Granular cell tumor in the scrotum of a pediatric patient: A case report of a rare clinical entity.

Granular cell tumors are rare tumors of Schwann cell origin that present in any anatomic location, age or sex. We present a case of a granular cell tumor in the scrotum of a prepubescent male. The tumor was excised, with histology revealing abundant eosinophilic cytoplasm and positive S-100 staining. No stigmata of malignancy were identified and no recurrence has been reported during follow-up.

Polygenic early-onset colorectal cancer in pediatric patients.

Colorectal cancer in the pediatric population is a rare but transpirable phenomenon. The occurrence should prompt suspicion for underlying genetic mutations in the setting of a hereditary cancer predisposition syndrome. In this series, we outline three pediatric patients with colonic adenocarcinoma who were found to have one or more germline mutations. The presence of compound mutations may lead to a hypermutator phenotype resulting in earlier presentation of colorectal cancer in childhood and adolescence. The diagnosis of colorectal cancer in pediatric patients warrants timely recognition, multigene panel testing, genetic counseling for the patient and family, and increased surveillance for intestinal and extra-intestinal tumors.

Correlation of histopathology and multi-modal magnetic resonance imaging in childhood osteosarcoma: Predicting tumor response to chemotherapy.

BACKGROUND: Osteosarcoma, which is the most common malignant pediatric bone cancer, remains dependent on an imprecise systemic treatment largely unchanged in 30 years. In this study, we correlated histopathology with magnetic resonance imaging (MRI), used the correlation to extract MRI-specific features representative of tumor necrosis, and subsequently developed a novel classification model for predicting tumor response to neoadjuvant chemotherapy in pediatric patients with osteosarcoma using multi-modal MRI. The model could ultimately serve as a testable biomarker for a high-risk malignancy without successful precision treatments. METHODS: Patients with newly diagnosed high-grade appendicular osteosarcoma were enrolled in a single-center observational study, wherein patients underwent pre-surgical evaluation using both conventional MRI (post-contrast T1-weighted with fat saturation, pre-contrast T1-weighted, and short inversion-time inversion recovery (STIR)) and advanced MRI (diffusion weighted (DW) and dynamic contrast enhanced (DCE)). A classification model was established based on a direct correlation between histopathology and MRI, which was achieved through histologic-MR image co-registration and subsequent extraction of MR image features for identifying histologic tumor necrosis. By operating on the MR image features, tumor necrosis was estimated from different combinations of MR images using a multi-feature fuzzy clustering technique together with a weighted majority ruling. Tumor necrosis calculated from MR images, for either an MRI plane of interest or whole tumor volume, was compared to pathologist-estimated necrosis and necrosis quantified from digitized histologic section images using a previously described deep learning classification method. RESULTS: 15 patients were enrolled, of whom two withdrew, one became ineligible, and two were subjected to inadequate pre-surgical imaging. MRI sequences of n = 10 patients were subsequently used for classification model development. Different MR image features, depending on the modality of MRI, were shown to be significant in distinguishing necrosis from viable tumor. The scales at which MR image features optimally signified tumor necrosis were different as well depending on the MR image type. Conventional MRI was shown capable of differentiating necrosis from viable tumor with an accuracy averaging above 90%. Conventional MRI was equally effective as DWI in distinguishing necrotic from viable tumor regions. The accuracy of tumor necrosis prediction by conventional MRI improved to above 95% when DCE-MRI was added into consideration. Volume-based tumor necrosis estimations tended to be lower than those evaluated on an MRI plane of interest. CONCLUSIONS: The study has shown a proof-of-principle model for interpreting chemotherapeutic response using multi-modal MRI for patients with high-grade osteosarcoma. The model will continue to be evaluated as MR image features indicative of tumor response are now computable for the disease prior to surgery.

Determination of a cone-beam CT low-dose protocol for root fracture diagnosis in non-endodontically treated anterior maxillary teeth.

OBJECTIVES: The aim of this study was to determine a "low-dose protocol" which provides acceptable diagnostic accuracy for detection of root fractures in unrestored anterior maxillary teeth, using an ex vivo model. METHODS: 48 maxillary anterior teeth, half with horizontal or oblique root fractures, were imaged using CBCT in an anthropomorphic model. Nine X-ray exposure combinations were used, including the manufacturer's standard ("reference") exposure and high-resolution settings ("HiRes"), by varying kV, exposure time, and rotation angle. Measurements of Dose Area Product (DAP) were recorded. Five dental radiologists assessed the scans for root fractures and judged image quality. Parameters of diagnostic accuracy were calculated, including area under the Receiver Operating Characteristic curve (Az). Objective measures of image quality were made at the same exposure combinations using an image quality phantom. RESULTS: Although there was a significant linear relationship between DAP and mean Az, only the lowest DAP exposure combination had a mean Az significantly different to the reference exposure. There was no significant effect on other diagnostic accuracy parameters when using HiRes compared with the reference exposure. There was a significant positive relationship between DAP and contrast resolution. HiRes did not significantly improve contrast resolution and made a small improvement to spatial resolution. CONCLUSIONS: Scope existed for radiation dose reduction compared with the manufacturer's guidance. There was no improvement in diagnostic accuracy using HiRes settings. A cautious recommendation for this CBCT machine is that it is possible to achieve a dose reduction of about 20% compared with the reference exposure parameters.

Imaging modalities to inform the detection and diagnosis of early caries.

BACKGROUND: The detection and diagnosis of caries at the earliest opportunity is fundamental to the preservation of tooth tissue and maintenance of oral health. Radiographs have traditionally been used to supplement the conventional visual-tactile clinical examination. Accurate, timely detection and diagnosis of early signs of disease could afford patients the opportunity of less invasive treatment with less destruction of tooth tissue, reduce the need for treatment with aerosol-generating procedures, and potentially result in a reduced cost of care to the patient and to healthcare services. OBJECTIVES: To determine the diagnostic accuracy of different dental imaging methods to inform the detection and diagnosis of non-cavitated enamel only coronal dental caries. SEARCH METHODS: Cochrane Oral Health's Information Specialist undertook a search of the following databases: MEDLINE Ovid (1946 to 31 December 2018); Embase Ovid (1980 to 31 December 2018); US National Institutes of Health Ongoing Trials Register (ClinicalTrials.gov, to 31 December 2018); and the World Health Organization International Clinical Trials Registry Platform (to 31 December 2018). We studied reference lists as well as published systematic review articles. SELECTION CRITERIA: We included diagnostic accuracy study designs that compared a dental imaging method with a reference standard (histology, excavation, enhanced visual examination), studies that evaluated the diagnostic accuracy of single index tests, and studies that directly compared two or more index tests. Studies reporting at both the patient or tooth surface level were included. In vitro and in vivo studies were eligible for inclusion. Studies that explicitly recruited participants with more advanced lesions that were obviously into dentine or frankly cavitated were excluded. We also excluded studies that artificially created carious lesions and those that used an index test during the excavation of dental caries to ascertain the optimum depth of excavation. DATA COLLECTION AND ANALYSIS: Two review authors extracted data independently and in duplicate using a standardised data extraction form and quality assessment based on QUADAS-2 specific to the clinical context. Estimates of diagnostic accuracy were determined using the bivariate hierarchical method to produce summary points of sensitivity and specificity with 95% confidence regions. Comparative accuracy of different radiograph methods was conducted based on indirect and direct comparisons between methods. Potential sources of heterogeneity were pre-specified and explored visually and more formally through meta-regression. MAIN RESULTS: We included 104 datasets from 77 studies reporting a total of 15,518 tooth sites or surfaces. The most frequently reported imaging methods were analogue radiographs (55 datasets from 51 studies) and digital radiographs (42 datasets from 40 studies) followed by cone beam computed tomography (CBCT) (7 datasets from 7 studies). Only 17 studies were of an in vivo study design, carried out in a clinical setting. No studies were considered to be at low risk of bias across all four domains but 16 studies were judged to have low concern for applicability across all domains. The patient selection domain had the largest number of studies judged to be at high risk of bias (43 studies); the index test, reference standard, and flow and timing domains were judged to be at high risk of bias in 30, 12, and 7 studies respectively. Studies were synthesised using a hierarchical bivariate method for meta-analysis. There was substantial variability in the results of the individual studies, with sensitivities that ranged from 0 to 0.96 and specificities from 0 to 1.00. For all imaging methods the estimated summary sensitivity and specificity point was 0.47 (95% confidence interval (CI) 0.40 to 0.53) and 0.88 (95% CI 0.84 to 0.92), respectively. In a cohort of 1000 tooth surfaces with a prevalence of enamel caries of 63%, this would result in 337 tooth surfaces being classified as disease free when enamel caries was truly present (false negatives), and 43 tooth surfaces being classified as diseased in the absence of enamel caries (false positives). Meta-regression indicated that measures of accuracy differed according to the imaging method (Chi2(4) = 32.44, P < 0.001), with the highest sensitivity observed for CBCT, and the highest specificity observed for analogue radiographs. None of the specified potential sources of heterogeneity were able to explain the variability in results. No studies included restored teeth in their sample or reported the inclusion of sealants. We rated the certainty of the evidence as low for sensitivity and specificity and downgraded two levels in total for risk of bias due to limitations in the design and conduct of the included studies, indirectness arising from the in vitro studies, and the observed inconsistency of the results. AUTHORS' CONCLUSIONS: The design and conduct of studies to determine the diagnostic accuracy of methods to detect and diagnose caries in situ are particularly challenging. Low-certainty evidence suggests that imaging for the detection or diagnosis of early caries may have poor sensitivity but acceptable specificity, resulting in a relatively high number of false-negative results with the potential for early disease to progress. If left untreated, the opportunity to provide professional or self-care practices to arrest or reverse early caries lesions will be missed. The specificity of lesion detection is however relatively high, and one could argue that initiation of non-invasive management (such as the use of topical fluoride), is probably of low risk. CBCT showed superior sensitivity to analogue or digital radiographs but has very limited applicability to the general dental practitioner. However, given the high-radiation dose, and potential for caries-like artefacts from existing restorations, its use cannot be justified in routine caries detection. Nonetheless, if early incidental carious lesions are detected in CBCT scans taken for other purposes, these should be reported. CBCT has the potential to be used as a reference standard in diagnostic studies of this type. Despite the robust methodology applied in this comprehensive review, the results should be interpreted with some caution due to shortcomings in the design and execution of many of the included studies. Future research should evaluate the comparative accuracy of different methods, be undertaken in a clinical setting, and focus on minimising bias arising from the use of imperfect reference standards in clinical studies.

Does anthropomorphic model design in ex vivo studies affect diagnostic accuracy for dental root fracture using CBCT?

OBJECTIVES: The evidence for diagnostic accuracy using cone beam computed tomography (CBCT) for dental applications depends heavily on ex vivo research, but there is little knowledge of whether the model used affects the diagnostic accuracy results. The objective of this study was to determine the impact of different designs of anthropomorphic models on diagnostic accuracy for the specific task of dental root fracture detection. METHODS: Horizontal or oblique root fracture was induced in 24 of 48 permanent maxillary incisors. The 48 teeth were scanned by CBCT using standard clinical exposure factors on five occasions, each with a different model design. Scans were viewed by five dental and maxillofacial radiologists, who each made a forced diagnosis of fracture or no fracture in each root and a judgment on root fracture using a five-point confidence scale. Sensitivity (Se), specificity (Sp) and areas under receiver operating characteristic (ROC) curve (Az) were calculated for each observer for each model. RESULTS: There were no significant differences between the diagnostic accuracy measurements recorded using different models. There were, however, numerous significant differences between observers using the same anthropomorphic model. CONCLUSIONS: Despite the differences in X-ray attenuation between the five model designs, the results suggest that the anthropomorphic model does not affect the results of diagnostic accuracy studies on root fracture using this CBCT machine at standard clinical exposures. This provides some confidence in the previously published evidence. The interobserver diagnosis differences indicate that research using only two observers could provide misleading results.

An investigation into dose optimisation for imaging root canal anatomy using cone beam CT.

OBJECTIVES: To identify a dose as low as diagnostically acceptable and a threshold level of image quality for cone beam CT (CBCT) imaging root canals, using maxillary first molar (M1M) second mesiobuccal (MB2) canals of varying complexity for two CBCT scanners. METHODS: Dose-area product (DAP) and contrast-to-noise ratio (CNR) were measured for two scanners at a range of exposure parameters. Subjective-image-quality assessment at the same exposures was performed for three M1Ms of varying MB2 complexity, positioned in an anthropomorphic phantom. Nine raters (three endodontists, three dental radiologists and three junior staff) assessed canal visibility, using a 5-point confidence scale rating. RESULTS: Identification of simple-moderate MB2 canal complexity was achieved at a range of protocols, with DAP values of ≥209.3 and ≥203.2 mGy cm² and CNRs of 3 and 7.6 for Promax®3D and Accuitomo-F170® respectively. For complex canal anatomy, target subjective image quality was not achieved, even at the highest DAP values for both scanners. Junior staff classified significantly more images as undiagnostic compared with senior staff (p = 0.043). CONCLUSIONS: In this first study to address optimisation of CBCT imaging of root canal anatomy, a similar threshold dose for both scanners was identified for M1Ms with simple-moderate MB2 canal complexity. Increasing dose to enhance visualisation of more complex canal anatomy was ineffective. Selection of standard protocols (while avoiding lower kV/mA protocols) instead of high-resolution scans was a practical means of reducing patient dose. CNR is not a transferable measure of image quality.

Viable and necrotic tumor assessment from whole slide images of osteosarcoma using machine-learning and deep-learning models.

Pathological estimation of tumor necrosis after chemotherapy is essential for patients with osteosarcoma. This study reports the first fully automated tool to assess viable and necrotic tumor in osteosarcoma, employing advances in histopathology digitization and automated learning. We selected 40 digitized whole slide images representing the heterogeneity of osteosarcoma and chemotherapy response. With the goal of labeling the diverse regions of the digitized tissue into viable tumor, necrotic tumor, and non-tumor, we trained 13 machine-learning models and selected the top performing one (a Support Vector Machine) based on reported accuracy. We also developed a deep-learning architecture and trained it on the same data set. We computed the receiver-operator characteristic for discrimination of non-tumor from tumor followed by conditional discrimination of necrotic from viable tumor and found our models performing exceptionally well. We then used the trained models to identify regions of interest on image-tiles generated from test whole slide images. The classification output is visualized as a tumor-prediction map, displaying the extent of viable and necrotic tumor in the slide image. Thus, we lay the foundation for a complete tumor assessment pipeline from original histology images to tumor-prediction map generation. The proposed pipeline can also be adopted for other types of tumor.

Granular cell tumor in a premenstrual female breast.

Granular cell tumor is an exceedingly rare pediatric breast mass, derived from Schwann cells which are most commonly observed in the oral cavity, skin, and subcutaneous tissue. When they occur in the breast, they can mimic intrinsic breast masses. Most cases are benign, but malignant cases have been reported. We present a case of a premenstrual, African-American 9 year old female with a painful right breast mass originally felt to be an epidermal inclusion cyst. An ultrasound was performed 17 months after original presentation which demonstrated a 1 cm well-circumscribed solid ovoid mass. Despite the relatively small size and benign imaging appearance of the mass, surgical resection was performed for symptom relief given the associated pain. This is the first known case of granular cell tumor of the breast in a premenstrual female.

Convolutional Neural Network for Histopathological Analysis of Osteosarcoma.

Pathologists often deal with high complexity and sometimes disagreement over osteosarcoma tumor classification due to cellular heterogeneity in the dataset. Segmentation and classification of histology tissue in H&E stained tumor image datasets is a challenging task because of intra-class variations, inter-class similarity, crowded context, and noisy data. In recent years, deep learning approaches have led to encouraging results in breast cancer and prostate cancer analysis. In this article, we propose convolutional neural network (CNN) as a tool to improve efficiency and accuracy of osteosarcoma tumor classification into tumor classes (viable tumor, necrosis) versus nontumor. The proposed CNN architecture contains eight learned layers: three sets of stacked two convolutional layers interspersed with max pooling layers for feature extraction and two fully connected layers with data augmentation strategies to boost performance. The use of a neural network results in higher accuracy of average 92% for the classification. We compare the proposed architecture with three existing and proven CNN architectures for image classification: AlexNet, LeNet, and VGGNet. We also provide a pipeline to calculate percentage necrosis in a given whole slide image. We conclude that the use of neural networks can assure both high accuracy and efficiency in osteosarcoma classification.

A rare cause of tonsil mass in a child: Lymphoid polyp.

OBJECTIVE: Solitary mass lesions of the palatine tonsils are rare in children. While a tonsillar mass can be concerning for a neoplasm, benign conditions may present with a mass arising from the surface of the palatine tonsils in children. We describe clinical and histopathological characteristics of a lymphoid polyp in a child with unilateral tonsillar mass. METHODS: Retrospective chart review. RESULTS: A 6-year-old girl presented for evaluation of recurrent acute tonsillitis and a mass on the left palatine tonsil. A pedunculated mass with the base attached to the left palatine tonsil was observed. The mass was completely removed by tonsillectomy. The final diagnosis was lymphoid polyp. CONCLUSION: Pediatricians, otolaryngologists, and pathologists should be aware of the occurrence of tonsillar lymphoid polyp in the pediatric age group.

COMPUTER AIDED IMAGE SEGMENTATION AND CLASSIFICATION FOR VIABLE AND NON-VIABLE TUMOR IDENTIFICATION IN OSTEOSARCOMA.

Osteosarcoma is one of the most common types of bone cancer in children. To gauge the extent of cancer treatment response in the patient after surgical resection, the H&E stained image slides are manually evaluated by pathologists to estimate the percentage of necrosis, a time consuming process prone to observer bias and inaccuracy. Digital image analysis is a potential method to automate this process, thus saving time and providing a more accurate evaluation. The slides are scanned in Aperio Scanscope, converted to digital Whole Slide Images (WSIs) and stored in SVS format. These are high resolution images, of the order of 109 pixels, allowing up to 40X magnification factor. This paper proposes an image segmentation and analysis technique for segmenting tumor and non-tumor regions in histopathological WSIs of osteosarcoma datasets. Our approach is a combination of pixel-based and object-based methods which utilize tumor properties such as nuclei cluster, density, and circularity to classify tumor regions as viable and non-viable. A K-Means clustering technique is used for tumor isolation using color normalization, followed by multi-threshold Otsu segmentation technique to further classify tumor region as viable and non-viable. Then a Flood-fill algorithm is applied to cluster similar pixels into cellular objects and compute cluster data for further analysis of regions under study. To the best of our knowledge this is the first comprehensive solution that is able to produce such a classification for Osteosarcoma cancer. The results are very conclusive in identifying viable and non-viable tumor regions. In our experiments, the accuracy of the discussed approach is 100% in viable tumor and coagulative necrosis identification while it is around 90% for fibrosis and acellular/hypocellular tumor osteoid, for all the sampled datasets used. We expect the developed software to lead to a significant increase in accuracy and decrease in inter-observer variability in assessment of necrosis by the pathologists and a reduction in the time spent by the pathologists in such assessments.

The use of intraoral ultrasound in the characterization of minor salivary gland malignancy: report of two cases.

It is generally accepted that ultrasound is now the first line of imaging of palpable lumps of the neck. Standardized protocols exist for the evaluation of thyroid, salivary gland and nodal disease, and sonography is increasingly being used in the characterization of intraoral soft tissue lesions. Here, we present two cases where intraoral sonography was invaluable in the early detection of oral malignancy.

PAX7 expression defines germline stem cells in the adult testis.

Spermatogenesis is a complex, multistep process that maintains male fertility and is sustained by rare germline stem cells. Spermatogenic progression begins with spermatogonia, populations of which express distinct markers. The identity of the spermatogonial stem cell population in the undisturbed testis is controversial due to a lack of reliable and specific markers. Here we identified the transcription factor PAX7 as a specific marker of a rare subpopulation of A(single) spermatogonia in mice. PAX7+ cells were present in the testis at birth. Compared with the adult testis, PAX7+ cells constituted a much higher percentage of neonatal germ cells. Lineage tracing in healthy adult mice revealed that PAX7+ spermatogonia self-maintained and produced expanding clones that gave rise to mature spermatozoa. Interestingly, in mice subjected to chemotherapy and radiotherapy, both of which damage the vast majority of germ cells and can result in sterility, PAX7+ spermatogonia selectively survived, and their subsequent expansion contributed to the recovery of spermatogenesis. Finally, PAX7+ spermatogonia were present in the testes of a diverse set of mammals. Our data indicate that the PAX7+ subset of A(single) spermatogonia functions as robust testis stem cells that maintain fertility in normal spermatogenesis in healthy mice and mediate recovery after severe germline injury, such as occurs after cancer therapy.

A high power ion thruster for deep space missions.

The Nuclear Electric Xenon Ion System ion thruster was developed for potential outer planet robotic missions using nuclear electric propulsion (NEP). This engine was designed to operate at power levels ranging from 13 to 28 kW at specific impulses of 6000-8500 s and for burn times of up to 10 years. State-of-the-art performance and life assessment tools were used to design the thruster, which featured 57-cm-diameter carbon-carbon composite grids operating at voltages of 3.5-6.5 kV. Preliminary validation of the thruster performance was accomplished with a laboratory model thruster, while in parallel, a flight-like development model (DM) thruster was completed and two DM thrusters fabricated. The first thruster completed full performance testing and a 2000-h wear test. The second successfully completed vibration tests at the full protoflight levels defined for this NEP program and then passed performance validation testing. The thruster design, performance, and the experimental validation of the design tools are discussed in this paper.

Atypical presentation of extranodal Rosai-Dorfman disease.

We describe a 42-year-old woman with progressive dyspnea on exertion resulting from pulmonary artery compression by a mediastinal mass due to extranodal Rosai-Dorfman disease. After initial biopsies were inconclusive, she underwent surgical resection of the mass to relieve the pulmonary artery compression, which was causing severe right ventricular dysfunction. Debulking of the mass required resection and reconstruction of the ascending aorta, pulmonary trunk, and bilateral pulmonary arteries using cardiopulmonary bypass and circulatory arrest. We believe this is the first report of Rosai-Dorfman disease manifesting as compression of the thoracic great vessels.