Surgeries that require the removal of lesions, such as cancer surgery, place a big burden on both patients and doctors. However, incorporating updated image recognition technology*1 makes it possible for doctors to identify areas of resection in less time and with high accuracy*2. This helps ease the time burden on doctors in preoperative simulations. Furthermore, if doctors can minimize the extent of resection*3, patients could also benefit because the after-effects of surgery will be reduced*4.
*1 The technology is cleared by the FDA. It is a supplement only and cannot make diagnoses or choose treatment on its own. Physicians are responsible for the use of this workstation and must confirm that organ regions are extracted correctly when using it for measurement.
*2 Xue-Yin Shen, Hee-Jung Wang, Bong-Wan Kim, Sung-Yeon Hong, Mi-Na Kim, Xu-Guang Hu Can we delineate preoperatively the right and ventral margins of caudate lobe of the liver? Ann Surg Treat Res. 2019 Sep;97(3):124-129. doi: 10.4174/astr.2019.97.3.124. Epub 2019 Aug 29. PMID: 31508392
*3 Shun-Ichi Ariizumi, Yutaka Takahashi, Yoshihito Kotera, Akiko Omori, Godai Yoneda, Han Mu, Satoshi Katagiri, Hiroto Egawa, Masakazu Yamamoto Novel virtual hepatectomy is useful for evaluation of the portal territory for anatomical sectionectomy, segmentectomy, and hemihepatectomy J Hepatobiliary Pancreat Sci. 2013 Mar;20(3):396-402. doi: 10.1007/s00534-012-0573-z. PMID: 23179558
*4 Kiyoshi Hasegawa, Norihiro Kokudo, Hiroshi Imamura, Yutaka Matsuyama, Taku Aoki, Masami Minagawa, Keiji Sano, Yasuhiko Sugawara, Tadatoshi Takayama, Masatoshi Makuuchi Prognostic impact of anatomic resection for hepatocellular carcinoma Ann Surg. 2005 Aug;242(2):252-9. doi: 10.1097/01.sla.0000171307.37401.db. PMID: 16041216
With an estimated shortage of 6.4 million doctors, planning for surgical procedures can be time-consuming and labor-intensive.
The world is facing a chronic shortage of doctors. According to the Institute for Health Metrics and Evaluation (IHME), there is an estimated shortage of 6.4 million doctors, which is likely to increase the burden on medical care, including in the surgical field*5.
When resection is required due to a disease such as cancer, surgeons do preoperative planning to determine the appropriate surgical procedure for the situation, to identify the location of the nerves/vessels relative to the affected area, and more. In the past, surgeons would individually look through the hundreds of 2D tomographic images acquired by CT and MRI to imagine the location and form of the affected area and the positions of blood vessels. Essentially, they were spending many hours creating a 3D visual in their minds*6. These tasks were tedious for surgeons.
*5 Source: Institute for Health Metrics and Evaluation (IHME), University of Washington School of Medicine https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(22)00532-3/fulltext
(estimate based on number of physicians needed globally to meet the authors’ specified target of 80 out of 100 on the universal health coverage effective coverage index).
*6 Yukio Oshiro, Nobuhiro Ohkohchi Three-Dimensional Liver Surgery Simulation: Computer-Assisted Surgical Planning with Three-Dimensional Simulation Software and Three-Dimensional Printing Tissue Eng Part A. 2017 Jun;23(11-12):474-480. doi: 10.1089/ten.TEA.2016.0528. Epub 2017 Apr 25. PMID: 28343411
Christophe Fleury of FUJFILM Healthcare Europe is introducing 3D medical image analysis systems to the surgical field mainly in Europe, Middle East and Africa.
— Christophe
I have been involved with Fujifilm’s 3D medical image analysis system since the development stage. My current role is as an intermediary between surgeons and the IT technicians developing this system. The most rewarding aspect of my job is how we are able to support not only doctors but also patients by developing the features that doctors want.
With the use of new technology, surgeons’ accuracy*7 and efficiency will increase, allowing more patients to access treatment. By solving the problems of surgeons and patients with our technology, we hope to contribute to people's health.
*7 Xue-Yin Shen, Hee-Jung Wang, Bong-Wan Kim, Sung-Yeon Hong, Mi-Na Kim, Xu-Guang Hu Can we delineate preoperatively the right and ventral margins of caudate lobe of the liver? Ann Surg Treat Res. 2019 Sep;97(3):124-129. doi: 10.4174/astr.2019.97.3.124. Epub 2019 Aug 29. PMID: 31508392
In only 2 to 3 minutes, a high volume of certain 2D images can become 3D*8. Making it possible to identify resection areas with greater precision
In just two to three minutes, our 3D medical image analysis system can convert certain CT and MRI tomograms into highly accurate 3D images*8, so they can be seen from various angles to provide accurate patient care. It is possible for suitably trained physicians or staff to select areas of the image and make it transparent, assign colors, and more. The surgery can be simulated before entering the operating room, and it can even be used to share the patient's condition with others on the patient’s care team.
This 3D medical image analysis system is most often used for lung, kidney, liver, pancreas, and colon cancer surgeries*9. Not only does it enable a more precise determination of the location of blood vessels, but it can also accommodate certain specific requests of surgeons. For example, if measurements can be made automatically from the 3D reconstructions, it will be easier for surgeons to ensure good safety margins around affected areas before resection. Our 3D medical image analysis delivers on this and does in fact make it easier for surgeons to ensure good margins.
By using this system in preoperative planning, surgeons can quickly grasp the patient's specific anatomical structures in three dimensions. As doctors are able to see the affected area more precisely, they are able to minimize the resection area, which can contribute to reducing the postoperative effects for the patient*10.
Another function of the 3D medical image includes its usage in explaining the surgery to the patient. When patients understand the pathology and surgical procedure, it promotes their active participation in treatment and postoperative care.
*8 This is the median time frame for 3D reconstruction of whole liver, intrahepatic vasculatures, and liver tumor from computed tomography images. Source: Takamoto T, Ban D, Nara S, Mizui T, Nagashima D, Esaki M, Shimada K. Automated Three-Dimensional Liver Reconstruction with Artificial Intelligence for Virtual Hepatectomy. J Gastrointest Surg. 2022 Oct;26(10):2119-2127. doi: 10.1007/s11605-022-05415-9. Epub 2022 Aug 8. PMID: 35941495.
*9 Fujifilm’s image recognition technology is not intended for use with or for the primary diagnostic interpretation of mammography images.
*10 Kiyoshi Hasegawa, Norihiro Kokudo, Hiroshi Imamura, Yutaka Matsuyama, Taku Aoki, Masami Minagawa, Keiji Sano, Yasuhiko Sugawara, Tadatoshi Takayama, Masatoshi Makuuchi Prognostic impact of anatomic resection for hepatocellular carcinoma Ann Surg. 2005 Aug;242(2):252-9. doi: 10.1097/01.sla.0000171307.37401.db. PMID: 16041216
Listening to surgeons' needs for even better systems
– Christophe
Around 2010, 3D medical image analysis systems were uncommon in the surgical field. That’s when we invited a number of surgeons and gave a presentation about this system.
We had proudly considered our system to be a breakthrough solution, but we were not sure what the surgeons would think of it. However, after I finished my presentation and left the podium, one doctor came over excitedly and said, “I want to use this system as soon as possible in my hospital.”
He became the first surgeon in Europe to adopt our 3D medical image analysis system.
When the surgeon told us, “This is beneficial to not only me, but to my patients,” we felt even more confident that our solution was in the right direction. Working closely with our technicians, we are determined to keep advancing our system to support all surgeons even more.
I am not a doctor, but I believe that with technology, we can help save the future of more people.
— Christophe
Technology supports us in every aspect of society. It will play an increasingly important role in the field of medicine, in places where we do not usually see it.
I am not a doctor, so I cannot help a patient in front of me like a surgeon. However, if we can improve the efficiency of surgeries and use of time of doctors with Fujifilm technology and products, I believe we can help to save the future of even more people.
And even as of today, I can say I am working with surgeons on operations, albeit from a distance.
Fujifilm began providing 3D image analysis systems in 2008. We support doctors and patients worldwide by applying to the medical field the image-processing technology that we have continued to pursue over the past 70 years. Automatic extraction from MRI data and enhanced vascular system extraction capabilities are all possible because of the data accumulated over time. We are also taking steps toward further enhancement of AI technology*11 in 3D medical image analysis systems.
*11 Software that uses AI technology, Deep Learning, in its design.
The performance and accuracy of the system do not automatically change after it is put on the market.
Application of AI Technology in 3D Medical Image Analysis Systems
Deep Learning is a form of AI machine learning that uses an algorithm based on the information-processing mechanisms of the human brain. By having AI learn a large amount of data, we are able to build complex recognition algorithms. Additionally, for Fujifilm’s 3D medical image analysis system, by taking in large amounts of image data of internal organs and other body parts, the system can automatically comprehend certain characteristics of a patient's anatomy. We are developing and operating this technology according to FDA rules and clearances to detect and measure suspected diseases in target images and areas.
Fujifilm will continue to strive for solutions to help reduce the burdens on doctors and patients.
We will NEVER STOP taking on healthcare challenges together.
For a healthier future.
Business solutions in all areas of prevention, diagnosis, and treatment.
Since Fujifilm launched its x-ray film in 1936, we have developed a wide range of diagnostic products, including x-ray diagnostic systems, ultrasound diagnostic systems, endoscopes, MRI, and CT. We have also applied our technological expertise from producing photographic films to enter the fields of prevention and treatment by developing and manufacturing biopharmaceuticals such as antibody drugs and vaccines, as well as providing key materials essential for the development of pharmaceutical products. As a comprehensive healthcare company, we will continue to leverage our wide range of technologies and expertise to contribute to people's health and advancement of healthcare.
References for the video
“More precise identification of the affected area”
Xue-Yin Shen, Hee-Jung Wang, Bong-Wan Kim, Sung-Yeon Hong, Mi-Na Kim, Xu-Guang Hu Can we delineate preoperatively the right and ventral margins of caudate lobe of the liver? Ann Surg Treat Res. 2019 Sep;97(3):124-129. doi: 10.4174/astr.2019.97.3.124. Epub 2019 Aug 29. PMID: 31508392
“Minimization of resection volume”
Shun-Ichi Ariizumi, Yutaka Takahashi, Yoshihito Kotera, Akiko Omori, Godai Yoneda, Han Mu, Satoshi Katagiri, Hiroto Egawa, Masakazu Yamamoto Novel virtual hepatectomy is useful for evaluation of the portal territory for anatomical sectionectomy, segmentectomy, and hemihepatectomy J Hepatobiliary Pancreat Sci. 2013 Mar;20(3):396-402. doi: 10.1007/s00534-012-0573-z. PMID: 23179558
Hisashi Saji, Tatsuya Inoue, Yasufumi Kato, Yoshihisa Shimada, Masaru Hagiwara, Yujin Kudo, Soichi Akata, Norihiko Ikeda Virtual segmentectomy based on high-quality three-dimensional lung modelling from computed tomography images Interact Cardiovasc Thorac Surg. 2013 Aug;17(2):227-32. doi: 10.1093/icvts/ivt120. Epub 2013 Apr 26. PMID: 23624984
Disclaimers
Fujifilm’s image recognition technology is a supplement only and cannot make diagnoses or choose treatment on its own. Physicians are responsible for the use of this workstation and must confirm that organ regions are extracted correctly when using it for measurement.
Synapse 3D is software for advanced processing and analysis of three-dimensional medical images that employs Artificial Intelligence/Deep Learning-enabled tools for Radiological and Cardiological Departments and Clinical and Surgical Departments. Synapse 3D converts two-dimensional images from scanning equipment such as PET/CT and MRI. This equipment is not part of Synapse 3D.
Synapse 3D is CE marked and is 510(k)-cleared by the U.S. FDA.
The statements by the physician in the video are based on that physician’s own opinions and experiences and on results that were achieved in that physician’s unique setting. Since many variables characterize each patient, physician, and healthcare facility, the achievement of successful results using Synapse 3D for one or set of patients does not mean that the same results will be achieved for the next patient or set of patients.
Warnings
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Only use Synapse 3D in accordance with the instructions for its intended use, and do not use Synapse 3D for any purpose other than its intended use.
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The 3D images reconstructed by Synapse 3D can inform a physician’s diagnosis of a patient or a surgeon’s proposed procedure, but cannot itself form any diagnosis, prognosis, or surgical plan, or perform any surgical procedure.
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The sale, distribution, and use of Synapse 3D is subject in the U.S. to the general controls of the he Federal Food, Drug and Cosmetic Act (as amended), the Medical Device Amendments Act of 1976 (as amended), and the regulations promulgated thereunder.
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Synapse 3D is not intended to be used as a stand-alone diagnostic or surgical device, and should only be used with imaging devices that are validated, maintained in accordance with their specifications, and operated in accordance with the manufacturer’s instructions for such use. In its capacity as the publisher of Synapse 3D, FUJIFILM makes no representations or warranties as to the validation, maintenance, or proper operation and use of any imaging devices the images from which are processed by Synapse 3D.
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Synapse 3D is not intended to characterize lesions or pathologies in a manner that would replace biopsy sampling, endoscopic, colonoscopic, laparoscopic, or similar examination, or other procedures.
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Synapse 3D is not intended to assist, but not replace, other procedures that comprise clinical decision-making.
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Because Synapse 3D is intended to reconstruct three-dimensional patient images of significant value to radiologists, physicians, and surgeons, these medical professionals could place too much reliance on these three-dimensional images, without continuing to fully use generally accepted methods of diagnosis, prognosis, and surgery.
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The results of using Synapse 3D for diagnosing, prognosing, and surgically treating patients with certain diseases and conditions, as reported in publicly available literature, cannot be extrapolated to patients with other diseases and conditions.