Category: In Focus

Categories
In Focus

From Surviving to Thriving: The Journey of a Childhood TB Survivor Turned Doctor

Introduction

On the eve of World Tuberculosis (TB) Day, I, Dr. Shibu Vijayan, want to share my story with you. A story of hope, resilience, and determination that has shaped my life and inspired me to dedicate my career to the fight against TB. As a childhood TB survivor, public health specialist, and now Medical Director at Qure.ai, my journey has taken me from the depths of illness to the forefront of digital and AI advances in TB control.

The Battle Begins

When I was 12 years old, my world was turned upside down. What started as hip pain, mild fever, and fatigue quickly escalated into a battle for my life with a disabled leg. I was diagnosed with tuberculosis, a disease that would keep me bedridden for six long months.

My world revolved around a bed, and the only view of the external world was through the window, with occasional parrots coming to eat the fruits from the creepers.

During this time, I endured 18 months of TB treatment, which included three months of painful injections and the constant struggle of nausea and vomiting. My adolescence was very restrictive, getting many disapprovals for playing out and participating in sports. My request to play games was repeatedly turned down, and I was reminded that I was a sick boy. But through it all, I never lost hope.

Finding Purpose in the Fight

My experience with TB became the catalyst for my future career. I resolved that once I recovered, I would become a doctor and dedicate myself to TB control. I wanted to ensure that no other child would have to go through what I did. So, true to my word, I went on to become the district TB officer and served as a doctor in the very same facility where I received my treatment.

District TB Office, Kollam

Embracing Digital and AI Advances

Now, as the Medical Director at Qure.ai, I have the opportunity to integrate cutting-edge digital and AI technology into the battle against TB. AI-powered tools for advanced diagnostic imaging and data analysis are revolutionizing how we detect and treat TB. By implementing these innovative solutions, we can reduce the time it takes to diagnose TB and improve the accuracy of detection. Not only does it save lives, but it also minimizes the suffering that comes with delayed diagnosis and treatment.

The Urgency of Early Diagnosis

In my 25 years of working in TB elimination, I have come to understand the critical importance of early diagnosis. Catching TB at its earliest stages increases the likelihood of successful treatment and helps prevent the spread of thedisease to others. Early diagnosis and intervention are essential in our mission to end the global TB epidemic.

District TB Office, Kollam

A Call to Action

As we observe World TB Day on March 24th, let us remember the millions of lives impacted by this devastating disease. My story is just one of many, and it is a testament to the resilience of the human spirit in the face of adversity. Together, we can harness the power of digital and AI advances to bring us closer to a world free of TB. Let us all commit to joining the fight against TB and ensuring that everyone, everywhere, has access to early diagnosis and life-saving treatment.

Conclusion

From surviving to thriving, my journey as a childhood TB survivor turned doctor is a testament to the power of hope and determination. As we continue to make strides in TB control and elimination, I remain dedicated to this cause, ensuring that future generations will not have to endure the pain and suffering I experienced.

So, this World TB Day, let us stand together and reaffirm our commitment to end TB once and for all.

Categories
In Focus Uncategorized

Burning Issue: Why Opportunistic Screening for Lung Cancer is the need of the hour

'Cancer Cures Smoking'

Did the above line make you look twice and think thrice? Years ago, the Cancer Patients Aid Association published this thought-provoking message, a genuinely fresh view on the relationship between tobacco and cancer. And why not?

Extensive research from across the world indicates that cigarette smoking can explain almost 90% of lung cancer risk in men and 70 to 80% in women. The WHO lists tobacco use as the first risk factor for cancer. The World Cancer Research Fund International goes a step further and plainly calls out smoking. With lung cancer racking up 2.21 million cases in 2021 and 1.8 million deaths, one can understand why healthcare stakeholders want to focus efforts on targeting common causes and reducing incidents of the disease.

Yet, a recent study indicates troubling trends.

Medanta Hospital is one of India’s leading medical facilities. Their research on lung cancer prevalence, conducted over a decade between 2012 – 2022 amongst 304 patients threw up a startling statistic – 50% of their lung cancer patient cohort were non-smokers. According to the doctors who conducted the research, Dr Arvind Kumar, Dr. Belal Bin Asaf and Dr. Harsh Puri, this was a sharp rise from earlier figures for non-smoking lung cancer patients (10-20%). But, there’s more.

The study indicates that, be it smokers or non-smokers, the risk group for lung cancer has expanded to a relatively more youthful population.

The WHO previously flagged a key factor for the rising trend in young, non-smokers being at risk for lung diseases – air pollution. Dr. Tedros Adhanom Ghebreyesus called air pollution a ‘silent public health emergency’ and ‘the new tobacco’. It presents clinicians working to treat and prevent lung cancer with a new conundrum – evaluating risk factors for the disease.

Simply put, how does one tackle the risk of lung cancer in a 25-year-old, non-smoking individual living a reasonably healthy lifestyle when a risk factor could be the simple act of breathing?

According to Dr. Matthew Lungren, the answer could be Opportunistic Screening – which he calls, “… the BEST use case for AI in radiology”

Qure.ai concurs. qXR, our artificial intelligence (AI) solution for chest X-rays, has been tried, tested and trusted to assist in identifying and reporting missing nodules, which highlights the importance of opportunistic screening for identifying potential lung cancers early.

All our recent studies, including the one with Massachusetts General Hospital (MGH) in a retrospective multi-center study, investigated and concluded that Qure’s CE approved qXR could identify critical findings on Chest X-Rays, including malignant nodules.  This spurs the possibility that opportunistic screening for indicators of lung cancer and other pulmonary diseases should become the norm.

Qure.ai’s solutions, can truly make the difference, augmenting the efforts of clinicians and radiologists any and every time a Chest X-ray or Chest CT is conducted.

November is Lung Cancer Awareness Month. What better moment than the last day of the month to urge everyone to think outside the box when it comes to demographics, risk factors, screening, and the role of AI in healthcare.

Categories
In Focus Uncategorized

Need for Speed: AI, AstraZeneca, and early lung cancer diagnosis

The AstraZeneca-Qure partnership

A thousand miles begins with a single step. In 2020, Qure.ai and AstraZeneca took the first step together to integrate advanced artificial intelligence (AI) solutions to identify lung diseases early in patients across AstraZeneca’s Emerging Markets region – Latin America, Asia, Africa, and the Middle East. In the past 2 years, the partnership has made significant progress, incorporating the use of AI technology with chest X-rays for multi-disease screening, including tuberculosis and heart failure along with lung cancer.

Lung Cancer: The need for early detection

In more than 40% of people suffering from Lung Cancer, it is detected at Stage 4, when their likelihood of surviving 5 years is under 10%. Only 20% are diagnosed at Stage 1 when the survival rate is between 68-92%. That’s why Lung Cancer is responsible for every 1 in 5 cancer deaths worldwide.

Though early detection facilitates early diagnosis and better patient outcomes, the disease’s silent progress to advanced stages makes it a challenge like none other. Low Dose CT (LDCT) remains the most effective means of screening for Lung Cancer. However, in LMICs, CTs can be prohibitively expensive, priced between USD 500 – 700, limiting their access. However, there is some hope.

Chest X-rays are one the most routinely performed exams in the world, representing 40% of the approximately 3.6 billion imaging tests that are performed annually. As a non-invasive diagnostic test with easy access and low costs, the chest X-ray is a valuable first line test to screen for radiological indications of issues in the lungs, heart, ribs, and more. Acquiring chest X-ray scans only takes minutes; but it warrants expert radiologists to read and analyze them.

Augmenting X-rays with the power AI

qXR, Qure.ai's AI-powered chest X-ray interpretation tool, can automatically detect and localize up to 30 abnormalities, including indicators of Lung Cancer, TB, and COVID-19. This is particularly impactful when millions of scans are examined using qXR to report any abnormalities that could otherwise be missed due to:

  • Lack of experienced personnel
  • Increased workloads, limiting access and time for detailed reads of abnormal scans
  • Incidental nodules indicative for Lung Cancer being missed because physicians are only looking at the results for which the X-rays were ordered and not incidental findings.

How Qure is making a difference

1. Working with grassroot level healthcare professionals

A. Leveraging Primary Care GP clinics in Malaysia

Qualitas Medical Group (QMG) is a chain of integrated general practice (GP) clinics, dental clinics, medical imaging centers, and ambulatory care management centers that play an integral role in Malaysia’s health system. Along with Lung Cancer Network Malaysia, QMG uses qXR to triage all chest X-rays taken of local workers, identifying incidental lung nodules that maybe indicative of lung cancer for further testing. qXR has also helped GPs to reduce their dependency on radiologists for second reads and reduced reporting turnaround time for chest X-rays from 2 days to the same day.

“Qure.ai’s state of the art deep learning technology is a potential game changer that will enhance and expedite diagnosis with rapid referral to relevant specialty “, said Dr Anand Sachithanandan, President, Lung Cancer Network Malaysia

B. Empowering Primary Care Physicians in Latin America

Primary care centers are the first medical care touchpoint and are crucial stakeholders for early diagnosis in disease care pathways. In collaboration with Lung Ambition Alliance, Latin America, Qure is empowering primary care physicians in 12 different countries with AI-enabled smart phone-based chest X-ray analysis and lung nodule screening.

In the absence of digital X-rays, physicians only need to click a picture of the X-ray film against a lightbox and upload it on the app to receive instant qXR analysis. Based on the results, they can guide the patient to the next appropriate steps.

2. Collaborating with Cancer Care Foundations

Assam is called India’s Cancer Capital as the state’s average cancer incident rate is double the national average. The high cancer burden, low public awareness, and a lack of specialised health-care infrastructure led the Govt. of Assam to partner with Tata Trusts and build the Assam Cancer Care Foundation (ACCF).

Potential lung cancer suspects are identified via door-to-door screenings as well as via a screening kiosk set up at the Fakhruddin Ali Ahmed Medical College and Hospital, Barpeta where ACCF have built a specialised cancer care unit. Chest X-rays of these individuals will be screened for detection of suspicious lung nodule(s) using qXR. Based on the result, they will either be called back for an LDCT/Biopsy or an oncology consultation.

3. Surveillance of all chest X-rays taken in a tertiary care hospital

The VPS Lakeshore, Kerala is a tertiary care hospital and a centre of excellence in Oncology and other specialities. It is well equipped to take up largescale screening programs and facilitate the required care continuum for high risk, suspected and confirmed disease cases. The hospital has a program in place where a tool surveys all chest X-rays taken to facilitate early detection of Lung Cancer.

Through our partnership with AstraZeneca, we have deployed qXR to scan all chest X-rays performed at the hospital to pick up possibly early cases of Lung Cancer. If any abnormal/nodule indicative cases are picked up by the software, it is instantly flagged to the radiologist/referring physician so that they can guide the patient along the next steps in the patient care pathway.

4. Public screening road shows

The Ministry Of Public Health, Thailand along with the AstraZeneca team initiated the “Don’t Wait. Get Checked” Lung Cancer Campaign in April ’22 at Central World Mall, in partnership with Banphaeo General Hospital, Digital Economy Promotion Agency (DEPA) and the Central Group. On the occasion of World No Tobacco Day, Qure.ai’s qXR was used to screen close to 200 people. The objective of this program was to directly impact Thailand's public health policies revolving around lung cancer.

Way Forward

“Building health systems that are resilient and sustainable will require finding new ways to prevent disease, diagnose patients earlier, and treat them more effectively. The benefits of the technology that Qure.ai offers align well with our corporate values, ultimately supporting our strategic objective to reshape healthcare delivery, close the cancer care gap and better chronic disease management, especially in low-to-middle income countries. We believe that innovative technology has the potential to transform patients’ outcomes, enabling more people to access care in timely, reliable and affordable ways, regardless of where they live”, said Pei-Chieh Fong, Medical VP, AstraZeneca International.

At the Davos World Economic Forum 2022, AstraZeneca pledged to join the WEF EDISON Alliance and committed to screening 5 million patients for lung cancer by 2025 in partnership with Qure.ai.

With the support of AstraZeneca Turkey, Qure.ai collaborated with Mersin University Hospital on a landmark study for the use of AI in Heart Failure detection, using our qXR suite. This study is an important indicator for the future of AI in healthcare and the use of technology to augment the efforts of physicians in the early detection of other diseases.

Categories
In Focus Uncategorized

Qure’s AI for detecting risk of heart failure

Every year, approximately 17.9 million lives are lost to cardiovascular diseases (CVD), the leading cause of death across the world. The rates of heart failure misdiagnosis range from 16.1% in hospitals to 68.5% in GP referral settings. In the EU alone, the economic burden of cardiovascular diseases exceeds €210 Bn.

A systematic analysis on 10 studies done across 5 countries found patients groups with comorbidities and COPD, and the elderly population in nursing homes were more likely to have unrecognized heart failure.

Turkey is known to have a higher prevalence of heart failure and Atrioventricular Septal Defect (AVSD) as compared to the western world. With millions of chest radiographs done annually for a host of reasons, a tool that could screen the data used in these studies to predict the early signs for risk of heart failure could be ground-breaking for care and patient outcomes.

Output generated by Chest X-ray AI Solution

Enlargement of heart in cases of heart failure

At the start of 2021, the Department of Cardiology at the Mersin University Faculty of Medicine initiated a study under Digital Transformation with Artificial Intelligence in Health with support from AstraZeneca Turkey to use Qure’s AI solutions to understand the role of AI in predicting heart failures early from incidental findings on Chest X-rays. Only patients who were previously not suspected or identified for signs of heart failure were included in the study.

Post risk assessment using the AI tool on chest radiographs, the department approached at-risk patients for follow-up tests. A larger number of patients were identified as at-risk but since this study was conducted during the pandemic restrictions, not all individuals came back to the hospital for follow-up. Of the high risk patients who came for follow up tests, 86% were identified to be confirmed heart failure patients. These individuals had confirmatory diagnoses with tests such as NT-proBNP and Echocardiography.

The results of this year-long exercise have the potential to change the use of AI in cardiology altogether.

Prof. Dr. Ahmet Çelik, President at Heart Failure Working Group of Turkish Society of Cardiology and the Principal Investigator in this research said,

“In this study, which was carried out for the early diagnosis of heart failure, the power of artificial intelligence to predict heart failure by looking at lung X-rays was realized with a sensitivity of 89.1 percent and a selectivity of 86.4 percent. More importantly 65.3 percent of patients diagnosed with heart failure had Preserved Ejection Fraction Heart Failure which is difficult to diagnose.”

 Qure’s AI solution has been found to have 95%+ sensitivity for both cardiomegaly and pleural effusion. It could potentially be a game-changer as a silent reader, without increasing the work burden on healthcare professionals or adding significant costs by changing care pathways. It could screen all chest radiographs done worldwide on non-suspecting cases adding thousands of undiagnosed cases onto the cardiology risk assessment, diagnosis, and eventually treatment pathway. With a well-thought-through system for detection and diagnosis, this technology could mean more lives saved with minimal additional investment.

AstraZeneca Middle East and Africa Region Medical Director Dr. Viraj Rajadhyaksha stated,

“By applying advanced artificial intelligence and machine learning approaches to patients who go to different units for many reasons, this project will enable them to touch the lives of patients who are diagnosed early and to meet the right treatments much earlier. The results of the research have the potential to create an early detection tool for heart failure for the first time in the world.”

AstraZeneca team aims to expand the project nationally and apply it to every lung x-ray taken. There has been research exploring the possibility of using AI for X-ray-based cardiac failure detection in a study setting. However, the potential impact on patients has not been demonstrated at such a scale before. This opens a world of opportunities for further focussed research evaluations to ascertain protocols of bringing in clinical practice.

Prof. Dr. Ahmet Çamsari, the Rector of Mersin University is a strong believer in the potential of AI to impact the diagnostic pathway for patients. He said,

“Our project will be one of the first projects where artificial intelligence is used in the early diagnosis of undiagnosed and suspected heart failure patients in our country and even in the world. In line with the results obtained, we aim to expand the project nationally and apply it to every lung x-ray taken. Again, we hope that these systems can be used in other fields such as radiological oncology and that artificial intelligence projects that touch the lives of patients can be implemented.”

Categories
In Focus Uncategorized

Aarthi Scans: Scripting tele-radiology growth in India

The rapidly increasing need for radiology diagnostic and image interpretation services around the world has brought two major issues to light. The first is the lack of radiologists and the other is the dearth of specialized knowledge.

Building reliable communication and image transfer systems to tap into the expertise of radiologists who are not on-site can solve these issues to some extent. Hospitals, mobile imaging firms, urgent care clinics, and even some private practices all around the world are increasingly using tele-radiology. Tele-radiology improves patient care by allowing radiologists to provide services without having to be physically present at the imaging site so that the patients can receive round-the-clock access to trained specialists.

Tele-radiology is significantly less expensive than having a radiologist on-site. These services are typically priced per exam, with the cost as low as $1 per X-ray Tele-radiology has transformed the practice of many radiology clinics around the world, allowing them to provide results faster and by facilitating access to the radiologist, adding enormous value to the diagnostic process.

To set up a tele-radiology system between two centres, one requiring radiologist’s services and one providing radiologist’s services, the following elements are needed:

  1. Modality – a system that captures the medical image and has the facility to send these images in the preferred format i.e., DICOM
  2. PACS – a system that stores, sends, and receives medical images (DICOMs) and that can be identifiable by a unique address (like IP address, port number, etc.)
  3. Gateway – a medium that handles communication between the two centers (source and the destination) – receives the medical images from the source and sends back the output in the required format) using API calls. Complying with the data security and Protected Health Information (PHI) standards, de-identification and re-identification of confidential information can be performed by the Gateway.
  4. API Hub – a single place where all the Application Programming Interfaces (APIs) can be published and shared with external parties/clients by the intended service provider (tele-radiology) com

Introducing Aarthi Scans: India’s largest Tele-radiology service provider

India with its population of around 1.44 billion, right now we have around 1 radiologist for 100,000 people. Most rural India still lacks adequate radiological services and personnel, and not all imaging centers have subspecialty expertise, tele-radiology plays a significant role in quality diagnostics.

Aarthi Scans and Labs, one of the largest diagnostic centers were started in the year 2000 by Mr. Govindarajan. Today Aarthi Scans has more than 100+ branches across 10 states.It was in 2011 that they started their tele-radiology services to provide quick reporting for emergency cases and nighttime reporting and to ensure continuous reporting even when radiologists go on leave. Their radiologists' review over 200,000 CTs, 250,000 MRIs, and 2.1 million chest X-rays annually.

“At that point of time in 2011, when we started tele-radiology, telemedicine as a concept had not evolved in India. Radiologists giving reports without being present at the scanning location was viewed with skepticism. But once the referring doctors started viewing the benefits of tele-radiology, like nighttime reports, subspecialty reporting, they were impressed. Radiologists also needed a lot of convincing to report tele-radiology images. We standardised and digitised patient history, records, improved communication channels between tele-radiologists and radiographer in scanning sites and there was a slow and steady adoption by the Radiologist community. Our PACS vendor – Mr Ravindran from Innowave Healthcare Technologies helped us a great deal in solving the workflow related issues and helping us choose the right technology for us.”

–  Govindarajan, Aarthi Scans and Labs

Aarthi Scans has taken a step forward by incorporating Artificial Intelligence (AI) into their reporting procedure, demonstrating their commitment to staying on the cutting edge of technology. The ratio of one radiologist to more than 100,000 people in India has resulted from stress in radiology reporting, scan misreads and reporting delays. Any solution that might assist radiologists to relax and improve their productivity is always welcome at the technologically advanced setup at Aarthi Scans, and AI can be of immense value add in this scenario.

Qure.ai's qXR, a Chest X-ray interpretation software – a CE Class II certified product – has been installed in Aarthi Scans diagnostic centers. The most common application of qXR in this setting is for Radiologist assistance to triage any scans with abnormalities on the worklist. The images are scanned and interpreted in under a minute. All scans that qXR identifies some findings in, are saved as a draft in the radiology worklist for further assessment and reporting. The report is generated in a natural language, significantly reducing the typing time that constitutes a significant portion of the reporting time. The final report is released in 30% lesser time due to this triaging mechanism and reading assistance by qXR.

Qure.ai is a leading solution provider and we validated a few solutions before choose Qure.ai.  We chose qXR because the accuracy in categorising a study as normal or abnormal is very high (95%)!”.  “We have been using qXRin our day-to-day radiological practice across India in all our branches. We are huge fans of qXR's accuracy and utility.”

– Dr. Arunkumar Govindarajan, Director, Aarthi Scans and Labs

Technical Integration

Qure PACS gateway for acquiring the Chest X-rays is integrated with Freedom Nano PACS which is present in every center of Aarthi Scans. Each center is authenticated with a unique token for the transmission of the studies and their corresponding results. The end-to-end transmission is supported by API calls that communicate with the Qure API hub to send the studies to the qXR AI models for processing. The AI interpretations are sent back to Freedom Nano PACS, where the radiologist can view the result from the individual centers. API and back to Freedom Nano PACS, where the radiologist can view the result from the individual centers. API and https-based communication make the data secured even on the cloud.

Since partnering with Aarthi Scans four months ago, qXR has processed over 45,000 scans, triaging 55% of scans with abnormal findings. On a daily basis, qXR processes 200 chest X-rays.

Scans that are classified as normal by qXR can be evaluated by the radiologist more quickly, giving them more time to review the abnormal scans and cutting down on overall reporting time. This has led to a reduction in the TAT by 30%. The qXR Secondary Capture output also uses contours to localize anomalies in the lungs, enabling radiologists to recognize abnormalities more accurately, without spending as much time as a regular scan.

Finalising a Chest X-ray report as 'normal' is like passing through the valley of uncertainty for every Radiologist and qXR is like that friendly colleague who assists you with a second opinion / confirmation without bias. qXR saves our Radiologists' time and removes doubt while reporting.qXR has resulted in a 30% reduction in reporting time for our Radiologists.

– Dr. Aarthi, Director, Aarthi Scans and Labs

Insights into incorporating AI into the practice – Dr. Arunkumar Govindarajan

“Learning about basics of Artificial Intelligence (AI) has helped me a lot to understand the inner workings of AI and terminologies. To start and understand in deep about AI one can take Coursera courses like – “AI for Everyone" by Andrew Ng and “AI for Medical Diagnosis” by DeepLearningAI. There are a lot of AI solutions out there, one can research in google to find which will suit your patients' and radiologist's needs. Once you fix a good AI vendor –

  • do your own validation and provide transparent feedback
  • partner with a good IT & PACS vendor and fix a workflow suited to your organization's needs. AI integration into PACS takes a bit of effort from the AI and PACS vendor. Be present during the meetings to ease the process and quickly resolve doubts”

What's Next?

After successful operations with qXR in all our centers, we will be next deploying Qure’s AI solution, qER for detecting brain abnormalities from head CT scans.

“Time is Brain and quick qER report never goes in vain” Dr. Arunkumar Govindarajan, Director, Aarthi Scans and Labs