Monthly Archives January 2021

Breast cancer is known to be the leading cause of cancer-related deaths in women globally, and compared to countries in the Middle East, Qatar has one of the highest cancer incidence and death rates. highest breasts.

Regular screening and early detection is crucial, with the American Cancer Society saying that when breast cancer is caught early and is in the localized stage, the five-year relative survival rate is 99%.

There are many breast diagnostic approaches, such as mammography, magnetic resonance imaging (MRI), ultrasound, among others, and the use of artificial intelligence (AI) in these diagnostic technologies becomes more and more popular.

Mammography is the most widely used breast cancer screening tool, but diagnosing cancer from these images is a challenge. One in five breast cancer cases are ignored by radiologists, and according to the American Cancer Society, 50 percent of all women who are screened over a 10-year period will experience a false positive, in which cancer is suspected. wrongly.

A false positive can lead to overtreatment with invasive biopsies and unnecessary stress for patients. A false negative can cause delay in detection and processing.

As digital mammography is used as the standard method for early detection of breast cancer and seems to have limitations, AI comes to the rescue. AI models are developed and used to predict breast cancer in mammograms more accurately than radiologists, thereby reducing false positives and false negatives.

“When you use the naked eye to define abnormalities in image data or when analyzing tissue, you can get the analysis wrong. However, with artificial intelligence, the classification of abnormal or normal tissue is more precise, ”said recently Halima Bensmail, senior scientist and associate professor at the Qatar Computing Research Institute, which is part of Hamad Bin Khalifa University in Qatar. Foundation (QF).

“Due to the large variation in data from patient to patient, traditional learning methods are unreliable and machine learning has evolved in recent years due to its ability to sift through data complex and large in order to be able to detect anomalies, ”she added.

In the field of digital imaging, the quality of mammography images from Qatar is considered adequate, according to a study entitled Breast Cancer Detection in Qatar: Evaluation of Mammography Image Quality Using A Standardized Assessment Tool, funded by the Qatar National Research Fund of QF . But the study also notes that as the country develops additional capacity and awareness for mammography screening, it will be important to continuously monitor image quality.

“People will always wonder how accurate your prediction is, or what is most important when designing a machine learning model: the performance of the model or the accuracy of the model. This answer depends on the application and the domain. But so far we don’t have a machine learning algorithm or artificial intelligence model that gives us 100 percent accuracy of the prediction, ”says Dr Bensmail.

So how does AI work to detect breast cancer or any other type of cancer?

Much of AI relies on machine learning. In machine learning, scientists train the system to learn something very specific, like bad breast tissue versus good breast tissue through pictures.

By training the system with massive amounts of data, it learns to differentiate bad tissue from good tissue. Over time, the algorithm learns to predict with great precision.

According to Dr Bensmail, AI algorithms such as deep learning and neural network-based algorithm provide extremely good results in detecting breast cancer – they provide 90-97% accuracy of the data image, as in mammograms. However, when enough data is not available, machine learning or AI models cannot be built effectively – and this is a challenge in the region.

“In the Arab world, breast cancer is the most frequently diagnosed cancer overall, accounting for around 17.7-19% of all new cancers in 2018, but there is some stigma among Arab women for a breast cancer screening. You really have to motivate and encourage them, which is not always easy. And people are also concerned about data privacy, ”she said.

With AI advancing rapidly, Dr Bensmail predicts that within the next 10 years or so, AI will become even more common in clinical practice. She says disease prediction, especially the classification of breast cancer in the radiology department, is something that happens quickly, especially in the area of ​​image data analysis.

“There are many institutes and groups of researchers who are working on processing image data in a precise way,” she added.

Seno’s Imagio® Breast Imaging System helps physicians differentiate benign and malignant breast lesions using a new combination of ultrasound and optoacoustic technology.

Seno Medical’s Imagio® Breast Imaging System uses non-invasive optoacoustic ultrasound (OA / US) technology to provide real-time information about suspicious breast lesions, helping providers characterize and differentiate masses that may or may not require a more invasive diagnostic evaluation.

San Antonio, TX, January 19, 2021 (GLOBE NEWSWIRE) – The Center for Devices and Radiological Health (CDRH) of the United States Food & Drug Administration (FDA) has granted Texas Séno Medical Instruments, Inc. (Seno) pre-market approval (PMA) for its revolutionary breast cancer diagnostic imaging technology which helps doctors better differentiate benign and malignant breast lesions. The company’s imagio^® The breast imaging system uses non-invasive opto-acoustic ultrasound (OA / US) technology to provide information about suspicious breast lesions in real time, helping providers characterize and differentiate masses that may or may not. require a more invasive diagnostic evaluation.

Breast biopsy procedures caused by false positive diagnostic evaluations in the United States cost the health care system more than $ 2 billion annually.^I Imagio de Seno^® Technology could mitigate this by providing providers with additional real-time information on suspicious breast masses and increased confidence to make a better decision about the need for diagnostic breast biopsies.

The company’s OA / US technology combines laser optics and grayscale ultrasound to provide fused functional and anatomical breast imaging. Optoacoustic images provide a unique blood map in and around breast masses, while ultrasound provides a traditional anatomical image. By the appearance or absence of two characteristic indicators of cancer – angiogenesis and deoxygenation – Seno Medical has shown that Imagio^® The OA / US Breast Imaging System will be a more effective tool in helping radiologists confirm or rule out malignancy compared to traditional diagnostic imaging modalities – without exposing patients to ionizing radiation (x-rays) or radiation. potentially harmful contrast agents. In addition to the new imagery provided by the Imagio system, Seno includes an AI physician decision support tool (the SenoGram^®) to help interpret the new images that, along with training and certification, help radiologists make the transition from ultrasound alone to OA / US imaging.

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The system is indicated for use by trained and qualified healthcare providers to assess palpable and non-palpable breast abnormalities in adult patients who are referred for diagnostic imaging breast exam following clinical presentation or breast cancer. ” other imaging tests such as a screening mammogram.

Seno CEO Tom Umbel commented, “We are delighted to have reached this milestone and look forward to advancing our technology platform in the United States with this FDA approval. Our internal team and our loyal investigators and clinical trial sites have worked diligently to bring Imagio^® to market and improve care for patients and providers with the precise diagnostic capabilities and enhanced decision support that our new OA / US imaging provides.

Seno Chief Medical Officer A. Thomas Stavros, MD, FACR, FSBI, believes that Imagio^® sets a better standard for how diagnostic modalities are to be judged. “Optimizing the diagnosis of breast masses requires a combination of very high sensitivity (≥ 98%) while simultaneously maximizing specificity and minimizing false positives and biopsies of benign masses. Other modalities have reported improvements in specificity, but these often occurred at the expense of the desired high sensitivity ≥ 98%. Data from the PMA study show that OA / US was successful in improving specificity at a fixed sensitivity of 98%, the part of the ROC curve where clinical decisions about whether or not to biopsy a mass are actually made. . “

Seno Medical Instruments, Inc. is a San Antonio, Texas-based medical imaging company engaged in the development and commercialization of a novel cancer diagnostic modality: optoacoustic imaging. Imagio by Seno Medical^® The breast imaging system merges opto-acoustic technology with ultrasound (OA / US) to generate functional and anatomical images of the breast in real time. To learn more about Seno Medical’s OA / US imaging technology and applications, visit www.SenoMedical.com.

^I Vlahiotis A, Griffin B, Stavros AT, Margolis J. Analysis of use patterns and associated costs of breast imaging and diagnostic procedures after screening mammography. ClinicoEconomics and Outcomes Research 2018: 10 157-167.

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CONTACT: Tom Umbel Seno Medical (210) 714-1912 [email protected]