Elastic Properties of Aging Human Hematoma Model In Vitro and Its Susceptibility to Histotripsy Liquefaction.

Objective: Tissue susceptibility to histotripsy disintegration has been reported to depend on its elastic properties. This work was aimed at investigation of histotripsy efficiency for liquefaction of human hematomas, depending on their stiffness and degree of retraction over time (0-10 d).

Methods: As an in vitro hematoma model, anticoagulated human blood samples (200 mL) were recalcified at different temperatures.

Machine learning based local recurrence prediction in colorectal cancer using polarized light imaging.

Significance: Current treatment for stage III colorectal cancer (CRC) patients involves surgery that may not be sufficient in many cases, requiring additional adjuvant systemic therapy. Identification of this latter cohort that is likely to recur following surgery is key to better personalized therapy selection, but there is a lack of proper quantitative assessment tools for potential clinical adoption.

Aim: The purpose of this study is to employ Mueller matrix (MM) polarized light microscopy in combination with supervised machine learning (ML) to quantitatively analyze the prognostic value of peri-tumoral collagen in CRC in relation to 5-year local recurrence (LR).

Mueller matrix polarization parameters correlate with local recurrence in patients with stage III colorectal cancer.

The peri-tumoural stroma has been explored as a useful source of prognostic information in colorectal cancer. Using Mueller matrix (MM) polarized light microscopy for quantification of unstained histology slides, the current study assesses the prognostic potential of polarimetric characteristics of peri-tumoural collagenous stroma architecture in 38 human stage III colorectal cancer (CRC) patient samples. Specifically, Mueller matrix transformation and polar decomposition parameters were tested for association with 5-year patient local recurrence outcomes.