Radiological, histological and immunohistochemical evaluation of periapical inflammatory lesions

Vol. 57 No. 2 Suppl., 2016
This supplement was not sponsored by Outside Organizations.


Antonela-Marcela Berar, Cosmina-Ioana Bondor, Luminita Matros, Radu-Septimiu Campian

The loss of teeth is largely caused by supporting tissue damage, because of bacterial invasion from the infected root canals. Sixty patients with periapical lesions (PLs) of endodontic origin were included in the study. Clinical and radiological examination was performed. Periapical radiographs were analyzed by two independent observers to determine the size and severity of PLs, using Periapical Index (PAI) scores. The tissue samples collected by periapical curettage during apicoectomy or after dental extractions by alveolar curettage were histologically and immunohistochemically analyzed. The PLs were histologically diagnosed as: periapical granulomas (PGs), granulomas with cystic potential and radicular cysts (RCs) with various degrees of inflammation. Capillary density was evaluated using the angiogenic index after immunohistochemical staining with CD34 monoclonal antibody. A statistically significant correlation was observed between PAI scores and the size of the lesions. 68.33% of cases were PGs, 18.33% PGs with cystic potential and 18.33% RCs with different degrees of inflammation. Seventy-five percent PLs had an angiogenic index 1 and 25% had an angiogenic index 2. Statistically significant differences were obtained between the angiogenic index and lesion size (p<0.05). Capillary density within PLs did not influence the severity scores of lesions detected on radiographs. The angiogenic index appeared not to be associated with the histological lesion type and the intensity of inflammation, but was more likely correlated with the degree of granulation tissue maturation and the size of PLs.

Corresponding author: Antonela-Marcela Berar, Teaching Assistant; e-mail:

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Otilia-Constantina Rogoveanu, Diana Kamal, Magdalena-Rodica Traistaru, Costin Teodor Streba

Gonarthrosis is a degenerative disease that affects mainly older people, but whose incidence has increased significantly in the last decade in population under the age of 65. The main objective of this study was developing a predictive model of synovial membrane degradation in relation to local nerve structures in patients with knee osteoarthritis, based on advanced morphometry and artificial neural networks (ANNs). We present here a pilot test of the method, describing preliminary findings in analyzing a pre-set number of images. We tested the system on a pre-defined set of 50 images from patients suffering of gonarthrosis in different stages. Biological material used for the histological study was synovial membrane fragments. We included 50 anonymized images from 25 consecutive patients. We found significant differences between mean fractal dimensions (FDs) of histological elements of normal and pathological tissues. In the case of immunohistochemistry, we found statistically relevant differences for mean FDs of all antibodies. We fed the data to the ANN system designed to recognize pathological regions of the examined tissue. We believe that further study will have an important contribution to the development and will bring new local targeted therapies. These could slow or reverse joint damage and pain relief in patients with osteoarthritis.

Corresponding author: Magdalena-Rodica Traistaru, Associate Professor, MD, PhD; e-mail:

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