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Cancer diagnosis is based on the assessment of patient biopsies to determine the tumor type, grade, and stage of malignancy. The proliferative potential of tumors correlates to their growth and metastasis. Visually identifying and quantifying mitotic figures (MF) in cancer biopsy tissue can be used as a surrogate for proliferative activity in tumors.

Cancer diagnosis depends on the assessment of patient biopsies to determine tumor type, grading, and stage of malignancy. Pathologists visually review specimens and count mitotic figures (MF) in a variety of cancer types to help gauge aggressiveness, guide treatment, and inform patient prognosis. Current technology for recording MF counts in surgical pathology is lacking in objectivity, and enumeration of MF by microscopy can be error prone. In particular, a lack of systematic means for recording contributes to recognized variability.

Scientists at the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD) have developed a method implemented as pulse sequences and software to be used with magnetic resonance imaging (MRI) scanners and systems. This technology is available for licensing and commercial development. The method allows for measuring and mapping features of the bulk or average apparent diffusion coefficient (ADC) of water in tissue – aiding in stroke diagnosis and cancer therapy assessment.

Medical imaging is an important resource for early diagnostic, detection, and effective treatment of cancers. However, the screening and review processes for radiologists have been shown to overlook a certain percentage of potentially cancerous image features. Such review errors may result in misdiagnosis and failure to identify tumors. These errors result from human fallibility, fatigue, and from the complexity of visual search required.

Many biological and clinical procedures require functional validation of a desired cell type. Current techniques to validate rely on various assays and methods, such as staining with dyes, antibodies, and nucleic acid probes, to assess stem cell health, death, proliferation, and functionality. These techniques potentially destroy stem cells and risk contaminating cells and cultures by exposing them to the environment; they are low-throughput and difficult to scale-up.

The successful treatment of cancer is correlated with the early detection of the cancerous cells. Conventional cancer diagnosis is largely based on qualitative morphological criteria, but more accurate quantitative tests could greatly increase early detection of malignant cells. It has been observed that the spatial arrangement of DNA in the nucleus is altered in cancer cells in comparison to normal cells. Therefore, it is possible to distinguish malignant cells by mapping the position of labeled marker genes in the nucleus.

Available for commercial development is software that provides automatic visualization of features inside biological image volumes in 3D. The software provides a simple and interactive visualization for the exploration of biological datasets through dataset-specific transfer functions and direct volume rendering. The method employs a K-Means++ clustering algorithm to classify a two-dimensional histogram created from the input volume. The classification process utilizes spatial and data properties from the volume.

Accurate measurement of low metabolite concentrations produced by medically important enzymes is commonly obscured by noise during magnetic resonance imaging (MRI). Measuring the turnover rate of low-level metabolites can directly quantify the activity of enzymes of interest, including possible drug targets in cancer and other diseases. Noise can cause the in vivo signal to fall below the limit of detection. A variety of denoising methods have been proposed to enhance spectroscopic peaks, but still fall short for the detection of low-intensity signals.

This invention pertains to a system for continuous observation of rodents in home-cage environments with the specific aim to facilitate the quantification of activity levels and behavioral patterns for mice housed in a commercial ventilated cage rack.  The home-cage in-rack provides daytime and nighttime monitoring with the stability and consistency of a home cage environment.