Dataset Information

Stereophotogrammetric three-dimensional photography is an accurate and precise planimetric method for the clinical visualization and quantification of human papilloma virus-induced skin lesions.

ABSTRACT: BACKGROUND:The quantification of human papilloma virus (HPV)-induced skin lesions is essential for the clinical assessment of the course of disease and the response to treatment. However, clinical assessments that measure dimensions of lesions using a caliper do not provide complete insight into three-dimensional (3D) lesions, and its inter-rater variability is often poor. OBJECTIVE:The aim of this study was to validate a stereophotogrammetric 3D camera system for the quantification of HPV-induced lesions. METHODS:The camera system was validated for accuracy, precision and interoperator and inter-rater variability. Subsequently, 3D photographs were quantified and compared to caliper measurements for clinical validation by Bland-Altman modelling, based on data from 80 patients with cutaneous warts (CW), 24 with anogenital warts (AGW) patients and 12 with high-grade squamous intraepithelial lesions of the vulva (vulvar HSIL) with a total lesion count of 220 CW, 74 AGW and 31 vulvar HSIL. RESULTS:Technical validation showed excellent accuracy [coefficients of variation (CV) ? 0.68%] and reproducibility (CVs ? 2%), a good to excellent agreement between operators (CVs ? 8.7%) and a good to excellent agreement between different raters for all three lesion types (ICCs ? 0.86). When comparing 3D with caliper measurements, excellent biases were found for diameter of AGW (long diameter 5%), good biases were found for diameter of AGW (short diameter 10%) and height of CW (8%), and acceptable biases were found for the diameter of CW (11%) and vulvar HSIL (short diameter 14%, long diameter 16%). An unfavourable difference between these methods (bias 25%) was found for the assessment of height of AGWs. CONCLUSION:Stereophotogrammetric 3D imaging is an accurate and reliable method for the clinical visualization and quantification of HPV-induced skin lesions.

SUBMITTER: Rijsbergen M

PROVIDER: S-EPMC6767777 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Stereophotogrammetric three-dimensional photography is an accurate and precise planimetric method for the clinical visualization and quantification of human papilloma virus-induced skin lesions.

Rijsbergen M M Pagan L L Niemeyer-van der Kolk T T Rijneveld R R Hogendoorn G G Lemoine C C Meija Miranda Y Y Feiss G G Bouwes Bavink J N JN Burggraaf J J van Poelgeest M I E MIE Rissmann R R

Journal of the European Academy of Dermatology and Venereology : JEADV 20190312 8

<h4>Background</h4>The quantification of human papilloma virus (HPV)-induced skin lesions is essential for the clinical assessment of the course of disease and the response to treatment. However, clinical assessments that measure dimensions of lesions using a caliper do not provide complete insight into three-dimensional (3D) lesions, and its inter-rater variability is often poor.<h4>Objective</h4>The aim of this study was to validate a stereophotogrammetric 3D camera system for the quantificati ...[more]

PMID: 30720900

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Project description:BackgroundComputer-aided diagnosis (CADx) software that provides a second opinion has been widely used to assist physicians with various tasks. In dermatology, however, CADx has been mostly limited to melanoma or melanocytic skin cancer diagnosis. The frequency of non-melanocytic skin cancers and the accessibility of regular digital macrographs have raised interest in developing CADx for broader applications.ObjectivesTo investigate the feasibility of using CADx to diagnose both melanocytic and non-melanocytic skin lesions based on conventional digital photographic images.MethodsThis study was approved by an institutional review board, and the requirement to obtain informed consent was waived. In total, 769 conventional photographs of melanocytic and non-melanocytic skin lesions were retrospectively reviewed and used to develop a CADx system. Conventional and new color-related image features were developed to classify the lesions as benign or malignant using support vector machines (SVMs). The performance of CADx was compared with that of dermatologists.ResultsThe clinicians' overall sensitivity, specificity, and accuracy were 83.33%, 85.88%, and 85.31%, respectively. New color correlation and principal component analysis (PCA) features improved the classification ability of the baseline CADx (p = 0.001). The estimated area under the receiver operating characteristic (ROC) curve (Az) of the proposed CADx system was 0.949, with a sensitivity and specificity of 85.63% and 87.65%, respectively, and a maximum accuracy of 90.64%.ConclusionsWe have developed an effective CADx system to classify both melanocytic and non-melanocytic skin lesions using conventional digital macrographs. The system's performance was similar to that of dermatologists at our institute. Through improved feature extraction and SVM analysis, we found that conventional digital macrographs were feasible for providing useful information for CADx applications. The new color-related features significantly improved CADx applications for skin cancer.

Project description:BackgroundMass spectrometry based quantification of peptides can be performed using the iTRAQ reagent in conjunction with mass spectrometry. This technology yields information about the relative abundance of single peptides. A method for the calculation of reliable quantification information is required in order to obtain biologically relevant data at the protein expression level.ResultsA method comprising sound error estimation and statistical methods is presented that allows precise abundance analysis plus error calculation at the peptide as well as at the protein level. This yields the relevant information that is required for quantitative proteomics. Comparing the performance of our method named Quant with existing approaches the error estimation is reliable and offers information for precise bioinformatic models. Quant is shown to generate results that are consistent with those produced by ProQuant, thus validating both systems. Moreover, the results are consistent with that of Mascot 2.2. The MATLAB scripts of Quant are freely available via http://www.protein-ms.de and http://sourceforge.net/projects/protms/, each under the GNU Lesser General Public License.ConclusionThe software Quant demonstrates improvements in protein quantification using iTRAQ. Precise quantification data can be obtained at the protein level when using error propagation and adequate visualization. Quant integrates both and additionally provides the possibility to obtain more reliable results by calculation of wise quality measures. Peak area integration has been replaced by sum of intensities, yielding more reliable quantification results. Additionally, Quant allows the combination of quantitative information obtained by iTRAQ with peptide and protein identifications from popular tandem MS identification tools. Hence Quant is a useful tool for the proteomics community and may help improving analysis of proteomic experimental data. In addition, we have shown that a lognormal distribution fits the data of mass spectrometry based relative peptide quantification.

Dataset Information

Stereophotogrammetric three-dimensional photography is an accurate and precise planimetric method for the clinical visualization and quantification of human papilloma virus-induced skin lesions.

Publications

Stereophotogrammetric three-dimensional photography is an accurate and precise planimetric method for the clinical visualization and quantification of human papilloma virus-induced skin lesions.

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