Physics World 07月02日 16:00
PhD student Ekaterina Shanina wins Early Career Researcher Award for PET phantom study
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加州大学戴维斯分校的博士生Ekaterina Shanina因其关于正电子发射断层扫描(PET)新型脑部模型的开创性研究,荣获“医学物理与生物学”早期职业研究者奖。Shanina的研究描述了一种名为PICASSO的独特PET脑部模型,该模型能够以极高的定量精度模拟静态和动态神经影像PET研究。该模型通过使用22Na点源在PET扫描仪的视野内移动,从而“绘制”数据集,克服了传统模型的诸多限制,简化了准备过程,并能够模拟动态研究。

🧠 Ekaterina Shanina因其在PET脑部模型研究中的杰出贡献,荣获Physics in Medicine & Biology早期职业研究者奖。

💡 Shanina的研究重点是开发一种名为PICASSO的新型PET脑部模型,该模型能够用于模拟逼真的静态和动态神经影像PET研究。

⚙️ PICASSO模型通过移动22Na点源来“绘制”数据集,克服了传统PET模型的局限性,如准备复杂和难以模拟动态研究等问题。

🔬 该模型能够生成具有任意静态和动态活动分布的脑部(或其他身体部位)图像,并具有极高的定量精度。

🚀 Shanina及其同事已将二维PICASSO模型扩展到能够生成全脑图像的3D版本,并正在探索其在模拟PET扫描仪不同时间飞行分辨率方面的新应用。

Ekaterina Shanina, a PhD student at the University of California, Davis, has won the Physics in Medicine & Biology Early Career Researcher Award for her research paper describing a novel brain phantom for positron emission tomography (PET).

Shanina’s study was chosen by Physics in Medicine & Biology’s editorial board as the “best paper” (based on the quality of scientific content and peer review ratings) in the journal’s Early Career Researcher Focus Collection 2024 – a programme established to support and highlight the work of emerging researchers in the medical physics and biomedical engineering community.

“The initiative recognises that early-career researchers often produce cutting-edge, high-impact work but may not yet have widespread visibility,” says Emma Harris, a guest editor on the collection. She explains that while the collection itself showcases a broad range of high-quality work, the award was introduced to further recognise an outstanding contribution from an early-career author – defined this year as someone who completed their PhD in 2018 or later.

“The award serves to highlight exceptional research that stands out for originality, rigour or impact,” says Harris, from the UK’s Institute of Cancer Research and Royal Marsden NHS Trust. “[It will] promote prestige and visibility to the awardee within the international research community, and provide a tangible form of encouragement and recognition that can support academic career progression.”

A new phantom for high-performance PET

In her award winning paper, PICASSO: a universal brain phantom for positron emission tomography based on the activity painting technique, Shanina describes a unique PET phantom called PICASSO and shows how it can be used to model realistic static and dynamic neuroimaging PET studies with excellent quantitative accuracy.

PET imaging offers an invaluable tool for studying the brain, prompting recent interest in developing advanced high-resolution PET scanners dedicated to brain imaging. Such developments create an associated requirement for appropriate imaging phantoms to evaluate and optimize scanner performance. The PICASSO phantom aims to meet these needs.

“UC Davis has been collaborating with Yale University and United Imaging Healthcare to develop a new high-performance brain PET scanner called the NeuroEXPLORER,” Shanina explains. “This scanner has high spatial resolution, which renders the most commonly used anthropomorphic brain phantom – the Hoffman phantom – unsuitable for evaluating its performance. At the same time, we wanted to explore the activity painting technique to create this unconventional phantom for PET imaging.”

Most physical PET phantoms need to be filled with a radioactive solution, which means that they can only model one type of tracer and making changes to the phantom structure is challenging. Such phantoms also require walls to separate different regions, which interferes with quantitative image evaluation, and designs with complex internal cavities are hard to fill without residual air bubbles.

“Our PICASSO phantom overcomes many of these limitations,” says Shanina.

It works by moving a 22Na point source around within the field-of-view of a PET scanner to “paint” one high-statistics dataset. The motion of the radioactive source is controlled by a robotic arm and contrast levels are defined by computationally sampling the acquired dataset. This approach can efficiently generate phantoms with arbitrary static and dynamic activity distributions in the brain (or other body regions) using a single PET acquisition.

“PICASSO uses a single dataset acquired with a sealed point source to efficiently generate a variety of activity distributions of various complexities and with arbitrarily fine features,” Shanina explains. “There’s no need for cumbersome phantom preparation, there are no cold walls or air bubbles, and the data contain some of the scanner parameters that are difficult to model analytically. We can even use it to model dynamic studies, which is a very challenging task for conventional phantoms.”

Since the paper was published last year, Shanina and colleagues have extended the two-dimensional PICASSO phantom into a 3D version that can generate whole-brain images. “We are also working on an exciting new application for the phantom, using it to model different time-of-flight resolutions of PET scanners,” she says. “To our knowledge, you cannot do this with any other phantoms that are not simulations.”

Shanina tells Physics World that she is “honoured and humbled” to win the Early Career Researcher Award. “I am very happy that this work keeps attracting people’s attention and interest,” she says. “Of course, I don’t do this all by myself. I am very grateful to have Simon Cherry and Jinyi Qi as my advisors supporting and encouraging me on this journey.”

The post PhD student Ekaterina Shanina wins Early Career Researcher Award for PET phantom study appeared first on Physics World.

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PET 脑部扫描 PICASSO 早期职业研究者奖 医学物理
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