RADIOLOGY
Breast cancer: The use of teleradiology and artificial intelligence Dr Arjun Kalyanpur, Chief Radiologist & CEO, Teleradiology Solutions highlights the role of teleradiology and artificial intelligence in early detection of breast cancer which is the leading cause of death among women in India Consider the following disturbing statistics about breast cancer in India 1. Breast cancer is the most common cancer among Indian women, with one woman being diagnosed with it every 4 minutes. 2. Breast cancer is on the rise in India. A 2018 report of Breast Cancer statistics stated that there were 1,62,468 new registered cases (and 87,090 reported deaths). 3. India has the highest mortality rates globally for breast cancer; 50-60 per cent of Indian women diagnosed with breast cancer die within a year of diagnosis. 4. More than 50 per cent of Indian women with breast cancer are in stage 3 or 4 of the disease. 5. Cancer survival becomes more difficult in the later stages of its growth. Late detection reduces survival by 3 to 17 times. Currently there are no measures for the prevention of breast cancer (the only somewhat radical exception being prophylactic mastectomy for women who are genetically at high risk of developing breast cancer). For this reason, early detection remains the primary focus in the fight against breast cancer as a delay in detection is linked to lower survival rates. The goal of early detection is to diagnose breast cancer patients at an early stage of disease before it has progressed/spread and when the prognosis for long-term survival is best. Furthermore, that allows for less invasive treatment including breast conservation procedures that permit better quality of life
What are the methods for
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March 2022
early detection of breast cancer? Traditionally the method has been breast self-examination or by a doctor at an annual medical check-up. The problem with this approach lies in the fact that breast examination only diagnoses tumors that have grown to a size where they are palpable (can be felt) which means they are already of a substantial size. Which brings us to mammography. Mammography is an imaging technique which is currently the procedure of choice worldwide for screening for breast cancer. It uses a lowdose of radiation (slightly more than a regular chest X-ray), which is considered safe and acceptable, without posing additional radiation risk. Two images of each breast are created under compression (a newer technology called tomosynthesis produces a larger number of images). Breast compression helps avoid movement that can blur the image as well as reduces the degree of overlap, thereby producing an image of greater clarity. DCIS or ductal carcinoma in situ is a precursor to invasive breast cancer where it is still contained within the duct in which it originated. At this early stage the cancer has not infiltrated the parenchyma of the breast and the lymphatics and cannot therefore metastasise. Mammography is capable of detecting DCIS with greater than 80 per cent accuracy. However, for mammography to make significant impact at a public health level, the need is for it to be conducted as a large-scale program. The challenges with running such a program include a) providing access to mammographic technology to women everywhere,
which is an issue in India b) the need for expert radiologists to analyse the images, given that misinterpretation can result in missing the diagnosis of cancer. Currently there is a shortage of radiologists worldwide, which varies by region. For example, based on WHO data, 14 countries in Sub- Saharan Africa have no radiologist expertise. In India, there are approximately 20,000 radiologists for our massive population of 1.2 billion, which is a grossly skewed ratio for the requirement. Conducting a screening program at scale is clearly impacted by such a significant constraint. The use of teleradiology is one method of ensuring that a mammography screening program can be effectively supported by accurate radiologic diagnosis. Teleradiology is the means by which images are transmitted from the point of acquisition to the location of the specialist radiologist for interpretation. In a radiologistshortage environment, small towns and villages are hardpressed to obtain radiologist expertise, and teleradiology
bridges the gap. Our teleradiology experience with the Poornasudha cancer foundation demonstrated the value of this collaboration. The foundation sends a mobile mammography unit (bus) to remote villages to conduct mammography screening at site for village women. Once enabled with teleradiology capability, the program could be supported by our Bangalore-based radiologists with expertise in mammography, allowing rural women access to the highest level of mammography diagnosis available. But even teleradiology is only a temporising measure. Given that the radiologist shortage shows no sign of abating in the near future, the role of Artificial Intelligence as a support for radiologists is becoming of increasing importance. The mammographic findings that are characteristic of malignancy including clustered micro calcifications, asymmetric densities, architectural distortion and masses. These findings are subtle and can be time-consuming for the radiologist to detect.
AI has been found to provide several significant benefits in the setting of mammography a) Accuracy: From an accuracy standpoint AI appears to be outperforming or at the very least equaling the skills of radiologists. A 2020 article published in Nature reported that in an independent study of six radiologists, the AI system outperformed all of the human readers. b) Workload reduction: A 2021 study from Spain reports that digital mammography screening strategies based on artificial intelligence systems
could reduce workload up to 70 per cent. c) Speed of review and triage: While it may take a radiologist a considerable amount of time to carefully review an entire mammogram, the AI algorithm performs its digital review instantaneously. This permits a process of triage wherein normal studies can be segregated from abnormals that need additional workup. d) Localisation and grading: Apart from detecting the cancer, contemporary algorithms also provide its location within the breast. An algorithm developed by our AI group, titled MammoAssist can also estimate the BIRADS score (a probability indicator of a mammogram being positive for cancer) which is currently the standard of care in mammography reporting. e) Comparison with priors: Given that screening mammography is performed annually, comparison with priors is an important, though time consuming facet of mammography reporting. Using deep learning techniques, the process of comparing with the prior examination can also be performed by an AI algorithm, thereby also assisting in more efficient and rapid diagnosis. Breast cancer is today a leading cause of death among women in India. To combat this disease and provide women with a fighting chance of survival early diagnosis is all important. To this end, teleradiology and artificial intelligence both provide technology-based solutions that can transform the outcome of patients with this now eminently treatable disease, raising hope for a dramatic change in its overall impact on the health and wellbeing of women.
