Biomedical subjects

Roberto Perotti

Publications and source records attributed to Roberto Perotti.

6 recordsLinked to original sources

PubMed2004

Melanoma computer-aided diagnosis: reliability and feasibility study.

BACKGROUND: Differential diagnosis of melanoma from melanocytic nevi is often not straightforward. Thus, a growing interest has developed in the last decade in the automated analysis of digitized images obtained by epiluminescence microscopy techniques to assist clinicians in differentiating early melanoma from benign skin lesions. PURPOSE: The aim of this study was to evaluate diagnostic accuracy provided by different statistical classifiers on a large set of pigmented skin lesions grabbed by four digital analyzers located in two different dermatological units. EXPERIMENTAL DESIGN: Images of 391 melanomas and 449 melanocytic nevi were included in the study. A linear classifier was built by using the method of receiver operating characteristic curves to identify a threshold value for a fixed sensitivity of 95%. A K-nearest-neighbor classifier, a nonparametric method of pattern recognition, was constructed using all available image features and trained for a sensitivity of 98% on a large exemplar set of lesions. RESULTS: On independent test sets of lesions, the linear classifier and the K-nearest-neighbor classifier produced a mean sensitivity of 95% and 98% and a mean specificity of 78% and of 79%, respectively. CONCLUSIONS: In conclusion, our study suggests that computer-aided differentiation of melanoma from benign pigmented lesions obtained with DB-Mips is feasible and, above all, reliable. In fact, the same instrumentations used in different units provided similar diagnostic accuracy. Whether this would improve early diagnosis of melanoma and/or reducing unnecessary surgery needs to be demonstrated by a randomized clinical trial.

Diagnosis, Computer-Assisted↗

PubMed2003

Dermoscopy of pigmented skin lesions: results of a consensus meeting via the Internet.

BACKGROUND: There is a need for better standardization of the dermoscopic terminology in assessing pigmented skin lesions. OBJECTIVE: The virtual Consensus Net Meeting on Dermoscopy was organized to investigate reproducibility and validity of the various features and diagnostic algorithms. METHODS: Dermoscopic images of 108 lesions were evaluated via the Internet by 40 experienced dermoscopists using a 2-step diagnostic procedure. The first-step algorithm distinguished melanocytic versus nonmelanocytic lesions. The second step in the diagnostic procedure used 4 algorithms (pattern analysis, ABCD rule, Menzies method, and 7-point checklist) to distinguish melanoma versus benign melanocytic lesions. kappa Values, log odds ratios, sensitivity, specificity, and positive likelihood ratios were estimated for all diagnostic algorithms and dermoscopic features. RESULTS: Interobserver agreement was fair to good for all diagnostic methods, but it was poor for the majority of dermoscopic criteria. Intraobserver agreement was good to excellent for all algorithms and features considered. Pattern analysis allowed the best diagnostic performance (positive likelihood ratio: 5.1), whereas alternative algorithms revealed comparable sensitivity but less specificity. Interobserver agreement on management decisions made by dermoscopy was fairly good (mean kappa value: 0.53). CONCLUSION: The virtual Consensus Net Meeting on Dermoscopy represents a valid tool for better standardization of the dermoscopic terminology and, moreover, opens up a new territory for diagnosing and managing pigmented skin lesions.

Algorithms↗

PubMed2002

Automated diagnosis of pigmented skin lesions.

Since advanced melanoma remains practically incurable, early detection is an important step toward a reduction in mortality. High expectations are entertained for a technique known as dermoscopy or epiluminescence light microscopy; however, evaluation of pigmented skin lesions by this method is often extremely complex and subjective. To obviate the problem of qualitative interpretation, methods based on mathematical analysis of pigmented skin lesions, such as digital dermoscopy analysis, have been developed. In the present study, we used a digital dermoscopy analyzer (DBDermo-Mips system) to evaluate a series of 588 excised, clinically atypical, flat pigmented skin lesions (371 benign, 217 malignant). The analyzer evaluated 48 parameters grouped into 4 categories (geometries, colors, textures and islands of color), which were used to train an artificial neural network. To evaluate the diagnostic performance of the neural network and to check it during the training process, we used the error area over the receiver operating characteristic curve. The discriminating power of the digital dermoscopy analyzer plus artificial neural network was compared with histologic diagnosis. A feature selection procedure indicated that as few as 13 of the variables were sufficient to discriminate the 2 groups of lesions, and this also ensured high generalization power. The artificial neural network designed with these variables enabled a diagnostic accuracy of about 94%. In conclusion, the good diagnostic performance and high speed in reading and analyzing lesions (real time) of our method constitute an important step in the direction of automated diagnosis of pigmented skin lesions.

Automation↗

PubMed2002

Digital dermoscopy analysis and artificial neural network for the differentiation of clinically atypical pigmented skin lesions: a retrospective study.

Noninvasive diagnostic methods such as dermoscopy or epiluminescence light microscopy have been developed in an attempt to improve diagnostic accuracy of pigmented skin lesions. The evaluation of the many morphologic characteristics of pigmented skin lesions observable by epiluminescence light microscopy, however, is often extremely complex and subjective. With the aim of obviating these problems of qualitative interpretation, methods based on mathematical analysis of pigmented skin lesions have recently been designed. These methods are based on computerized analysis of digital images obtained by epiluminescence light microscopy. In this study we used a digital dermoscopy analyzer with 147 clinically atypical pigmented skin lesions (90 nevi and 57 melanomas) to determine its discriminating power with respect to histologic diagnosis. The system evaluated 48 objective parameters used to train an artificial neural network. Using the artificial neural network with 10 variables selected by a stepwise procedure, we obtained a maximum accuracy in distinguishing melanoma from benign lesions of about 93%. Comparing this result with those of the many studies using classical epiluminescence light microscopy, it emerges that the method proposed is equal or even superior in diagnostic accuracy and has the advantage of not depending on the expertise of the clinician who examines the lesion.

Humans↗

PubMed2002

Skin allograft in the treatment of toxic epidermal necrolysis (TEN).

BACKGROUND: TEN is a severe form of exfoliative dermatitis. Its course is acute and its outcome fatal in 40% of cases. Wound cover to prevent fluid/protein loss and infections and to control pain, is the first step, as for burns. Skin allograft can be successfully used for this purpose. OBJECTIVE: We report two cases of TEN with de-epithelialization of 50 and 70% of the total body surface area. The patients were given support therapy and treated with human glycerol-preserved skin allografts for wound cover. METHODS: Patients were grafted with glycerol-preserved donor skin, obtained from a skin bank. RESULTS: Re-epithelization of treated areas was complete in 8 days; pain relief was obtained soon after the graft. CONCLUSIONS: Glycerol-preserved skin allograft is an effective treatment in extensive skin loss, for its barrier and analgesic effect. Quality standards of this product ensure safety and simplicity of use at limited cost.

Aged↗

PubMedDate not supplied

Dimensional contour stability of acrylic resin bases for complete dentures before and after water sorption.

PURPOSE: To evaluate the dimensional contour variations of acrylic resin denture bases before and after storage in water. MATERIALS AND METHODS: The fit of 40 bases was evaluated by measuring the thickness of a layer made with silicone placed between the bases and the casts. The measurements were repeated on a new set of silicone layers after having stored the bases in water for 42 days. RESULTS: Significant differences were found both for the maxillary and the mandibular bases. CONCLUSION: Water sorption had an important effect on the contour of the prosthetic bases.

Absorption↗