Smartphone image analysis for real time adequacy assessment during kidney biopsy

摘要该项目的目标是开发可作为智能手机部署的图像分析工具 在经皮肾活检（PRB）过程中辅助真实的活检充分性评估的应用 程序. PRB仍然是诊断和治疗内科肾病患者的重要工具 该技术是一种治疗肾脏疾病的方法，包括使用活检枪从肾脏获得一个小的组织针芯。一 如果获得了足够的肾皮质组织以满足提供肾活检的标准，则认为活检是“足够的”。 组织病理学诊断如果获得的组织不足，或者如果组织不含肾皮质， 足够的肾小球，那么核心被认为是“不足”的。在过去的15年里， 由于组织不足，不足以进行完整诊断的患者已上升至15%， 对卫生保健系统以及直接风险的病人谁必须重新活检或去没有准确的 诊断.理想情况下，可以在活检时通过检查获得的核心来评估充分性， 病理学家的显微镜这种真实的时间评估使得活检医师能够获得额外的信息。 如果认为现有组织芯不充分，则使用组织芯。然而，资源限制明显 限制了许多活检室中充分性评价的可用性。随着广泛采用 通过智能手机，现在有机会通过宏观图像而不是显微镜来评估活检组织。 另一个步骤是将图像分析功能构建到智能手机上的应用程序中， 活检医生获得关于他们收集的材料是否 足够或活检是否“错过”，以及需要获得更多的组织。最近对123，372名原住民的研究 肾活检发现，PRB的漏诊率从2005年的2%显著增加到2020年的14%， 这归因于进行活检的放射科医生的参与增加， 直径的活检针。肾活检漏诊率的增加显着影响了患者的护理 医学肾脏疾病的管理，并强调需要改进的工具， 在患者离开活检室之前收集的组织是否充足。在第一阶段，Arkana实验室 将与波士顿大学的Kolachalama实验室合作，使用从未使用过的 开发一个深度神经网络，可以准确地分类活检的哪些部分， 核心代表肾皮质与非皮质组织，其可包括肾髓质、肾周脂肪、纤维囊， 和非肾组织。在第二阶段，我们将使用从肾脏活检中获得的图像来扩展这些努力。 由Arkana优化算法评估的充分性，然后使用这些结果来开发一个 专业版的智能手机应用程序，将提供给所有肾活检从业者使用 几乎任何智能手机摄像头。

SUMMARY. The goal of this project is to develop image analysis tools that can be deployed as a smartphone application to aid in the real time assessment of biopsy adequacy during percutaneous renal biopsy (PRB) procedures. PRB remains an essential tool for the diagnosis and treatment of patients with medical kidney disease and involves obtaining a small needle core of tissue from the kidney with the use of a biopsy gun. A biopsy is deemed “adequate” if sufficient renal cortical tissue is obtained to meet criteria for rendering a histopathologic diagnosis. If insufficient tissue is obtained, or if the tissue does not contain renal cortex with enough glomeruli, then the core is deemed “inadequate”. Over the last 15 years, the rate of kidney biopsies that are inadequate for complete diagnosis due to insufficient tissue has risen to 15%, representing a significant drain on the health care system as well as a direct risk to patients who must be re-biopsied or go without an accurate diagnosis. Ideally, adequacy can be assessed at the time of biopsy by examination of the obtained cores under a microscope by a pathologist. Such real time assessment enables the biopsy physician to obtain additional cores of tissue if existing cores are deemed to be inadequate. However, resource constraints have markedly limited the availability of adequacy evaluation within many biopsy suites. With the widespread adoption of smartphones, there is now an opportunity to evaluate biopsy tissue via macro images instead of a microscope. An additional step is to build image analysis capabilities into an application on the smartphone, thus enabling the biopsy physician to obtain reliable instantaneous feedback about whether the material they have collected is sufficient or whether the biopsy “missed”, and more tissue needs to be obtained. A recent study of 123,372 native kidney biopsies found that the miss rate in PRB increased markedly from 2% in 2005 to 14% in 2020, largely attributed to the increased involvement of radiologists performing the biopsies and their preference for smaller diameter biopsy needles. This increase in kidney biopsy miss rate significantly impacts patient care in the management of medical kidney disease and highlights the need for improved tools for assessing the adequacy of tissue collected before the patient leaves the biopsy suite. In Phase I, Arkana Laboratories will collaborate with the Kolachalama laboratory at Boston University using biopsy cores taken from unused deceased donor kidneys to develop a deep neural network that can accurately classify which portions of a biopsy core represent renal cortex vs non-cortex tissue, which may include renal medulla, perirenal fat, fibrous capsule, and non-renal tissue. In Phase II, we will extend these efforts using images taken from kidney biopsies received by Arkana to optimize the algorithmic assessment of adequacy and then use these results to develop a professional version of the smartphone application that will be available to all kidney biopsy practitioners using virtually any smartphone camera.