcare, marking a significant step towards a more sustainable and efficient future.

What is RadioView.AI?

The RadioView.AI application revolutionizes medical imaging by offering seamless access to various scans like MRI, X-rays, and CT scans with unparalleled accuracy and contrast akin to traditional radiology films. This transformative tool not only optimizes patient care delivery, facilitating swift and efficient diagnoses but also champions environmental conservation by eliminating the need for radiological films. By harnessing RadioView.AI, healthcare providers streamline their processes while significantly reducing the ecological footprint associated with film-based imaging, marking a crucial stride toward a more sustainable healthcare landscape.

Project Aim

The project aims to implement RadioView.AI in hospitals, introducing a digital platform for viewing scans to revolutionize care delivery and promote environmental sustainability. By eliminating the need for radiology films, we significantly reduce environmental pollution.

Prototype Image

Figure 3: Prototype image of the RadioView.AI application showing user interface

Current Progress

We have already started the integration of the application in various hospitals and medical centers of Pakistan.

Integration Completed

SNo. Site Type
1. Holy Family Hospital Hospital
2. Sarwar Foundation Hospital Hospital

Integration Initiated and Currently in Progress

SNo. Site Type
1. Rai Ali Nawaz Hospital Hospital
2. Al-Madina Diagnostics Radiology Center
3. Abid Imaging Center Radiology Center
4. Bashir Diagnostic Imaging Center Radiology Center
5. Sandho Diagnostic Center Hospital
6. Modern Diagnostic Center Radiology Center
7. Pak CT Scan Center Radiology Center
8. Mian Diagnostics Radiology Center
9. Ittefaq 3D CT Scan Radiology Center

Integration Process to be Initiated Soon

SNo. Site Type Status
1. Shifa Hospital Private Hospital Demo Given – Approved by HOD Neurology
2. Ghurki Hospital Trust Hospital Demo Given – Awaiting Response
3. Services Hospital Teaching Hospital Demo Given to HOD – Awaiting Administration’s Approval
4. Gulab Devi Hospital Teaching Hospital Demo Given – Awaiting HOD’s Response

Environmental Impact of the Project

  1. Environmental Sustainability: By eliminating the need for radiology films in health care, the project significantly reduces environmental pollution associated with film production and disposal. This eco-conscious approach aligns with global efforts to reduce healthcare’s environmental footprint, contributing to a healthier planet.
  2. Reduced Carbon Footprint: By eliminating radiology films, the project reduces the carbon footprint associated with film production, transportation, and disposal. This reduction in healthcare-related environmental impact aligns with global efforts to combat climate change.
  3. Improved Health: Embracing eco-friendly solutions in healthcare holds immense promise for improving public health on a global scale. By reducing our reliance on fossil fuels and transitioning to cleaner, renewable energy sources, we can significantly reduce air pollution, resulting in fewer cases of respiratory diseases, cardiovascular problems, and even premature deaths.
  4. Decrease in Plastic Waste: The project anticipates a noteworthy environmental achievement, aiming to reduce plastic waste by approximately 300 million tons (UN Foundation Report 2023). This ambitious goal signifies a significant stride in curbing the detrimental impact of plastic pollution on our ecosystems.
  5. Reduction in Waste Management Costs: A key economic advantage of the project lies in its potential to bring about a substantial reduction in waste management costs, estimated at approximately $1.3 trillion (World Wildlife Fund, 2023). This financial efficiency not only promotes sustainable practices but also addresses the economic burden associated with waste management on a global scale.

Figure 4: Impact of RadioView.AI app implementation on environment preservation

NeuroICH Application

Organization has also developed NeuroICH application which is another way to reducing the use of radiological films and keeping the environment greener.

NeuroICH is an advanced AI model that can provide brain scan images at par with the gold standard CT scan machines used by the radiologists in hospitals. It is designed to accurately identify bleeding in brain, making it particularly useful in diagnosing this critical conditions. With this cutting-edge technology, healthcare providers can obtain precise brain scans to facilitate prompt diagnoses and targeted treatments, improving patient outcomes and saving lives.

We have trained our AI model on open datasets and were able to achieve overall accuracy of 98% for detection of ICH with no accuracy less than 97% for individual ICH types. The sensitivity and specificity of the NeuroICH model is 97.5% and 97.4% respectively.

References

Aalto-Korte, K.; Suuronen, K. Plastic materials and glues. Contact Dermat. 2019, 2019, 1–28.

Adeniran, A. A., & Shakantu, W. (2022). The health and environmental impact of plastic waste disposal in South African Townships: A review. International Journal of Environmental Research and Public Health, 19(2), 779.

Castiglioni, I., Rundo, L., Codari, M., Di Leo, G., Salvatore, C., Interlenghi, M., … & Sardanelli, F. (2021). AI applications to medical images: From machine learning to deep learning. Physica Medica, 83, 9-24.

Cohen, S. (2017). The Human and Financial Cost of Pollution. https://news.climate.columbia.edu/2017/10/23/the-human-and-financial-cost-of-pollution/ (Accessed on September 19, 2023).

Fleck, A. (2022) Recycling Efforts Not Enough to Solve Plastic Waste Problem. https://www.statista.com/chart/27756/global-waste-management-projections/ (Accessed on September 19, 2023).

Gore, J. C. (2020). Artificial intelligence in medical imaging. Magnetic resonance imaging, 68, A1-A4.

Hilal, N., Tawfik, T. A., Ahmed, S. N., & Hamah Sor, N. (2022). The effect of waste medical radiology as fiber reinforcement on the behavior of eco-efficient self-compacting concrete. Environmental Science and Pollution Research, 29(32), 49253-49266.

Organization for Economic Co-operation and Development (OCED), 2019. https://www.oecd-ilibrary.org/sites/aa1edf33-en/1/3/1/index.html?itemId=/content/publication/aa1edf33-en&_csp_=ca738cf5d4f327be3b6fec4af9ce5d12&itemIGO=oecd&itemContentType=book#section-d1e841 (Accessed on September 19, 2023).

The Lancet Commission on Pollution and Health, Global Alliance for Health and Pollution, 2015. http://gahp.net/the-lancet-report-2/ (Accessed on September 19, 2023).

Thrall, J. H., Brink, J. A., & Zalis, M. E. (2023). The ESG (Environmental, Social, Governance) Movement and Radiology: Opportunities and Strategy. Journal of the American College of Radiology.

Veitch, A. (2021). Uniting the global gastroenterology community to meet the challenge of climate change and nonrecyclable waste.

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