Measuring Surface Area of Skin Lesions with 2D and 3D Algorithms

Extraction of Ruler Markings For Estimating Physical Size of Oral Lesions

Small ruler tapes are commonly placed on the surface of the human body as a simple and efficient reference for capturing on images the physical size of a lesion. In this paper, we describe our proposed approach for automatically extracting the measurement information from a ruler in oral cavity images which are taken during oral cancer screening and follow up. The images were taken during a study that aims to investigate the natural history of histologically defined oral cancer precursor lesions and identify epidemiologic factors and molecular markers associated with disease progression. Compared to similar work in the literature proposed for other applications where images are captured with greater consistency and in more controlled situations, we address additional challenges that our application faces in real world use and with analysis of retrospectively collected data. Our approach considers several conditions with respect to ruler style, ruler visibility completeness, and image quality. Further, we provide multiple ways of extracting ruler markings and measurement calculation based on specific conditions. We evaluated the proposed method on two datasets obtained from different sources and examined cross-dataset performance.

Digital Planimetry With a New Adaptive Calibration Procedure Results in Accurate and Precise Wound Area Measurement at Curved Surfaces

BACKGROUND

The purpose of this study was to determine the accuracy of wound area measurement at a curved surface using a digital planimetry (DP) with the newly proposed adaptive calibration.

METHODS

Forty wound shapes were printed and placed at the side surfaces of cylinders with diameters of 9.4 and 6.2 cm. Area measurements were carried out using a commercial device SilhouetteMobile (Aranz, New Zealand) and the planimetric app Planimator. Planimetric area measurements were carried out using 2 one-dimensional calibration markers placed above and below the wound shape. The method of adaptive calibration for DP was described. Reference area values of wound shapes were obtained by pixel counting on digital scans made with an optical scanner. Relative errors (REs) and relative differences (RDs) for area measurements were analyzed.

RESULTS

The median of REs for the DP with adaptive calibration (DPwAC) was equal to 0.60% and was significantly smaller than the median for the SilhouetteMobile device (SMD) (2.65%), and significantly smaller than the median for the DP (2.23%). The SD of RDs for the DPwAC of 0.87% was considerably lower than for the SMD (6.45%), and for the DP without adaptive calibration (2.51%). The mean of RDs for the DPwAC (0.082%) was not significantly different from zero, which means that the systematic error was not present for the DPwAC.

CONCLUSIONS

The use of the adaptive calibration in DP to measure the areas at curved surface resulted in a significant increase of accuracy and precision, and removal of systematic error. The DPwAC revealed 4.4 times lower error and 7.4 times higher precision of area measurement at curved surfaces than the SMD.

Translation of Pharmacodynamic Biomarkers of Antibiotic Efficacy in Specific Populations to Optimize Doses

Antibiotic efficacy determination in clinical trials often relies on non-inferiority designs because they afford smaller study sample sizes. These efficacy studies tend to exclude patients within specific populations or include too few patients to discern potential differences in their clinical outcomes. As a result, dosing guidance in patients with abnormal liver and kidney function, age across the lifespan, and other specific populations relies on drug exposure-matching. The underlying assumption for exposure-matching is that the disease course and the response to the antibiotic are similar in patients with and without the specific condition. While this may not be the case, clinical efficacy studies are underpowered to ensure this is true. The current paper provides an integrative review of the current approach to dose selection in specific populations. We review existing clinical trial endpoints that could be measured on a more continuous rather than a discrete scale to better inform exposure-response relationships. The inclusion of newer systemic biomarkers of efficacy can help overcome the current limitations. We use a modeling and simulation exercise to illustrate how an efficacy biomarker can inform dose selection better. Studies that inform response-matching rather than exposure-matching only are needed to improve dose selection in specific populations.

SfM-3DULC: Reliability of a new 3D wound measurement procedure and its accuracy in projected area

Three‐dimensional (3D) wound measurement lacks a gold standard to test accuracy. It is useful to develop procedures to scan wounds and reconstruct their 3D model with low‐cost techniques. We present a new procedure (Structure from Motion [SfM]‐3DULC) that uses photographs for measuring nine wound variables. We also propose a new variant of ImageJ in which an orthophoto is used to measure the projected area (Ortho‐ImageJ). In addition, we compare the wound measurements made by dermatologists and non‐experts. A group of five experts in dermatology and five non‐specialists measured 33 leg wounds five times per procedure. Intra‐rater and inter‐rater reliability scores of SfM‐3DULC were evaluated with the intraclass correlation coefficient (ICC 2,1). The accuracy of the two new procedures (SfM‐3DULC and Ortho‐ImageJ) in the measurement of projected area was assessed by comparing their values with those obtained using ImageJ, with the Wilcoxon matched‐pairs signed rank test (α = 0.05). This test was also used to analyse the differences between the measurements made by dermatologists and non‐experts. All the variables measured by dermatologists using SfM‐3DULC showed excellent scores of intra‐rater reliability (ICC > 0.99) and inter‐rater reliability (ICC > 0.98). No significant differences between the three procedures were found when comparing their projected area values. Significant differences between the measurements of dermatologists and non‐experts were found in most of the variables: circularity coefficient, perimeter, projected area, surface area, and reference surface area. The wound measurement procedure SfM‐3DULC has an excellent reliability, is accurate for the measurement of projected area, and can be used by dermatologists for wound monitoring in everyday clinical practice.

The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine

Chronic dermatological ulcers cause great discomfort to patients, and while monitoring the size of wounds over time provides significant clues about the healing evolution and the clinical condition of patients, the lack of practical applications in existing studies impairs users' access to appropriate treatment and diagnosis methods. We propose the UTrack framework to help with the acquisition of photos, the segmentation and measurement of wounds, the storage of photos and symptoms, and the visualization of the evolution of ulcer healing. UTrack-App is a mobile app for the framework, which processes images taken by standard mobile device cameras without specialized equipment and stores all data locally. The user manually delineates the regions of the wound and the measurement object, and the tool uses the proposed UTrack-Seg segmentation method to segment them. UTrack-App also allows users to manually input a unit of measurement (centimeter or inch) in the image to improve the wound area estimation. Experiments show that UTrack-Seg outperforms its state-of-the-art competitors in ulcer segmentation tasks, improving F-Measure by up to 82.5% when compared to superpixel-based approaches and up to 19% when compared to Deep Learning ones. The method is unsupervised, and it semi-automatically segments real-world images with 0.9 of F-Measure, on average. The automatic measurement outperformed the manual process in three out of five different rulers. UTrack-App takes at most 30 s to perform all evaluation steps over high-resolution images, thus being well-suited to analyze ulcers using standard mobile devices.

Measurement of wound area for early analysis of the scar predictive factor

Objective:

to evaluate the use of the 2D-FlexRuler as a facilitating tool for the early calculation of the predictive scar factor of chronic wounds.

Method:

a descriptive study with a quantitative, experimental, longitudinal and prospective approach. The sample consisted of 22 outpatients. 32 chronic wounds were analyzed. The wound edges were identified and drawn on the 2D-FlexRuler. The calculations of the areas of chronic wounds were obtained by manual, traditional methods, by software and Matlab algorithm. These areas were compared with each other to determine the efficiency of the proposed ruler in relation to traditional methods.

Results:

the calculation of the wound area by the traditional method and Kundin’s coefficient show average errors greater than 40%. The manual estimation of the area with the 2D-FlexRuler is more accurate in relation to traditional measurement methods, which were considered quantitatively disqualified. When compared with the reference method, for example, the Klonk software, the data obtained by 2D-FlexRuler resulted in an error of less than 1.0%.

Conclusion:

the 2D-FlexRuler is a reliable metric platform for obtaining the anatomical limits of chronic wounds. It facilitated the calculation of the wound area under monitoring and allowed to obtain the scar predictive factor of chronic wounds with precocity in two weeks.