Correction of bias in the estimation of cell volume fraction from histology sections

Cancer characterization using light backscattering spectroscopy and quantitative ultrasound: an ex vivo study on sarcoma subtypes

Histological analysis is the gold standard method for cancer diagnosis. However, it is prone to subjectivity and sampling bias. In response to these limitations, we introduce a quantitative bimodal approach that aims to provide non-invasive guidance towards suspicious regions. Light backscattering spectroscopy and quantitative ultrasound techniques were combined to characterize two different bone tumor types from animal models: chondrosarcomas and osteosarcomas. Two different cell lines were used to induce osteosarcoma growth. Histological analyses were conducted to serve as references. Three ultrasound parameters and intensities of the light reflectance profiles showed significant differences between chondrosarcomas and osteosarcomas at the 5% level. Likewise, variations in the same biomarkers were reported for the two types of osteosarcoma, despite their similar morphology observed in the histological examinations. These observations show the sensitivity of our techniques in probing fine tissue properties. Secondly, the ultrasound spectral-based technique identified the mean size of chondrosarcoma cells and nuclei with relative errors of about 22% and 9% respectively. The optical equivalent technique correctly extracted scatterer size distributions that encompass nuclei and cells for chondrosarcomas and osteosarcomas ([Formula: see text] and [Formula: see text] respectively). The optical scattering contributions of nuclei were estimated at 52% for the chondrosarcomas and 69% for the osteosarcomas, probably indicating the abundant and the absent extracellular matrix respectively. Thus, the ultrasound and the optical methods brought complementary parameters. They successfully estimated morphological parameters at the cellular and the nuclear scales, making our bimodal technique promising for tumor characterization.

Enhancing Interrogation of Skeletal Muscle Samples for Informative Quantitative Data

Careful quantitative analysis of histological preparations of muscle samples is crucial to accurate investigation of myopathies in man and of interpretation of data from animals subjected to experimental or potentially therapeutic treatments. Protocols for measuring cell numbers are subject to problems arising from biases associated with preparative and analytical techniques. Prominent among these is the effect of polarized structure of skeletal muscle on sampling bias. It is also common in this tissue to collect data as ratios to convenient reference dominators, the fundamental bases of which are ill-defined, or unrecognized or not accurately assessable. Use of such 'floating' denominators raises a barrier to estimation of the absolute values that assume practical importance in medical research, where accurate comparison between different scenarios in different species is essential to the aim of translating preclinical research findings in animal models to clinical utility in Homo sapiens.This review identifies some of the underappreciated problems with current morphometric practice, some of which are exacerbated in skeletal muscle, and evaluates the extent of their intrusiveness into the of building an objective, accurate, picture of the structure of the muscle sample. It also contains recommendations for eliminating or at least minimizing these problems. Principal among these, would be the use of stereological procedures to avoid the substantial counting biases arising from inter-procedure differences in object size and section thickness.Attention is also drawn to the distortions of interpretation arising from use of undefined or inappropriate denominators.