Featured Bio: Meet Marc Massaro — Marc is the Sr. Sales Director for AlgoMedica, the Silicon Valley- Based AI developer of PixelShine. In Diagnostic Imaging for 26 years he has worked in a variety of roles with modality vendors (NM, MR, PT, US) and for the last 13 years in Advanced Visualization, most recently ending an 8-year stint at TeraRecon to join AlgoMedica. Marc is from the Northeast, living for many years in CT with his wife and family.
Tell us about your area of focus and why you joined Algomedica: I’m fortunate to have had a well-rounded career thus far, with experience in the modality setting, advanced-visualization, enterprise viewing, and AI. The exposure to so many areas and layers of technologies has taught me a great deal about workflow, interoperability, and patient care in the context of the clinical and operational needs of the providers we serve in the Diagnostic Imaging community.
AI is a natural progression for me and I joined AlgoMedica based on the strength of the product, IP, leadership team and the opportunity to advance the state of the art in CT and associated technologies.
What is the mission of Algomedica? Stated simply, our mission is two-fold; Firstly, our algorithm is aimed at making patients safer and reducing wherever possible the cumulative effect of radiation dose. Secondly we are committed to increasing the diagnostic quality of every CT dataset that is acquired, whether the source scanner is a current flagship model or a 9 year old workhorse performing a heavy caseload.
What are some customer success stories and Radiologist testimonials? Our installed base of customers find success in many ways; whether it be increased detectability of findings, the efficiency gains associated with consistently better diagnostic quality or the impact of PixelShine on downstream workflows. Just in the past week we have had users discovering unexpected benefits of PIxelShine. For example, a high-volume cardiac imager in the Southeast has found that some IR datasets cause their automated EF workflow to fail due to the quality of the dataset. Processed with PixelShine, these cases are running well with accurate EF calculations.
“You nailed it when it comes to lung parenchyma! Higher dose reduction, better noise reduction, edges better defined, no artifacts.”
Dr. Sarabjeet Singh – Founder, CT Protocols LLC. Formerly Head – Radiation Dose Reduction Labs, Mass General Hospital
“PixelShine is the type of AI technology that clinicians should be leveraging to improve patient care and reduce radiation dose. PixelShine enables radiology to push the boundaries of technology to minimize radiation risk to our patients.”
Dr. Jose Morey, University of Virginia
“Machine learning tools like PixelShine have the potential to expand low dose CT beyond pediatrics and lung screening. PixelShine could make low dose imaging routine for all applications.”
Dr. Arun Krishnaraj, MD, MPH, Univ. of Virginia Health System
“PixelShine from AlgoMedica is a revolutionary tool in image processing and allows for substantially reduced radiation dose.”
Dr. Andrew Smith, MD, PhD, Chief of Body CT, Dept. of Radiology at UAB
Pixelshine processing of filtered back projection images creates higher quality studies, in a fraction of the time, than our CT scanner can produce with its most recent generation of iterative reconstruction. It is a monumental achievement. Dr. Michael Winkler, MD, MSCCT, FICA
“Fabulous, very impressive and I am looking forward to using it in my clinic”
Dr. Torben Kristensen MD, Director, Radiology Department, Palo Alto Medical Clinic
Can you talk more to the different uses your customers are finding for the algorithm? The exciting part is that we are finding new uses all the time. Beyond the routine application to CT datasets, we are finding benefits in how PixelShine works in combination with other AI, Advanced Visualization or even a 3D Printing workflow. For example, we are beginning a trial with PixelShine and a commercially available AI algorithm for Lung Nodule detection to assess the impact PixelSHine can have on nodule detection for consistency and accuracy especially for non-solid or semi-solid lesions.
Advanced Visualization workflows are becoming increasingly automated and with difficult datasets, those workflows can fail or produce results requiring time-consuming manual editing. This is an area with a great deal of potential for PixelShine.
What is the core competency and capability of PixelShine? PixelShine is an FDA-cleared algorithm for de-noising CT datasets, increasing diagnostic quality and detectability while supporting new CT protocols to drive patient dose down. PixelShine is important because of the machine’s ability to increase the conspicuity of those subtle pathologies which are borderline visible and could potentially be missed or take much longer for a radiologist to discover. The applications are wide and deep applying to CT without limit and apply to Filtered Back projection (FBP) and Iterative Reconstruction (IR). Some common use-cases are: LD and ULD Lung Screening, Cardiac Imaging (Dx and Structural Heart), Neurology, Low-contrast Abdominal Pediatric CT, Obese Patients, Virtual Colonography, MSK.
We have at hand an opportunity to truly transform and advance CT imaging, which is very exciting.
Do you have publications and papers available? We have a library of papers on the AlgoMedica website at https://algomedica.com/resources-page/publications/ and there are some more recent that are in the process of being uploaded.
So what’s next for AlgoMedica? We are busy working on the next PixelSHine release and of course supporting our installed base and research partners. Beyond that we have a roadmap to include AI for other modalities and are exploring adding workflow layers to PixelShine. We have our sights set on strategic partnerships as well, with a variety of healthcare enterprises and companies in our space where our efforts and technology are synergistic.