Search Results (4)

Cutaneous squamous cell carcinoma (cSCC) is the second-most-prevalent malignancy in humans. A delayed diagnosis of cSCC leads to heightened invasiveness and positive surgical margins. Bowen’s disease (BD) represents an early form of cSCC and presents as a small erythematous, photo-distributed, psoriasiform plaque. Although certain dermoscopy features in BD are quite characteristic, histopathology remains the gold standard for diagnosis and provides a severity-scoring system that assists in guiding appropriate treatment strategies. The classification of precancerous lesions of the vulva and penis has undergone multifarious transformations due to variations in clinical and histopathological characteristics. Presently, erythroplasia of Queyrat is categorized as a clinical variant of penile intraepithelial neoplasia (PeIN). The diagnoses of vulvar intraepithelial neoplasia (VIN) and PeIN present significant challenges and typically necessitate one or more biopsies, potentially guided by dermoscopy. Aceto-white testing demonstrates a notably high negative predictive value for genital precancerous lesions. Histopathological examination represents the gold-standard diagnosis in VIN and PeIN, while p16 and p53 immunostainings alongside HPV testing provide crucial diagnostic clues. The histopathologic features, degree of differentiation, and associations with lichen planus, lichen sclerosus, and HPV guide the selection of conservative treatments or surgical excision. Full article

Colposcopy is an essential examination tool to identify cervical intraepithelial neoplasia (CIN), a precancerous lesion of the uterine cervix, and to sample its tissues for histological examination. In colposcopy, gynecologists visually identify the lesion highlighted by applying an acetic acid solution to the cervix using a magnifying glass. This paper proposes a deep learning method to aid the colposcopic diagnosis of CIN by segmenting lesions. In this method, to segment the lesion effectively, the colposcopic images taken before acetic acid solution application were input to the deep learning network, U-Net, for lesion segmentation with the images taken following acetic acid solution application. We conducted experiments using 30 actual colposcopic images of acetowhite epithelium, one of the representative types of CIN. As a result, it was confirmed that accuracy, precision, and F1 scores, which were 0.894, 0.837, and 0.834, respectively, were significantly better when images taken before and after acetic acid solution application were used than when only images taken after acetic acid solution application were used (0.882, 0.823, and 0.823, respectively). This result indicates that the image taken before acetic acid solution application is helpful for accurately segmenting the CIN in deep learning. Full article

Precancerous screening using visual inspection with acetic acid (VIA) is suggested by the World Health Organization (WHO) for low–middle-income countries (LMICs). However, because of the limited number of gynecological oncologist clinicians in LMICs, VIA screening is primarily performed by general clinicians, nurses, or midwives (called medical workers). However, not being able to recognize the significant pathophysiology of human papilloma virus (HPV) infection in terms of the columnar epithelial-cell, squamous epithelial-cell, and white-spot regions with abnormal blood vessels may be further aggravated by VIA screening, which achieves a wide range of sensitivity (49–98%) and specificity (75–91%); this might lead to a false result and high interobserver variances. Hence, the automated detection of the columnar area (CA), subepithelial region of the squamocolumnar junction (SCJ), and acetowhite (AW) lesions is needed to support an accurate diagnosis. This study proposes a mask-RCNN architecture to simultaneously segment, classify, and detect CA and AW lesions. We conducted several experiments using 262 images of VIA+ cervicograms, and 222 images of VIA−cervicograms. The proposed model provided a satisfactory intersection over union performance for the CA of about 63.60%, and AW lesions of about 73.98%. The dice similarity coefficient performance was about 75.67% for the CA and about 80.49% for the AW lesion. It also performed well in cervical-cancer precursor-lesion detection, with a mean average precision of about 86.90% for the CA and of about 100% for the AW lesion, while also achieving 100% sensitivity and 92% specificity. Our proposed model with the instance segmentation approach can segment, detect, and classify cervical-cancer precursor lesions with satisfying performance only from a VIA cervicogram. Full article

Applying Lugol’s iodine solution to the cervix followed by colposcopic assessment is an established standard test to identify low grade/high grade squamous intraepithelial lesions (LSIL/HSIL). Here, we assessed the performance of Lugol’s iodine test during colposcopy using a standardized protocol with 5% acetic acid followed by 5% Lugol’s iodine solution and recording the most severe acetowhite (MSAWL) and iodine-negative (MSINL) lesions in a prospective cohort of consecutive women referred to our specialized colposcopy unit. The primary study endpoint was the sensitivity/specificity of MSINL for the detection of LSIL/HSIL. Secondary endpoints were the time to first appearance of the MSINL, MSINL staining intensity, and fading of MSINL. Three hundred and twenty women were included. The sensitivity and specificity of MSINL for the detection of LSIL/HSIL was 81.4 (95%—confidence interval (CI) 77.3–85.0)% and 29.5 (24.2–35.5)%, respectively. Ninety-six MSINL were identified exclusively by Lugol’s iodine test (no pathology, n = 46; LSIL, n = 29; HSIL, n = 21) (number needed to biopsy to identify one additional LSIL/HSIL = 1.9). In 17/320 (5.3%) patients, the clinical management was changed based on the result of Lugol’s iodine test. Video analysis showed an instant appearance of the MSINL within 10 s in 100% of cases. Intensity of MSINL significantly correlated with the presence/absence of LSIL/HSIL (Spearman rank order correlation; p < 0.0001). Fading of iodine-induced staining intensity over time was not observed. Thus, Lugol’s iodine showed moderate sensitivity and poor specificity, but changed clinical management in 5% of cases when used in addition to acetic acid. Full article