From the cluster to the clinic: Real-time treatment planning for transcranial ultrasound therapy using deep learning (Ext.)

这是早期职业奖学金的延伸：聚焦超声手术基于模型的治疗计划。脑部疾病对世界各地的卫生服务构成巨大挑战，研究表明，这些疾病影响了多达三分之一的成年人口。在英国，大约六分之一的人患有神经系统疾病，六分之一的人患有常见的精神疾病。据估计，这些疾病每年的总费用超过1000亿英镑。这些疾病对患者来说是毁灭性的，并大大降低了他们的生活质量。今天，病人通常通过处方药物来改变大脑的功能。对许多病人来说，这可以减轻他们的症状。然而，如果这些药物长期使用，它们的有效性往往会下降，并且可能有许多副作用。由于存在一种被称为血脑屏障的保护层，药物也很难像预期的那样离开血流进入大脑。根据他们的诊断，一些患者可能还会接受外科手术，切除部分大脑或植入小电线，利用电流刺激脑细胞。一个令人兴奋的替代药物和手术是使用超声波。超声波成像以拍摄怀孕期间发育中的婴儿而闻名。然而，超声波现在也开始用于治疗脑部疾病。这是可能的，因为超声波会引起机械振动，以不同的方式影响大脑。例如，它们可以使组织升温或产生搅动脑细胞和组织支架的力量。根据所使用的超声脉冲的模式，可能有几种不同类型的治疗。这包括精确地破坏组织的小区域，在大脑中产生或抑制电信号，或者暂时打开血脑屏障以使药物更有效地输送。这些治疗都是完全非侵入性的，有可能显著改善患者的预后。超声治疗的一个主要挑战是确保超声能量被传递到医生确定的精确位置。这很困难，因为颅骨非常坚硬，导致超声波被反射和扭曲。利用强大的超声波在人体中传播的计算机模型来预测和纠正这些扭曲是可能的。然而，这些模型可能需要数小时或数天才能在大型超级计算机上运行，因此目前还不能用于患者治疗。这项研究的目的是开发一种新型模型，可以非常快速地预测声波在大脑中的传播方式。这将基于一种称为深度学习的特殊类型的人工智能。深度学习模型将被训练来预测由颅骨引起的变形。模型将通过使用上述强大的计算机模型生成的大量训练样例来学习这一点。作为该项目的一部分，这些模型将使用以往临床治疗的患者数据进行严格测试。还将进行精心策划的实验室实验，使用旨在模拟头骨和大脑的幻影材料。新的模型将允许医生自动纠正由颅骨引起的扭曲，并快速预测治疗结果。这将是脑部疾病治疗的重大突破，并使突破性的超声治疗得到广泛应用。

This is an extension of the Early Career Fellowship: Model-Based Treatment Planning for Focused Ultrasound Surgery.Brain disorders present a huge challenge for health services across the world, with studies showing these conditions affect as many as one third of the adult population. In the UK, approximately 1 in 6 people are affected by a neurological disorder and 1 in 6 by a common psychiatric disorder. The total annual cost of these conditions is estimated to exceed £100 billion. These disorders can be devastating for patients and greatly reduce their quality of life. Today, patients are often treated by the prescription of drugs that alter the way the brain functions. For many patients, this causes a reduction in their symptoms. However, if these drugs are used for long periods of time, their effectiveness often decreases and there can be many side-effects. It can also be difficult for drugs to exit the blood-stream and enter the brain as desired because of a protective lining called the blood-brain barrier. Depending on their diagnosis, some patients may also be offered surgical procedures to remove part of the brain or implant small wires that use electricity to stimulate brain cells.One exciting alternative to drugs and surgery is the use of ultrasound. Ultrasound imaging is well known for taking pictures of developing babies during pregnancy. However, ultrasound is now also starting to be used to treat brain disorders. This is possible because ultrasound waves cause mechanical vibrations that affect the brain in different ways. For example, they can cause the tissue to heat up or generate forces that agitate the brain cells and tissue scaffolding. Several different types of treatment are possible depending on the pattern of ultrasound pulses used. This includes precisely destroying small regions of tissue, generating or suppressing electrical signals in the brain, or temporarily opening the blood-brain barrier to allow drugs to be delivered more effectively. These treatments are all completely non-invasive and have the potential to significantly improve outcomes for patients. A major challenge for ultrasound therapy is ensuring the ultrasound energy is delivered to the precise location identified by the doctor. This is difficult because the skull bone is very rigid and causes the ultrasound waves to be reflected and distorted. It is possible to predict and correct for these distortions using powerful computer models of how ultrasound waves travel through the body. However, these models can take many hours or days to run on large supercomputers, so cannot currently be used for patient treatments. The aim of this fellowship extension is to develop a new type of model that can make very fast predictions of how sound waves travel in the brain. This will be based on a special type of artificial intelligence called deep learning. The deep learning models will be trained to predict the distortion caused by the skull bone. The models will learn this using a large number of training examples generated using the powerful computer models mentioned above. As part of the project, the models will be rigorously tested using patient data from previous clinical treatments. Carefully planned laboratory experiments using phantom materials designed to mimic the skull and brain will also be conducted. The new models will allow doctors to automatically correct for distortions caused by the skull and quickly predict the treatment outcomes. This would be a major breakthrough in the treatment of brain disorders and enable the wide-spread application of ground-breaking ultrasound therapies.