PDF(Pubmed)
Abstract：
Skeletal muscle, the major processor of dietary glucose, stores it in myriad glycogen granules. Their numbers vary with cellular location and physiological and pathophysiological states. AI models were developed to derive granular glycogen content from electron-microscopic images of human muscle. Two UNet-type semantic segmentation models were built: \"Locations\" classified pixels as belonging to different regions in the cell; \"Granules\" identified pixels within granules. From their joint output, a pixel fraction pf was calculated for images from patients positive (MHS) or negative (MHN) to a test for malignant hyperthermia susceptibility. pf was used to derive vf, the volume fraction occupied by granules. The relationship vf (pf) was derived from a simulation of volumes (\"baskets\") containing virtual granules at realistic concentrations. The simulated granules had diameters matching the real ones, which were measured by adapting a utility devised for calcium sparks. Applying this relationship to the pf measured in images, vf was calculated for every region and patient, and from them a glycogen concentration. The intermyofibrillar spaces and the sarcomeric I band had the highest granular content. The measured glycogen concentration was low enough to allow for a substantial presence of non-granular glycogen. The MHS samples had an approximately threefold lower concentration (significant in a hierarchical test), consistent with earlier evidence of diminished glucose processing in MHS. The AI models and the approach to infer three-dimensional magnitudes from two-dimensional images should be adaptable to other tasks on a variety of images from patients and animal models and different disease conditions.
摘要：
骨骼肌,膳食葡萄糖的主要处理器，储存在无数的糖原颗粒中。它们的数量随细胞位置以及生理和病理生理状态而变化。开发了AI模型，以从人体肌肉的电子显微镜图像中得出颗粒状糖原含量。建立了两个UNet类型的语义分割模型：“位置”将像素分类为属于单元格中的不同区域；“颗粒”识别了颗粒内的像素。从他们的联合输出来看，对于恶性高热易感性测试阳性(MHS)或阴性(MHN)患者的图像,计算像素分数pf.pf被用来推导vf，颗粒占据的体积分数。关系vf（pf）是从模拟实际浓度下包含虚拟颗粒的体积（“篮子”）得出的。模拟颗粒的直径与真实颗粒相匹配，这是通过调整为钙火花设计的实用程序来测量的。将此关系应用于图像中测量的pf，计算每个地区和患者的vf，和糖原浓度。肌原纤维间空间和肌节I带的颗粒含量最高。测量的糖原浓度足够低以允许非颗粒糖原的大量存在。MHS样品的浓度大约低三倍（在分层测试中很重要），与早期MHS中葡萄糖处理减少的证据一致。AI模型和从二维图像推断三维大小的方法应该适用于来自患者和动物模型以及不同疾病状况的各种图像上的其他任务。
