Relevant Diagnostic Features Research Articles

A brief insight regarding Nasopalatine duct cyst- Report of two cases with a review of literature

Abstract Nasopalatine duct cysts (NPDCs) are among the most common nonodontogenic cysts, typically located in the midline of anterior maxillary hard palate. They usually arise from the embryonic epithelial vestiges of the nasopalatine duct. NPDCs predominantly affect adult males, generally during their fourth decade of life. Clinically, they present as asymptomatic or occasionally painful, fluctuant or discharging swellings involving the hard palate. Radiographically, NPDCs are characterized by a well-defined, fairly corticated, inverted pear-shaped or heart-shaped radiolucency situated between the roots of the maxillary incisors. Histopathologically, NPDCs exhibit a wide spectrum of findings. The lining may be comprised of stratified squamous, pseudostratified ciliated columnar, columnar, or cuboidal epithelium, or a combination and transition of these types. The cystic capsule is fibrocollagenous and can exhibit certain unique features, such as neurovascular bundles, mucous glands, and cartilaginous rests. NPDCs are typically managed through surgical enucleation, and recurrences are rare. Herein, we present two cases of NPDCs, along with a brief overview of their origin, relevant diagnostic features, and management.

Enhancing Thyroid Disease Diagnosis through Emperor Penguin Optimization Algorithm

The thyroid gland plays a pivotal role in maintaining overall health, making the accurate diagnosis of thyroid diseases crucial. In this study, we propose an innovative approach to enhance the diagnostic accuracy of thyroid diseases through the integration of the Emperor Penguin Optimization Algorithm (EPO). EPO, inspired by the efficient foraging behavior of emperor penguins, offers a unique optimization strategy for feature selection and model tuning in medical diagnostics. By employing EPO, we optimize the selection of relevant diagnostic features and fine-tune the parameters of machine learning models.
 Our experimental results demonstrate a significant improvement in diagnostic accuracy compared to traditional methods. The EPO-enhanced Thyroid Disease Diagnosis model achieves superior performance, ensuring a higher true positive rate and a lower false positive rate. This promising outcome suggests that EPO can be a valuable tool in the development of more accurate and reliable diagnostic systems for thyroid diseases, potentially leading to early detection and improved patient outcomes.
 Our approach achieved an impressive accuracy rate of 99.7 % when tested.

Classification and challenges in the histopathological diagnosis of peripheral T-cell lymphomas, emphasis on the WHO-HAEM5 updates.

Mature T-cell lymphomas represent neoplastic expansions of T-cell lymphocytes with a post-thymic derivation. Most of these tumors feature aggressive clinical behavior and challenging histopathological diagnosis and classification. Novel findings in the genomic landscape of T-cell lymphomas are helping to improve the understanding of the biology and the molecular mechanisms that underly its clinical behavior. The most recent WHO-HAEM5 classification of hematolymphoid tumors introduced novel molecular and histopathological findings that will aid in the diagnostic classification of this group of neoplasms. The current review article summarizes the most relevant diagnostic features of peripheral T-cell lymphomas with an emphasis on the updates that are incorporated at the WHO-HAEM5.

Perturbed Composite Attention Model for Macular Optical Coherence Tomography Image Classification

In this article, we propose a deep architecture stemming from a perturbed composite attention mechanism with the following two novel attention modules: Multilevel perturbed spatial attention (MPSA) and multidimension attention (MDA) for macular optical coherence tomography (OCT) image (scan) classification. MPSA is designed by adding positive perturbations to the attention layers, thereby amplifying both the salient regions of input images and discriminative features obtained from intermediate layers of the network. On the other hand, the MDA encodes the normalized interdependency of spatial information among various channels of the extracted feature maps. The perturbed composite attention mechanism enables the new architecture to automatically extract relevant diagnostic features at different levels of feature representation resulting in the superior classification of macular diseases such as age-related macular degeneration (AMD), diabetic macular edema (DME), and choroidal neovascularization (CNV). The proposed end-to-end trainable architecture does not require preprocessing steps, such as region of interest extraction, denoising, and retinal flattening, making the network more robust and fully automatic. Experimental results on three macular OCT datasets and ablation studies show that our proposed network outperforms the current state-of-the-art methodologies.

Classification of Wideband Tympanometry by Deep Transfer Learning With Data Augmentation for Automatic Diagnosis of Otosclerosis.

Otosclerosis is a common disease of the middle ear leading to stapedial fixation. Its rapid and non-invasive diagnosis could be achieved through wideband tympanometry (WBT), but the interpretation of the raw data provided by this tool is complex and time-consuming. Convolutional neural networks (CNN) could potentially be applied to this situation to help the clinicians categorize WBT data. A dataset containing 135 samples from 80 patients with otosclerosis and 55 controls was obtained. We designed a lightweight CNN to categorize samples into the otosclerosis and control. Receiver operating characteristic (ROC) analysis showed an area under the curve (AUC) of 0.95 ±0.011, and the F1-score was 0.89 ±0.031 ( r=10). The performance was further improved by data augmentation schemes and transfer learning strategies (AUC: 0.97 ±0.010, F1-score: 0.94 ±0.016, , ANOVA). Finally, the most relevant diagnostic features employed by the CNN were assessed via the activation pattern heatmaps. These results are crucial for the visual interpretation of WBT graphic outputs which clinicians use in routine, and for a better understanding of the WBT signal in relation to the ossicular mechanics.

Fabrication of microcalcifications for insertion into phantoms used to evaluate x-ray breast imaging systems

Physical breast phantoms can be used to evaluate x-ray imaging systems such as mammography, digital breast tomosynthesis and dedicated breast computed tomography (bCT). These phantoms typically attempt to mimic x-ray attenuation properties of adipose and fibroglandular tissues within the breast. In order to use these phantoms for task-based objective assessment of image quality, relevant diagnostic features should be modeled within the phantom, such as mass lesions and/or microcalcifications. Evaluating imaging system performance in detecting microcalcifications is of particular interest due to its’ clinical significance. Many previously-developed phantoms have used materials that model microcalcifications using unrealistic chemical composition, which do not accurately portray their desired x-ray attenuation and scatter properties. We report here on a new method for developing real microcalcification simulants that can be embedded in breast phantoms. This was achieved in several steps, including cross-linking hydroxyapatite and calcium oxalate powders with a binder called polyvinylpyrrolidone (PVP), and mechanical compression. The fabricated microcalcifications were evaluated by measuring their x-ray attenuation and scatter properties using x-ray spectroscopy and x-ray diffraction systems, respectively, and were demonstrated with x-ray mammography and bCT images. Results suggest that using these microcalcification models will make breast phantoms more realistic for use in evaluating task-based detection performance of the abovementioned breast imaging techniques, and bode well for extending their use to spectral imaging and x-ray coherent scatter computed tomography.

Flexibility of emerging face categorization at different levels of abstraction

Categorization of visual stimuli at different levels of abstraction relies on the encoding of relevant diagnostic features present at different spatial scales. We used the Eidolon Factory, an image-manipulation algorithm that introduces random disarray fields across spatial scales, to study how such a process flexibly combines perceptual information to perform successful categorization depending on task demands. Images of animal faces, human faces, and everyday objects were disarrayed coherently (random fields correlated) or incoherently (random fields randomized) to create a family of 50 eidolons per stimulus image with increasing disarray. Participants (N = 243) viewed each family of eidolons in a smooth sequence from maximum disarray to no disarray and performed a category verification task either at the superordinate (any face type) or basic (human face only) levels at two levels of uncertainty: participants in one group used their gut feeling to respond, whereas another group had to be sure of their decision. When participants used their gut feeling to respond, we observed a superordinate-level advantage. When they were sure of their response, we observed a basic-level advantage. Coherently disarrayed sequences impaired target detection compared to incoherently disarrayed sequences for both levels of response certainty. Furthermore, participants’ sensitivity in the Any Face condition increased when they observed coherently disarrayed sequences and had to be sure of their response. These results suggest that the visual system does not strictly adhere to feedforward processing but flexibly adjusts to the relevant perceptual information depending on task context.

Into Clinical Practice: Diagnosis and Therapy of Retroperitoneal Fibrosis.

We aim to review the most relevant diagnostic features and treatment options of retroperitoneal fibrosis, in order to provide a useful guide for clinical practice. The recent literature highlights the role of imaging studies such as computed tomography, magnetic resonance imaging and positron emission tomography as useful tools for the diagnosis of retroperitoneal fibrosis, with retroperitoneal biopsy being reserved to atypical cases. The treatment approach is mainly conservative and is based on the use of medical therapies plus urological interventions. Medical therapies essentially comprise glucocorticoids and immunosuppressants-either traditional or biological agents such as rituximab. Surgical ureterolysis is only left for refractory cases. Recent findings in retroperitoneal fibrosis highlight the possibility of a non-invasive diagnostic approach and a conservative treatment strategy.

Advanced diagnostic imaging and intervention in tendon diseases.

Degenerative tendon pathology represents one of the most frequent and disabling musculoskeletal disorders. Diagnostic radiology plays a fundamental role in the clinical evaluation of tendon pathologies. Moreover, several minimally invasive treatments can be performed under imaging guidance to treat tendon disorders, maximizing the efficacy and reducing procedural complications. In this review article we describe the most relevant diagnostic features of conventional and advanced US and MRI imaging in tendon disorders, along with the main options for image-guided intervention. (www.actabiomedica.it)

Comprehensive description of T2 value spatial variations in non-osteoarthritic femoral cartilage using three-dimensional registration of morphological and relaxometry data

PurposeThe aim of this study was to develop and assess a method of quantifying cartilage T2 relaxation times in a series of volumes of interest (VOIs) covering the entire cartilage of the femoral condyles. Subsequently, the method was used to test for T2 spatial variations in non-osteoarthritic (OA) knees. MethodsTen non-OA subjects (five female, average 30 years) were enrolled after informed consent. Three-dimensional bone and cartilage models were created by double echo steady state (DESS) morphological magnetic resonance image (MRI) segmentation, and the models were semi-manually registered with multi-slice, multi-echo (MSME) T2 MRI. Mean T2 values were calculated for 12 VOIs derived from cartilage thickness literature and their respective superficial and deep layers. ResultsAnalyses showed that intra- and inter-rater reliabilities of the presented method were “good” to “excellent” in more than 90% of the VOIs. Additionally, several spatial differences in T2 values were observed, including, for the medial condyle, higher T2 values in the anterior and central VOIs versus in the posterior VOI (p < .05). T2 values were also generally higher in the superficial versus deep layers (p < .05). ConclusionsThe presented MRI T2 analysis method is reliable and provides a comprehensive quantification of spatial heterogeneity of healthy cartilage compositional properties. This method can be further applied to better understand knee OA pathophysiology and potentially define clinically relevant diagnostic features of the disease.

Think big — think omics

Traditionally the laboratory diagnosis of inborn errors of metabolism largely relies on targeted hypothesis‐driven measurements of metabolites in body fluids. The hypothesis is usually based on the phenotypic characteristics of the patient, defined through deep phenotyping or phenomics. The biochemical phenotype, or rather the ‘metabolite profile’ reflects both endogenous factors such as genotype(s), gene expression, the different chemical reactions taking place in the body, as well as exogenous factors such as dietary habits, drug metabolism and the microbiome. The last decade has seen the emergence of untargeted, hypothesis‐free measurements. NMR spectroscopy and mass spectrometry in combination with different separation techniques (LC, GC or CE) pave the way to an important next step in our understanding of inborn errors of metabolism. The aim of untargeted metabolomics is to identify and measure as many metabolites as possible, including unknowns, to generate the metabolic fingerprint characteristic for a biological sample and indicative for genetic defects influencing human metabolism. Typically, untargeted metabolomics techniques show more than 10,000 “features” in a single body fluid sample. These are big data! Bioinformatic‐ and chemometric techniques are required to reveal the relevant diagnostic features, which in turn help identify the specific aetiologic condition in the individual patient. This approach is rather different from classical metabolomics studies that usually describe the comparison between a patient group and a control group. This issue of the journal illustrates that “next generation metabolic screening” (NGMS) techniques enable us to use untargeted metabolomics for diagnostics in a clinical setting (Coene et al 2018). Untargeted metabolomics techniques are approaching maturity. It is demonstrated in this special JIMD issue that untargeted metabolomics techniques can identify the vast majority of IEM‐diagnoses as reliably as the conventional techniques. In addition, many examples from NMR spectroscopy and untargeted MS analyses have already emerged that unravel the identity of hitherto unknown inborn errors of metabolism (van Karnebeek et al 2016; Pol et al 2018). These techniques also have the power to discover novel biomarkers even in well‐known and in‐depth studied inborn errors of metabolism (Abela et al 2016; Abela et al 2017).

An eye tracking study of bloodstain pattern analysts during pattern classification

Bloodstain pattern analysis (BPA) is the forensic discipline concerned with the classification and interpretation of bloodstains and bloodstain patterns at the crime scene. At present, it is unclear exactly which stain or pattern properties and their associated values are most relevant to analysts when classifying a bloodstain pattern. Eye tracking technology has been widely used to investigate human perception and cognition. Its application to forensics, however, is limited. This is the first study to use eye tracking as a tool for gaining access to the mindset of the bloodstain pattern expert. An eye tracking method was used to follow the gaze of 24 bloodstain pattern analysts during an assigned task of classifying a laboratory-generated test bloodstain pattern. With the aid of an automated image-processing methodology, the properties of selected features of the pattern were quantified leading to the delineation of areas of interest (AOIs). Eye tracking data were collected for each AOI and combined with verbal statements made by analysts after the classification task to determine the critical range of values for relevant diagnostic features. Eye-tracking data indicated that there were four main regions of the pattern that analysts were most interested in. Within each region, individual elements or groups of elements that exhibited features associated with directionality, size, colour and shape appeared to capture the most interest of analysts during the classification task. The study showed that the eye movements of trained bloodstain pattern experts and their verbal descriptions of a pattern were well correlated.

Two new species of Anatrichis LeConte (Coleoptera: Carabidae: Oodini) from Japan, with notes on the taxonomic position of Oodes infimus Andrewes.

Two new species of the genus Anatrichis LeConte, 1853 are described from Japan, A. morii, sp. n. (type locality: Fukuoka Prefecture, Shimotoubaru) and A. ryukyuensis, sp. n. (type locality: Okinawa Prefecture, Iriomote Island). Relevant diagnostic features of the new species are described, illustrated and compared with those of other species. A new combination is proposed: Anatrichis infima (Andrewes, 1936), comb. n. from Oodes infimus, and a lectotype designation is made for this species. The "indica" group of species is defined to include all the Asiatic congeners.

Fourier domain image fusion for differential X-ray phase-contrast breast imaging

X-Ray Phase-Contrast (XPC) imaging is a novel technology with a great potential for applications in clinical practice, with breast imaging being of special interest. This work introduces an intuitive methodology to combine and visualize relevant diagnostic features, present in the X-ray attenuation, phase shift and scattering information retrieved in XPC imaging, using a Fourier domain fusion algorithm. The method allows to present complementary information from the three acquired signals in one single image, minimizing the noise component and maintaining visual similarity to a conventional X-ray image, but with noticeable enhancement in diagnostic features, details and resolution. Radiologists experienced in mammography applied the image fusion method to XPC measurements of mastectomy samples and evaluated the feature content of each input and the fused image. This assessment validated that the combination of all the relevant diagnostic features, contained in the XPC images, was present in the fused image as well.

Hereditary Spherocytosis

Neonatal jaundice is commonly encountered in the neonatal period. Although it is mostly asymptomatic, severe cases may present as encephalopathy or kernicterus. Hereditary spherocytosis (HS) is the most common cause of nonimmune hemolytic anemia and the third most common cause of kernicterus after glucose-6-phosphate-dehydrogenase deficiency and ABO isoimmunization. Awareness of the clinical presentation and the laboratory tests necessary to diagnose the disease can lead to early detection and effective interventions, thereby preventing adverse outcomes. This article focuses on HS: its pathophysiology, clinical presentation in the neonatal period, natural history, and the relevant diagnostic features of evaluation.

High-Performance Computational Analysis of Glioblastoma Pathology Images with Database Support Identifies Molecular and Survival Correlates.

In this paper, we present a novel framework for microscopic image analysis of nuclei, data management, and high performance computation to support translational research involving nuclear morphometry features, molecular data, and clinical outcomes. Our image analysis pipeline consists of nuclei segmentation and feature computation facilitated by high performance computing with coordinated execution in multi-core CPUs and Graphical Processor Units (GPUs). All data derived from image analysis are managed in a spatial relational database supporting highly efficient scientific queries. We applied our image analysis workflow to 159 glioblastomas (GBM) from The Cancer Genome Atlas dataset. With integrative studies, we found statistics of four specific nuclear features were significantly associated with patient survival. Additionally, we correlated nuclear features with molecular data and found interesting results that support pathologic domain knowledge. We found that Proneural subtype GBMs had the smallest mean of nuclear Eccentricity and the largest mean of nuclear Extent, and MinorAxisLength. We also found gene expressions of stem cell marker MYC and cell proliferation maker MKI67 were correlated with nuclear features. To complement and inform pathologists of relevant diagnostic features, we queried the most representative nuclear instances from each patient population based on genetic and transcriptional classes. Our results demonstrate that specific nuclear features carry prognostic significance and associations with transcriptional and genetic classes, highlighting the potential of high throughput pathology image analysis as a complementary approach to human-based review and translational research.

The implications of the new paradigm of dental caries

The caries process is the ubiquitous, natural metabolism in the biofilm that causes numerous fluctuations in pH. The interaction of this biofilm with the dental tissues may result in a caries lesion. However, lesion formation and progression can be controlled, particularly by disturbing plaque regularly with a fluoride containing toothpaste. This paradigm implies that everyone with teeth is at risk to lesion development. Treatment of caries is principally non-operative, involving plaque control, fluoride and a sensible diet. Operative dentistry repairs un-cleansable cavities and is part of plaque control. A diagnosis is a mental resting place on the way to a treatment decision. The relevant diagnostic features with respect to caries are lesion activity (active lesions require active management) and un-cleansable cavities. When teaching undergraduates, it is important that they are credited for the non-operative treatment of caries as well as for operative dentistry. This is equally important in dental practice where an appropriate skills mix of the dental team is required to deliver dental health cost-effectively. Training more dentists may be an expensive mistake as far as disease control is concerned. It is ironic that dentists make most money from operative care and specialist treatment when disease control could be delivered relatively cheaply. The key to dental health is regular and effective plaque control with a fluoride containing toothpaste, from cradle to grave.

Brain Tumors

Richard Prayson, Bette Kleinschmidt-DeMasters, Mark Cohen and David Elder Brain Tumors Demos Medical Publishing , New York , 2010 . 318 + xv Pages. Price $140 (hardback). ISBN 978-1933864693 Brain Tumors is one of a series of pathology texts by Demos Medical Publishing which aim to cover the full spectrum of surgical pathology in a case-based series format. In addition to a volume on brain tumours the Consultant Pathology Series currently includes volumes on head and neck pathology and tumorigenic melanocytic proliferations with forthcoming volumes in the series covering pathology of the liver, bladder and thyroid papillary lesions. The authors are all experienced pathologists who have accumulated large collections of difficult cases. The cases presented in Brain Tumors are based on actual consultations with no less than 101 individual chapters over 318 pages. The text covers a full range of histopathological diagnoses, ranging from normal and reactive conditions to the rarer tumours which have only recently been included in the most up to date World Health Organization (WHO) classification. Each chapter follows an identical format. A short introductory paragraph provides background clinical information including age, clinical presentation and imaging findings. Next is a summary of the reporting pathologist's opinion with a description of the histological findings. This opinion is then expanded upon in a section of comment and discussion with further details of the diagnostic histological features, a review of relevant differential diagnoses and some clinicopathological correlation. A discussion of the immunohistochemical findings and, where relevant, the molecular pathology, is also included. Each case is accompanied by a series of illustrations to highlight the relevant diagnostic features and two or three references for those wishing to do some further reading. Although not currently available, the publishers anticipate that the images from the book, along with additional images to supplement the presentation of the case, will eventually become available on a website for downloading, study and use in education. Brain Tumors is an attempt to cover the entire scope of central nervous system malignancy (with a few exceptions) and will, as the preface states, offer the beginner or relatively inexperienced pathologist an opportunity to review the basics and see some of the rarer entities. The descriptions of the histology are succinct with the diagnostic features nicely illustrated by the accompanying micrographs. In each case the thought process leading to each diagnosis is clearly reviewed and the utility of immunohistochemical markers and special stains are elaborated upon, with their role in ruling out alternative diagnoses clearly explained. The format of the text is easily accessible with a user-friendly layout, and the consistency of presentation means that the relevant information is easily located at a glance. It is not in the same league as some other textbooks on the histopathology of brain tumours, such as the WHO classification and the Armed Forces Institute of Pathology (AFIP) fascicle on tumours of the central nervous system. It does not cover intra-operative diagnoses or detailed information on the genetics of brain tumours, although ultrastructural features are briefly covered in some of the chapters where relevant. As such it will not provide the sort of detailed information that a specialist neuropathologist may need to access. However, in fairness, this is not a claim that the authors make and although each entity is covered, in most cases, in only two to three pages, the amount of information that the authors are able to provide is impressive. Indeed even the more experienced neuropathologist is likely to find the description and differential diagnosis of the rarer entities useful on those occasions that they face them as part of their daily practice. In summary Brain Tumors certainly delivers what it promises to its intended target audience. It will provide those at the start of their careers in diagnostic neuropathology or general pathologists who occasionally dabble in diagnostic neuropathology with a well thought out, practical and easily accessible resource which covers the whole range of brain tumours in an easy to read textbook. The well-organized layout, the short but informative reviews of each diagnostic entity and the good quality micrographs justify a competitively placed price of $140.

Axial computed tomography of the patellofemoral joint with and without quadriceps contraction.

Computed tomography was used to analyze the patellofemoral relationship during the first 60 degrees of knee flexion in patients with chronic patellofemoral pain syndrome (49 knees) and a healthy control group (15 knees). The patellofemoral joints were imaged axially through the center of the patella articular cartilage with the knee flexed 0 degrees, 0 degrees with maximal quadriceps muscle contraction, 30 degrees, and 60 degrees. In 0 degrees of knee flexion, the sulcus angle was greater in the symptomatic group than in normal controls. The patella displaced further laterally, and the lateral patellar tilt was greater. The patellar lateral index was found to be greater at 0 degrees and indicated severe abnormality with full quadriceps muscle contraction. The Laurin angle was pathologic with increased medial opening, especially with muscle contraction. At 30 degrees of knee flexion, these differences were less marked than at 0 degrees. No relevant differences were found with 60 degrees of knee flexion. This study showed that the sulcus angle, lateral patellar displacement, lateral patellar tilt, patella lateral condyle index, and Laurin angle are relevant diagnostic features in 0 degrees of knee flexion, indicating a pathological femoral patellar gliding mechanism. Our evaluation also demonstrated the influence of full quadriceps muscle contraction, especially regarding lateral patellar displacement and the Laurin angle, and it was most prominent on the patella lateral condyle index. Thus, quadriceps muscle contraction often creates a more pathological displacement of the patella, which can be depicted using axial computed tomography.

Case report 712

Synovial cysts are a common complication of osteoarthritis in the lumbar spine, causing pain and neurological symptoms. However with early diagnosis a good clinical result can be expected. This report describes a documented case of hemorrhage into a synovial cyst demonstrated on both MR and CT imaging and summarizes the relevant diagnostic features. The sites of origin of such a synovial hemorrhagic cyst are described and its relationship to an arthritic facet joint is stressed.