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用于将高分辨率标本PET-CT与组织病理学进行联合配准以增强对放射性示踪剂分布理解的方法。

Method for co-registration of high-resolution specimen PET-CT with histopathology to improve insight into radiotracer distributions.

作者信息

Maris Luna, Göker Menekse, Debacker Jens M, De Man Kathia, Van den Broeck Bliede, Van Dorpe Jo, Van de Vijver Koen, Keereman Vincent, Vanhove Christian

机构信息

Department of Electronics and Information Systems, Medical Image and Signal Processing, Ghent University, Ghent, Belgium.

Clinical Department, XEOS Medical, Ghent, Belgium.

出版信息

EJNMMI Phys. 2024 Oct 14;11(1):85. doi: 10.1186/s40658-024-00681-9.

Abstract

BACKGROUND

As the spatial resolution of positron emission tomography (PET) scanners improves, understanding of radiotracer distributions in tissues at high resolutions is important. Hence, we propose a method for co-registration of high-resolution ex vivo specimen PET images, combined with computed tomography (CT) images, and the corresponding specimen histopathology.

METHODS

We applied our co-registration method to breast cancer (BCa) specimens of patients who were preoperatively injected with 0.8 MBq/kg [ F]fluorodeoxyglucose ([F]FDG). The method has two components. First, we used an image acquisition scheme that minimises and tracks tissue deformation: (1) We acquired sub-millimetre (micro)-PET-CT images of ±2 mm-thick lamellas of the fresh specimens, enclosed in tissue cassettes. (2) We acquired micro-CT images of the same lamellas after formalin fixation to visualise tissue deformation. (3) We obtained 1 hematoxylin and eosin (H&E) stained histopathology section per lamella of which we captured a digital whole slide image (WSI). Second, we developed an automatic co-registration algorithm to improve the alignment between the micro-PET-CT images and WSIs, guided by the micro-CT of the fixated lamellas. To estimate the spatial co-registration error, we calculated the distance between corresponding microcalcifications in the micro-CTs and WSIs. The co-registered images allowed to study standardised uptake values (SUVs) of different breast tissues, as identified on the WSIs by a pathologist.

RESULTS

We imaged 22 BCa specimens, 13 cases of invasive carcinoma of no special type (NST), 6 of invasive lobular carcinoma (ILC), and 3 of ductal carcinoma in situ (DCIS). While the cassette framework minimised tissue deformation, the best alignment between the micro-PET-CT images and WSIs was achieved after deformable co-registration. We found an overall average co-registration error of 0.74 ± 0.17 mm between the micro-PET images and WSIs. (Pre)malignant tissue (including NST, ILC, and DCIS) generally showed higher SUVs than healthy tissue (including healthy glandular, connective, and adipose tissue). As expected, inflamed tissue and skin also showed high uptake.

CONCLUSIONS

We developed a method to co-register micro-PET-CT images of surgical specimens and WSIs with an accuracy comparable to the spatial resolution of the micro-PET images. While currently, we only applied this method to BCa specimens, we believe this method is applicable to a wide range of specimens and radiotracers, providing insight into distributions of (new) radiotracers in human malignancies at a sub-millimetre resolution.

摘要

背景

随着正电子发射断层扫描(PET)扫描仪空间分辨率的提高,了解高分辨率下组织中的放射性示踪剂分布非常重要。因此,我们提出了一种用于高分辨率离体标本PET图像与计算机断层扫描(CT)图像以及相应标本组织病理学进行配准的方法。

方法

我们将配准方法应用于术前注射0.8 MBq/kg [ F]氟脱氧葡萄糖([F]FDG)的乳腺癌(BCa)患者标本。该方法有两个组成部分。首先,我们使用了一种可最小化并跟踪组织变形的图像采集方案:(1)我们获取了封装在组织盒中的新鲜标本±2毫米厚薄片的亚毫米(微观)PET-CT图像。(2)在福尔马林固定后,我们获取了相同薄片的微观CT图像以观察组织变形。(3)我们为每个薄片获取1张苏木精和伊红(H&E)染色的组织病理学切片,并采集了数字全切片图像(WSI)。其次,我们开发了一种自动配准算法,以在固定薄片的微观CT引导下改善微观PET-CT图像与WSI之间的对齐。为了估计空间配准误差,我们计算了微观CT和WSI中相应微钙化之间的距离。配准后的图像可用于研究病理学家在WSI上识别的不同乳腺组织的标准化摄取值(SUV)。

结果

我们对22个BCa标本进行了成像,其中13例为非特殊类型浸润性癌(NST),6例为浸润性小叶癌(ILC),3例为导管原位癌(DCIS)。虽然组织盒框架使组织变形最小化,但在可变形配准后,微观PET-CT图像与WSI之间实现了最佳对齐。我们发现微观PET图像与WSI之间的总体平均配准误差为0.74±0.17毫米。(癌)前组织(包括NST、ILC和DCIS)通常比健康组织(包括健康腺体、结缔组织和脂肪组织)显示出更高的SUV。正如预期的那样,发炎组织和皮肤也显示出高摄取。

结论

我们开发了一种方法,可将手术标本的微观PET-CT图像与WSI进行配准,其精度与微观PET图像的空间分辨率相当。虽然目前我们仅将此方法应用于BCa标本,但我们相信该方法适用于广泛的标本和放射性示踪剂,能够在亚毫米分辨率下深入了解(新型)放射性示踪剂在人类恶性肿瘤中的分布情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f2b/11473743/a3bebba6d8f1/40658_2024_681_Fig1_HTML.jpg

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