1,720,984 research outputs found
Fractal Analysis of the Bone Marrow in Myelodysplastic Syndromes
No full textBasic researchers and clinicians are increasingly aware of the remarkable importance of the fractal approaches in the morphological study of cells and tissues, providing information that can help to understand pathological changes. In our experience, fractal analysis has been able to produce important data on the differential diagnosis in the patient. Here we report new data on the fractal analysis of the bone marrow in myelodysplastic syndromes, a group of hematologic neoplasms characterized by morphological dysplasia, aberrant hematopoiesis, peripheral blood refractory cytopenia, with an increased risk of transformation to acute myeloid leukemia. Ninety cases of Myelodysplastic Syndromes, 20 samples of normal bone marrow, 16 cases of benign hyperplastic bone marrow and 9 cases of acute myeloid leukemia (AML) were studied. In myelodysplastic syndromes, fractal dimension is statistically increased compared with the normal condition, and, moreover, it increases with the severity of the lesion. Statistically, four classes arise. Healthy bone marrow, D = 1.72 ± 0.08, “hyperplasia” and “refractory anemia”, D = 1.79 ± 0.08,” refractory anemia with excess blasts- 1” and “refractory anemia with excess blasts -2”, D = 1.86 ± 0.08 and a fourth group, which represents the most severe condition (HIV-related myelodysplastic syndrome, chronic myelomonocytic leukemia and acute myeloid leukemia), with D = 1.95 ± 0.05, i.e. the complete loss of the diffusion limited aggregation structure that characterizes the normal bone marrow. Fractal analysis appears to be able to add objective information relating to the differential diagnosis in myelodysplastic syndromes
Entropy Evaluation of Bone Marrow Biopsies in Myelodysplastic Syndromes
No full textNew data on fractal analysis of the bone marrow in myelodysplastic syndromes are
recently arising in order to perform differential diagnosis and prognosis in those diseases.
Here we report the use of Entropy, or Information Dimension, to evaluate bone marrow biopsies in healthy subjects, in refractory anemia, in refractory anemia with excess blasts (-1 & -2) and in acute myeloid leukemia. Entropy is statistically increased in the patients compared with the normal condition (p < 0.01). Interestingly, entropy increases with the severity of the lesions (p < 0.01). Evaluation of Entropy of the histologic images appears to be able to add objective information relating to the differential diagnosis in myelodysplastic syndromes
Differential diagnosis between mycosis fungoides and chronic dermatitis by fractal analysis
No full textIn this study we compared the diagnostic power
of NCI to that of fractal geometry applied, at
transmission electron microscopy level, as a tool to
analyze the nuclear contour of lymphoid cells.
The resulting mean D was always greater than
the topological dimension (P<0.001) and the
coefficient of determination of the linear fits had
R2 value >0.95, showing the fractal approach
appropriated (the mean ranges of scales for which
linear log-log plot were found were between 100
and 700 nm). Both D and NCI were found to be
significantly higher in MF (D=1.21+0.03; median
=1.22; range 1.16-1.28 NCI=7.6+0.6; median
=7.4; range 6.7-8.2) than in CD (D=1.11+
0.02: median=1.11; range 1.05-1.14; NCI=
6.1+0.4; median=5.8; range 5.6-7.3) (Fig. 2,
P<0.001). D significantly differed between nuclei
showing NCI<7 (D=1.09+0.02, #=705) and
nuclei with NCI>7 (D=1.19+0.02; #=520)
(P<0.001). A significant positive correlation was
found between D and NCI (r=0.75, P<0.001).
The variance of D values was three times lower
than that of NCI values (MF: 2.5 vs. 8%; CD: 1.9 vs.
6.9%, PB/0.01, PB/0.01, respectively).
We suggest that fractal analysis could be an
additional tool in the challenging differential
diagnosis between benign dermatitis and early
stage MF
Fractal analysis of epithelial-connective tissue interface in basal cell carcinoma of the skin
No full textThis paper investigates the use of computerized fractal analysis for objective characterization of the complexity of the epithelial-connective tissue interface in basal cell carcinoma and the ability of the technique to quantitatively discriminate among different diagnostic categories. Tumor boundaries were extracted by means of image analysis. The fractal dimension was calculated by using the box-counting method. The results showed that the shape of the boundaries between epithelium and stroma is significantly more complex in infiltrative high risk tumors than in circumscribed low risk ones (p<0.001), with 100% correct classifications. This study shows that the computerized fractal analysis of epithelial-connective tissue interface in basal cell carcinomas can provide an accurate, quantitative, inexpensive technique to help in tumor diagnosis
Metodo per la valutazione di parametri quantitativi dei globuli rossi su strisci di sangue periferico
No full textFractal dimension of epithelial-connective tissue interface in basal cell carcinoma of the skin
No full textAnalisi quantitativa del DNA nei carcinomi della mammella. Una comparazione tra analisi d'immagine e citometria a flusso
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
- …
