Prostate mechanical imaging: a new method for prostate assessment

OBJECTIVES: To evaluate the ability of prostate mechanical imaging (PMI) technology to provide an objective and reproducible image and to assess the prostate nodularity. METHODS: We evaluated the PMI device developed by Artann Laboratories in a pilot clinical study. For the 168 patients (ages 44 to 94) who presented to an urologist for prostate evaluation, PMI-produced images and assessment of prostate size, shape, consistency/hardness, mobility, and nodularity were compared with digital rectal examination (DRE) findings. The PMI and DRE results were further tested for correlation against a transrectal ultrasound of the prostate (TRUS) guided biopsy for a subgroup of 21 patients with an elevated prostate-specific antigen level. RESULTS: In 84% of the cases, the PMI device was able to reconstruct three-dimensional (3D) and 2D cross-sectional images of the prostate. The PMI System and DRE pretests were able to determine malignant nodules in 10 and 6 patients, respectively, of the 13 patients with biopsy-confirmed malignant inclusions. The PMI System findings were consistent with all 8 biopsy negative cases, whereas the DRE had 1 abnormal reading for this group. The correlation between PMI and DRE detection of palpable nodularity was 81%, as indicated by the area under the receiver operating characteristic curve. Estimates of the prostate size provided by PMI and DRE were statistically significantly correlated. CONCLUSIONS: The PMI has the potential to enable a physician to obtain, examine, and store a 3D image of the prostate based on mechanical and geometrical characteristics of the gland and its internal structures

Differentiation of benign and malignant breast lesions by mechanical imaging.

Mechanical imaging yields tissue elasticity map and provides quantitative characterization of a detected pathology. The changes in the surface stress patterns as a function of applied load provide information about the elastic composition and geometry of the underlying tissue structures. The objective of this study is the clinical evaluation of breast mechanical imager for breast lesion characterization and differentiation between benign and malignant lesions. The breast mechanical imager includes a probe with pressure sensor array, an electronic unit providing data acquisition from the pressure sensors and communication with a touch-screen laptop computer. We have developed an examination procedure and algorithms to provide assessment of breast lesion features such as hardness related parameters, mobility, and shape. A statistical Bayesian classifier was constructed to distinguish between benign and malignant lesions by utilizing all the listed features as the input. Clinical results for 179 cases, collected at four different clinical sites, have demonstrated that the breast mechanical imager provides a reliable image formation of breast tissue abnormalities and calculation of lesion features. Malignant breast lesions (histologically confirmed) demonstrated increased hardness and strain hardening as well as decreased mobility and longer boundary length in comparison with benign lesions. Statistical analysis of differentiation capability for 147 benign and 32 malignant lesions revealed an average sensitivity of 91.4% and specificity of 86.8% with a standard deviation of +/-6.1%. The area under the receiver operating characteristic curve characterizing benign and malignant lesion discrimination is 86.1% with the confidence interval ranging from 80.3 to 90.9%, with a significance level of P = 0.0001 (area = 50%). The multisite clinical study demonstrated the capability of mechanical imaging for characterization and differentiation of benign and malignant breast lesions. We hypothesize that the breast mechanical imager has the potential to be used as a cost effective device for cancer diagnostics that could reduce the benign biopsy rate, serve as an adjunct to mammography and to be utilized as a screening device for breast cancer detection

Quantitative Assessment and Interpretation of Vaginal Conditions

Introduction: Few means exist to provide quantitative and reproducible assessment of vaginal conditions from biomechanical and functional standpoints. Aim: To develop a new approach for quantitative biomechanical characterization of the vagina. Methods: Vaginal tactile imaging (VTI) allows biomechanical assessment of soft tissue and function along the entire length of the anterior, posterior, and lateral vaginal walls. This can be done at rest, with applied vaginal deformation, and with pelvic muscle contraction. Results: Data were analyzed for 42 subjects with normal pelvic floor support from an observational case-controlled clinical study. The average age was 52 years (range = 26–90 years). We introduced 8 VTI parameters to characterize vaginal conditions: (i) maximum resistance force to insertion (newtons), (ii) insertion work (millijoules), (iii) maximum stress-to-strain ratio (elasticity; kilopascals per millimeter), (iv) maximum pressure at rest (kilopascals), (v) anterior-posterior force at rest (newtons), (vi) left-right force at rest (newtons), (vii) maximum pressure at muscle contraction (kilopascals), and (viii) muscle contraction force (newtons). We observed low to moderate correlation of these parameters with subject age and no correlation with subject weight. 6 of 8 parameters demonstrated a P value less than .05 for 2 subject subsamples divided by age (≤52 vs >52 years), which means 6 VTI parameters change with age. Conclusions: VTI allows biomechanical and functional characterization of the vaginal conditions that can be used for (i) understanding “normal” vaginal conditions, (ii) quantification of the deviation from normality, (iii) personalized treatment (radiofrequency, laser, or plastic surgery), and (iv) assessment of the applied treatment outcome. Egorov V, Murphy M, Lucente V, et al. Quantitative Assessment and Interpretation of Vaginal Conditions. Sex Med 2018;6:39–48

Modeling and in vitro experimental validation for kinetics of the colonoscope in colonoscopy

Colonoscopy is the most sensitive and specific means for detection of colon cancers and polyps. To make colonoscopy more effective several problems must be overcome including: pain associated with the procedure, the risk of perforation, and incomplete intubation colonoscopy. Technically, these problems are the result of loop formation during colonoscopy. Although, several solutions such as modifying the stiffness of the colonoscope, using an overtube and developing image-guided instruments have been introduced to resolve the looping problem, the results of these systems are not completely satisfactory. A new paradigm to overcome loop formation is proposed that is doctor-assistive colonoscopy. In this approach, the endoscopists performance is enhanced by providing using a kinetic model that provides information such as the shape of the scope, direction of the colon and forces exerted within certain sections. It is expected that with the help of this model, the endoscopist would be able to adjust the manipulation to avoid loop formation. In the present studies, the kinetic model is developed and validated using an ex vivo colonoscopy test-bed with a comprehensive kinematic and kinetic data collection. The model utilizes an established colon model based on animal tissue with position tracking sensors, contact force sensors for the intraluminal portion of the scope and a Colonoscopy Force Monitor for the external insertion tube