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Optimization of ovine bone decalcification for increased cellular detail: a parametric study.

C BroomfieldN MeisJames W JohnsonD ReganK McGilvrayC Puttlitz
Published in: Journal of histotechnology (2021)
There are many published methods of decalcifying bone for paraffin histology; however, the current literature lacks details regarding the processing of ovine tissue. Ovine bone tissue presents challenges, as samples are often denser and larger than other comparative animal models, thus increasing decalcification times. Trifluoroacetic Acid (TFAA) has previously been used to decalcify ovine bone samples for histological analysis. Unfortunately, TFAA is a strong acid and often results in loss of cellular detail, especially in the connected soft tissue. This is generally manifested as over staining with eosin, and a decrease in cellular features which impacts overall histological interpretation. It is well known that leaving tissue in acid for long periods degrades cellular detail; therefore, minimizing decalcification time is critical to accurately determine cellular morphology. Six decalcification solutions (8% TFAA, 20% TFAA, 8% formic acid, 20% formic acid, Formical-4, and XLCal, and three temperatures (room temperature, 30°C, 37°C), were examined to determine their effects on cellular detail in ovine vertebrae and humeral heads. These data clearly indicate that 20% formic acid at 30°C yielded better decalcification rates (2.6 d ± 0.9 d) and cellular detail (none to mild changes) for the vertebrae samples, and 20% formic acid at RT yielded the best cellular detail (none to minimal loss) for humerus samples with a moderate amount of time (6.5 d ± 1.7). These results should establish the optimal demineralization procedures for ovine bone used in scientific studies resulting in improved cellular detail while minimizing decalcification times.
Keyphrases
  • soft tissue
  • bone mineral density
  • room temperature
  • systematic review
  • machine learning
  • randomized controlled trial
  • postmenopausal women
  • high intensity
  • electronic health record
  • big data