Large Image Microscope Array for the Compilation of Multimodality Whole Organ Image Databases

Abstract

Three-dimensional, structural and functional digital image databases have many applications in education, research, and clinical medicine. However, to date, apart from cryosectioning, there have been no reliable means to obtain whole-organ, spatially conserving histology. Our aim was to generate a system capable of acquiring high-resolution images, featuring microscopic detail that could still be spatially correlated to the whole organ. To fulfill these objectives required the construction of a system physically capable of creating very fine whole-organ sections and collecting high-magnification and resolution digital images. We therefore designed a large image microscope array (LIMA) to serially section and image entire unembedded organs while maintaining the structural integrity of the tissue. The LIMA consists of several integrated components: a novel large-blade vibrating microtome, a 1.3 megapixel peltier cooled charge-coupled device camera, a high-magnification microscope, and a three axis gantry above the microtome. A custom control program was developed to automate the entire sectioning and automated raster-scan imaging sequence. The system is capable of sectioning unembedded soft tissue down to a thickness of 40 mm at specimen dimensions of 200 3 300 mm to a total depth of 350 mm. The LIMA system has been tested on fixed lung from sheep and mice, resulting in large high-quality image data sets, with minimal distinguishable disturbance in the delicate alveolar structures.

An Automated Segmentation Approach for Highlighting the Histological Complexity of Human Lung Cancer

“…Following fixation the nodules were isolated from the surrounding lobe via gross dissection. A custom built system, termed the large image microscope array (LIMA), was utilized to sequentially image and section throughout the entire nodule mass at 250 μ m intervals 15. Each 250 μ m nodule section underwent paraffin processing, was embedded and sectioned to generate a series of slides with 4 μ m histology sections.…”

Exploration of the volumetric composition of human lung cancer nodules in correlated histopathology and computed tomography

“…These multi modal datasets have include multi row detector computerized tomography (MDCT) scans, micro-CT scans, and three dimensional pathology using a purpose built precision tissue microtome with digital camera that is referred to as the Large Image Microscope Array (LIMA) [2], as well as standard histopathology. All of these samples from the same lung cancer are cross registered pixel for pixel, giving the opportunity to describe the complexity of the lung cancer biomass.…”

A Process Model for Direct Correlation between Computed Tomography and Histopathology

“…The nodules were then imaged using the Siemens MicroCAT II system (Siemens Pre-Clinical, Knoxville, TN) at 80 keV, 100 microA to produce isotropic 28 micron voxels. LIMA subsequently sectioned the tissue at 252 microns and imaged the cut tissue surface at a resolution of 8.5 × 8.5 microns (10 × magnification) (9–12). The LIMA system imaged the tissue surface before cutting and removing the section, hence retaining the spatial correspondence between tissue sections as described in the introduction (Fig 1).…”