Medtech firms get personal with digital twins 利用數位雙胞胎 醫學科技公司「探人隱私」

Sun, Sep 09, 2018 - Page 9

Armed with a mouse and computer screen instead of a scalpel and operating theater, cardiologist Benjamin Meder carefully places the electrodes of a pacemaker in a beating, digital heart. Using this “digital twin” that mimics the electrical and physical properties of the cells in patient 7497’s heart, Meder runs simulations to see if the pacemaker can keep the congestive heart failure sufferer alive — before he has inserted a knife.

The digital heart twin developed by Siemens Healthineers is one example of how medical device makers are using artificial intelligence (AI) to help doctors make more precise diagnoses as medicine enters an increasingly personalized age. Experts say the success of AI in medical technology will hinge on access to reliable data, not only to create models for diagnosis but also to predict how effective treatments will be for a specific patient in the days and years to come.

“Imagine that in the future, we have a patient with all their organ functions, all their cellular functions, and we are able to simulate this complexity,” said Meder, a cardiologist at Heidelberg University Hospital in Germany who is testing Siemens Healthineers’ digital heart software. “We would be able to predict weeks or months in advance which patients will get ill, how a particular patient will react to a certain therapy, which patients will benefit the most. That could revolutionize medicine.”

To this end, Siemens Healthineers has built up a vast database of more than 250 million annotated images, reports and operational data on which to train its new algorithms. In the example of the digital twin, the AI system was trained to weave together data about the electrical and physical properties and the structure of a heart into a 3D image. One of the main challenges was hiding the complexity and creating an interface that is easy to use, said Tommaso Mansi, a senior R&D director at Siemens Healthineers who developed the software.

To test the technology, Meder’s team created 100 digital heart twins of patients being treated for heart failure in a six-year trial. The computer makes predictions based on the digital twin and they are then compared with actual outcomes. His team hopes to finish evaluating the predictions by the end of this year. If the results are promising, the system will be tested in a larger, multi-center trial as the next step to getting the software approved by regulators for commercial use.

(Reuters)

心臟科醫師班雅明‧梅德爾沒有拿手術刀,人也不在手術室,只準備了一隻滑鼠和電腦螢幕,就在一顆跳動的數位心臟裡面細心裝設心律調節器的電極。藉由這個「數位雙胞胎」,模擬出編號7497病人心臟內細胞的電子與物理特性。在真正下刀前,梅德爾跑了多次模擬,確認這個心律調節器能否讓一位鬱血性心臟衰竭的患者存活下來。

隨著醫學邁入愈趨個人化的時代,醫療器材製造商開始運用人工智慧來協助醫生做出更精確的診斷,西門子醫療研發的數位心臟雙胞胎只是其中的一個例子。專家認為,人工智慧能否在醫學技術領域獲得成功,將取決於可信賴數據的存取權限,這不只是為了製造出診斷用的模型,同時也是為了預測治療方式對某位特定病人日後或未來數年的有效程度。

梅德爾表示:「想像一下,未來有一位病人具備完整的器官功能、細胞功能,然後我們能夠模擬這樣的複雜性。」梅德爾是德國海德堡大學醫院的心臟科醫師,目前正在試用西門子醫療的數位心臟軟體。他指出:「我們可能有能力在數星期或數個月之前就預測出哪一位病人會生病、某一位特定病人將會對某種療法產生什麼樣的反應,哪些病人會受惠最多。這可能對醫學帶來革命。」

為了這個目標,西門子醫療建置了一個巨大資料庫,收錄超過兩億五千萬張附有註解的影像、報告,以及運算數據,藉此訓練出新的演算機制。以數位雙胞胎為例,人工智慧系統被訓練為能把某顆心臟的電子與物理特性、以及其結構的種種數據編製成3D影像。開發出該軟體的西門子醫療研發部門資深主管托瑪索‧曼西表示,主要的挑戰之一在於把複雜性隱藏起來,設計出容易使用的介面。

為了測試這項技術,梅德爾的團隊在為期六年的臨床試驗中,為因心臟衰竭而接受治療的病人們創造出一百顆數位雙胞胎心臟。電腦根據這些數位雙胞胎做出預測,然後這些預測會被拿來和實際結果進行比較。該團隊希望能在二○一八年底完成預測的評估。如果評估結果前景看好,這個系統將會以更大的規模,並在多間醫學中心進行臨床試驗,讓該軟體邁向下一步,以期獲得有關當局核准可供商業使用。

(台北時報章厚明譯)