A\npicture is worth a thousand words. This is clearly true in medical diagnosis.\nIndeed, medical imaging has become a powerful tool in the diagnosis and\ntreatment of illness. Over the past seven years, the team in the Biomedical\nImaging Laboratory, established by the Faculty of Science and Technology (FST),\nhas worked relentlessly in this field, producing encouraging results that have\ngarnered international recognition. Prof Greta Mok, founder of the laboratory,\nhopes to apply artificial intelligence (AI) and other related technologies in\nnuclear medicine to improve diagnosis and treatment of medical conditions for\nMacao residents.<\/p>
Prof\nMok is an associate professor in the Department of Electrical and Computer\nEngineering and a joint associate professor in the Faculty of Health Sciences.\nShe is the first native of Macao to become a medical imaging scholar in Macao.\nAt age 18, she left Macao to pursue higher education at Yang-Ming University in\nTaiwan. After graduation, she was admitted by Johns Hopkins University in the\nUnited States, a universally acclaimed institution in the fields of medicine\nand public health. She is also the first Macao native to obtain a doctoral\ndegree at JHU. She was later recruited by the Chinese University of Hong Kong\nas a junior faculty member before returning to Macao to join UM in 2010. Two\nyears later, in 2012, she founded Macao\u2019s first Biomedical Imaging Laboratory.<\/p>
Nuclear Medicine Imaging<\/b><\/p>
In\nnuclear medicine, patients are given small amounts of radioisotope-labelled\ndrugs either orally or by injection. The radioisotopes then circulate through\nthe body and are absorbed specifically by target organs or tumours under\nexamination. The isotopes undergo radioactive decays and emit gamma rays from\nwithin the body, which are captured by a gamma camera to create images. By\nreconstructing and analysing these images, doctors can assess organ functions,\ntumour location, disease progression and staging, and effectiveness of the\ntreatment. Prof Mok says that organ movements, such as the beating of the heart\nor the inflation and exhalation of the lungs, can sometimes lead to artifacts,\nwhich can degrade the interpretations of imaging results.<\/p>
The\nresearch team currently focuses on the development of nuclear medical\ninstrumentation, methods of medical image generation, and subsequent processing\nand analysis, with the aim of making medical images of the brain, heart, liver\nand other organs more accurate, in order to improve the medical diagnosis and\ntreatment of cancers. \u2018Take the brain for example. We can\u2019t directly assess the\nbrain functions from the physical examination,\u2019 says Prof Mok. \u2018There are a lot\nof diseases such as Parkinson\u2019s disease and dementia that don\u2019t have obvious\nsymptoms before the onset of the diseases. So the best way to detect disease\npre-emptively is to use non-invasive medical imaging techniques, and nuclear\nmedicine has obvious advantages over other imaging technologies in this\napplication.\u2019 In the assessment of a tumour, the doctor can prescribe a\npositron emission tomography (PET) scan, where glucose labelled with\nradioactive fluorine is injected into the patient\u2019s body. Since the malignant\ntumour usually absorbs more glucose than normal tissues, the doctor can\npinpoint the location of the tumour and assess the severity of the condition by\ndetecting and quantifying the unusually \u2018bright spots\u2019.<\/p>
Three Major Research Projects<\/b><\/p>
According\nto Prof Mok, the lab currently has three major research projects. The first is\nthe development of an active breathing controller to remove respiratory\nartefacts and related image acquisition and post-processing software. When the\npatient is scanned, this controller can suspend the patient\u2019s breathing while\ncollecting images, thereby removing respiratory artefacts, improving the\nquality of imaging, and enabling more accurate quantification of the lesions.\nThe second project is to design and develop a multi-purpose, multi-pinhole\ncollimator that can collect more gamma photons than traditional single-pinhole\nand parallel-hole collimators. This collimator can enhance the sensitivity of\nthe scanner, which can in turn reduce image noise, radiation dose or scanning\ntime. The lab has commissioned a Dutch company to customise a prototype of the\ncollimator. The device has already been installed on the lab\u2019s single-photon\ncomputed tomography (CT) scanner and is undergoing further evaluation.<\/p>
In\naddition to diagnosis, radioactive drugs can also be used for treatment of\ncancers, which is exactly the focus of the lab\u2019s third project. The lab has\ndeveloped a piece of 3D computer software for internal dose calculation in\ntargeted radionuclide therapy. It can be used to evaluate the radiation dose\nabsorbed by the tumour and various organs, an important index for treatment\nefficacy and potential toxicity. Hospitals and research institutions can apply\nthis software to optimise dose calculation for each individual patient, so that\ntreatment planning could be more precise and personalised.<\/p>
Prof\nMok says that AI technology is increasingly used in medical imaging research.\nShe says, \u2018AI technology not only can help to improve the image quality, it can\nalso reduce the radiation dose. I hope to apply AI technology in all three\nresearch projects. With our first project on respiratory artifact reduction, we\nhave already successfully reduced image noise using AI technology. In the\nfuture, we will study the use of AI technology to reduce the radiation dose and\nimage acquisition time to benefit the patients.\u2019<\/p>
Enormous Potential<\/b><\/p>
Under\nthe leadership of Prof Mok, the lab has trained over a dozen postgraduate\nstudents from Macao and mainland China, who are now working at universities,\nindustries, and medical institutions in Macao and other parts of the world.\nAmong them, doctoral students Zhang Duo and Sun Jingzhang foresee enormous\npotential in applying AI technology to medical imaging research.<\/p>
Over\nthe past few years, under the guidance of Prof Mok, Zhang has published some\npapers on medical image correction, including one paper that examines the\neffects of different respiratory patterns on medical images. During his\ndoctoral study, Zhang was recommended by Prof Mok to work as a visiting scholar\nfor one year at the University of Massachusetts Medical School and Yale\nUniversity in the US, where he participated in cutting-edge research. \u2018I gained\na lot from working at Yale. According to my supervisor at Yale, I did in one\nmonth what other students did in one semester,\u2019 Zhang says. Because of his\noutstanding performance and the solid grounding in research he developed at UM,\nYale\u2019s supervisor invited him to be a postdoctoral research fellow at the\nuniversity, but he had other plans. \u2018Our lab is in close contact with research\ninstitutions in the Greater China region, Europe, and the US, and we also\ncollaborate with institutions in the Greater Bay Area, such as the Chinese\nUniversity of Hong Kong and Shenzhen Institutes of Advanced Technology of the\nChinese Academy of Sciences. I plan to find a job at a university in the\nGreater Bay Area after graduation, because I see great potential for career\ndevelopment in this area. It would also be more convenient for me to keep in\nclose research contact with Prof Mok.\u2019<\/p>
Sun\nJingzhang, another of Prof Mok\u2019s PhD students, has both a bachelor\u2019s and\nmaster\u2019s degree in computer science. One of his research projects at UM\ninvolves using artificial neural networks to reduce noise in medical imaging.\n\u2018I have a background in computer science, and I used to study image processing.\nThere aren\u2019t many people doing research in this area, so I want to explore\nmore,\u2019 he says. Sun now uses deep learning techniques to try to tackle some\nchallenging issues concerning medical image quality.<\/p>
International Recognition<\/b><\/p>
The\nresearch results from the lab have been applied on more than 50 patients in\nTaiwan and the US to improve their medical diagnosis. The team has also won\nmany awards at international conferences in recent years. At the Third Asian\nNuclear Medicine Academic Forum in 2017, the team stood out among strong\nresearch groups from Asia and won the sole first prize in the Fourth Rising\nNuclear Medicine Professional Challenge, the highest honour of the forum, for\ntheir work titled \u2018A Framework for Improved 3D Personalised Targeted\nRadionuclide Therapy Dosimetry Using Registration on Sequential ECT\/CT\u2019. It was\nthe first time that a team from Macao had won this award. The same project\nlater received the International Best Abstract Award and the third prize of the\nComputer and Instrumentation Council (CalC) Young Investigator Award (YIA) at\nthe 64th Annual Meeting of the Society of Nuclear Medicine and Molecular\nImaging held in Denver, Colorado, US in the same year. It was the first time a\nresearch team from the Greater China region had been shortlisted for, much less\nreceived, an award in this YIA category. Two other notable teams shortlisted\nfor this award were from Stanford University and MD Anderson Cancer Center.<\/p>
The\nYear 2018 continued to be a fruitful year for Prof Mok\u2019s team. At the 65th\nAnnual Meeting of the Society of Nuclear Medicine and Molecular Imaging (SNMMI)\nheld in Philadelphia, Prof Mok received the International Best Abstract Award\nfor the second consecutive year for her work titled \u2018Comparison of Different\nTc-99m-MAA Imaging Protocols for Y-90 SIRT Treatment Planning\u2019, as well as the\nTracy Lynn Faber Memorial Award, in recognition of her major contributions to\nhigh performance Emission Computed Tomography and Computed Tomography\ninstrumentation, reconstruction, and analysis. She is the first Chinese\nscientist to ever receive this prestigious award.<\/p>
\u2018These\ninternational awards are certainly very encouraging for the research team,\u2019\nsays Prof Mok. \u2018In a \u201cdesert of isotopes\u201d like Macao, it is exceedingly\ndifficult to conduct research in nuclear medicine. For the same experiment, you\nneed to work extra hard to make it happen. Most clinical trials have to be\nconducted outside of Macao. All the past winners of these international awards\nhad the full support of their medical schools. UM doesn\u2019t have a medical\nschool, and isotopes are just hard to obtain. But the team managed to overcome\nall the difficulties and won these international awards. We feel really\nhonoured and thankful.\u2019<\/p>
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It\nis not easy to build a lab from scratch. Prof Mok says, \u2018I am very grateful to\nmy team and my students for their support. I am also grateful to the university\nfor its trust and to the international and local societies for their\nrecognition. Because of them, our hard work over the years has not been in\nvain. Everyone in the lab puts their hearts and souls into what they are doing.\nThey are full of dreams and they are passionate about their research. I hope\nthe fruits of our research can be applied in Macao as well. Hopefully we will\nincrease collaborations with hospitals in Macao to let local patients be the\nfirst to benefit from our technology. Our goal is to bring real changes in the\ndiagnosis and treatment of illnesses for local residents using medical imaging\ntechnologies.\u2019<\/p>