Characterization of a bipartite medial cuneiform: micro-CT and anatomical study / Caracterización de un cuneiforme medial bipartito: micro-CT y estudio anatómico

A bipartite medial cuneiform is an anatomical variant consisting in a horizontal division of the bone. Previous descriptions of the joint type, obtained from archaeological material or clinical reports, are unclear. This study was conducted in a fresh-frozen left foot, which allowed studying the morphology of the ligaments after anatomical dissection. In addition a Micro-CT analysis was performed to elucidate the osseous structure supporting the articular surfaces. A complex ligamentous system was found between the two halves of the bipartite medial cuneiform. Two articular surfaces were observed between the two components. Hyaline cartilage was observed at the posterior surface, while fibrous tissue was found at the anterior surface. Micro-CT analysis revealed different osseous structures for each articular surface, thus proving the existence of two joint types. The finding of a bipartite medial cuneiform in a fresh-frozen specimen allowed us to perform an analysis of the soft-tissues and articular surfaces that shows the presence of hyaline cartilage and articular ligaments in the diarthrodial joint as well as the fibrous component of the synfibrosis. Micro-CT analysis further reinforces our morphological findings. Our results prove that two different joint types exist, which could help explaining the disparity of descriptions in the literature.

El cuneiforme medial bipartito es una variación anatómica que consiste en una división horizontal del hueso. Las descripciones previas del tipo de articulación entre los dos fragmentos, obtenidas de material arqueológico o de reportes clínicos, son heterogéneas. Este estudio se llevó a cabo en un pie izquierdo disecado en fresco, lo que permitió analizar la morfología de los ligamentos. Adicionalmente se llevó a cabo un análisis con Micro-CT a fin de aclarar la estructura ósea de soporte de las superficies articulares. Un sistema ligamentoso complejo une las dos mitades del cuneiforme medial bipartito. Se observaron dos superficies articulares uniendo ambos componentes. En la superficie posterior se encontró cartílago hialino, en tanto que la superficie anterior presentaba tejido fibroso uniendo las superficies articulares. El análisis por Micro-CT mostró que la estructura ósea de soporte de cada una de las superficies articulares es diferente, confirmando la existencia de dos articulaciones distintas. El hallazgo de un cuneiforme medial bipartito en un espécimen fresco ha permitido el estudio de las partes blandas y superficies articulares, demostrando la presencia simultánea del cartílago hialino y los ligamentos propios de una diartrosis y del tejido fibroso propio de una sinfibrosis, lo que ha sido posteriormente corroborado por el análisis por Micro-CT. Nuestros resultados demuestran por tanto que se trata de dos articulaciones distintas, lo cual explica la disparidad de las descripciones en la literatura.

Breastfeeding and Immunohistochemical Expression of ki-67, p53 and BCL2 in Infiltrating Lobular Breast Carcinoma.

BACKGROUND/AIM: Invasive lobular breast carcinoma is the second most common type of breast cancer after invasive ductal carcinoma. According to the American Cancer Society, more than 180,000 women in the United States find out they have invasive breast cancer each year. Personal history of breast cancer and certain changes in the breast are correlated with an increased breast cancer risk. The aim of this work was to analyze breastfeeding in patients with infiltrating lobular breast carcinoma, in relation with: 1) clinicopathological parameters, 2) hormonal receptors and 3) tissue-based tumor markers. MATERIALS AND METHODS: The study included 80 women with ILC, 46 of which had breastfeed their children. Analyzed parameters were: age, tumor size, axillary lymph node (N), distant metastasis (M), histological grade (HG), estrogen receptor (ER), progesterone receptor (PR), androgen receptor (AR), Ki-67, p53 and BCL2. RESULTS: ILC of non-lactating women showed a larger (p = 0.009), lymph node involvement (p = 0.051) and distant metastasis (p = 0.060). They were also more proliferative tumors measured by Ki-67 (p = 0.053). Breastfeeding history did not influence the subsequent behavior of the tumor regardless of histological subtype. CONCLUSION: Lactation seems to influence the biological characteristics of ILC defining a subgroup with more tumor size, axillary lymph node involvement, distant metastasis and higher proliferation measured by ki-67 expression.

A quantitative method for the characterization of lytic metastases of the bone from radiographic images.

The aim of our study was to assess the diagnostic usefulness of the gray level parameters to distinguish osteolytic lesions using radiological images. Materials and Methods. A retrospective study was carried out. A total of 76 skeletal radiographs of osteolytic metastases and 67 radiographs of multiple myeloma were used. The cases were classified into nonflat (MM1 and OL1) and flat bones (MM2 and OL2). These radiological images were analyzed by using a computerized method. The parameters calculated were mean, standard deviation, and coefficient of variation (MGL, SDGL, and CVGL) based on gray level histogram analysis of a region-of-interest. Diagnostic utility was quantified by measurement of parameters on osteolytic metastases and multiple myeloma, yielding quantification of area under the receiver operating characteristic (ROC) curve (AUC). Results. Flat bone groups (MM2 and OL2) showed significant differences in mean values of MGL (P = 0.048) and SDGL (P = 0.003). Their corresponding values of AUC were 0.758 for MGL and 0.883 for SDGL in flat bones. In nonflat bones these gray level parameters do not show diagnostic ability. Conclusion. The gray level parameters MGL and SDGL show a good discriminatory diagnostic ability to distinguish between multiple myeloma and lytic metastases in flat bones.

Design of a Web-tool for diagnostic clinical trials handling medical imaging research.

New clinical studies in medicine are based on patients and controls using different imaging diagnostic modalities. Medical information systems are not designed for clinical trials employing clinical imaging. Although commercial software and communication systems focus on storage of image data, they are not suitable for storage and mining of new types of quantitative data. We sought to design a Web-tool to support diagnostic clinical trials involving different experts and hospitals or research centres. The image analysis of this project is based on skeletal X-ray imaging. It involves a computerised image method using quantitative analysis of regions of interest in healthy bone and skeletal metastases. The database is implemented with ASP.NET 3.5 and C# technologies for our Web-based application. For data storage, we chose MySQL v.5.0, one of the most popular open source databases. User logins were necessary, and access to patient data was logged for auditing. For security, all data transmissions were carried over encrypted connections. This Web-tool is available to users scattered at different locations; it allows an efficient organisation and storage of data (case report form) and images and allows each user to know precisely what his task is. The advantages of our Web-tool are as follows: (1) sustainability is guaranteed; (2) network locations for collection of data are secured; (3) all clinical information is stored together with the original images and the results derived from processed images and statistical analysis that enable us to perform retrospective studies; (4) changes are easily incorporated because of the modular architecture; and (5) assessment of trial data collected at different sites is centralised to reduce statistical variance.

A complementary method for the detection of osteoblastic metastases on digitized radiographs.

PURPOSE: This study was conducted to evaluate the diagnostic usefulness of gray level parameters in order to distinguish healthy bone from osteoblastic metastases on digitized radiographs. MATERIALS AND METHODS: Skeletal radiographs of healthy bone (n = 144) and osteoblastic metastases (n = 35) were digitized using pixels 0.175 mm in size and 4,096 gray levels. We obtained an optimized healthy bone classification to compare with pathological bone: cortical, trabecular, and flat bone. The osteoblastic metastases (OM) were classified in nonflat and flat bone. These radiological images were analyzed by using a computerized method. The parameters (gray scale) calculated were: mean, standard deviation, and coefficient of variation (MGL, SDGL, and CVGL, respectively) based on gray level histogram analysis. Diagnostic utility was quantified by measurement of parameters on healthy and pathological bone, yielding quantification of area under the receiver operating characteristic (ROC) curve, AUC. RESULTS: All three image parameters showed high and significant values of AUC when comparing healthy trabecular bone and nonflat bone OM, showing MGL the best discriminatory ability (0.97). As for flat bones, MGL showed no ability to distinguish between healthy and flat bone OM (0.50). This could be achieved by using SDGL or CVGL, with both showing a similar diagnostic ability (0.85 and 0.83, respectively). CONCLUSION: Our results show that the use of gray level parameters quantify healthy bone and osteoblastic metastases zones on digitized radiographs. This may be helpful as a complementary method for differential diagnosis. Moreover, our method will allow us to study the evolution of osteoblastic metastases under medical treatment.