Visual Diagnosis Research Articles

Development of a portable DNA extraction and cross-priming amplification (CPA) tool for rapid in-situ visual diagnosis of plant diseases

Plant pathogens cause severe losses to crop yields and economic returns in agriculture. Despite plant tissue DNA extraction of typically constituting a preliminary step in nucleic acid-based molecular diagnostics, such lab-based methods can be time-consuming and arduous to complete many samples. To mitigate these challenges, we developed an inexpensive portable DNA extraction technique that is lightweight and suitable for deployment in sampling locations, such as fields. It includes a DNA extraction device fabricated with a Steel Microneedle Array (SMA) and a simple high-efficiency DNA extraction buffer. As a result, DNA extraction times can be reduced to within ~ 1 min, and the eluted DNA is demonstrated to be suitable for subsequent molecular biological analyses without requiring additional purification. Cross-priming amplification (CPA) technology was first established to detect Phytophthora infestans, which achieves sensitivity attainment of 10–7 ng/µL. The detection result can be conveniently estimated with naked-eye visual inspection using fluorescent dsDNA binding dye. CPA was demonstrated to be more feasible than PCR-based approaches and performed well in species-specific and practicability tests. This study elucidates a novel integrated pathogen detection technique coupled with SMA-Device extraction and a modified visual CPA assay to establish and verify various field-based samples infected with multiple pathogens. Altogether, the total sample-to-answer time for pathogen detection was reduced to ~ 1.5 h, making field-based analysis affordable and achievable for farmers or extension workers inside and outside the laboratory.

Low tensor train and low multilinear rank approximations of 3D tensors for compression and de-speckling of optical coherence tomography images

Objective. Many methods for compression and/or de-speckling of 3D optical coherence tomography (OCT) images operate on a slice-by-slice basis and, consequently, ignore spatial relations between the B-scans. Thus, we develop compression ratio (CR)-constrained low tensor train (TT)—and low multilinear (ML) rank approximations of 3D tensors for compression and de-speckling of 3D OCT images. Due to inherent denoising mechanism of low-rank approximation, compressed image is often even of better quality than the raw image it is based on. Approach. We formulate CR-constrained low rank approximations of 3D tensor as parallel non-convex non-smooth optimization problems implemented by alternating direction method of multipliers of unfolded tensors. In contrast to patch- and sparsity-based OCT image compression methods, proposed approach does not require clean images for dictionary learning, enables CR as high as 60:1, and it is fast. In contrast to deep networks based OCT image compression, proposed approach is training free and does not require any supervised data pre-processing. Main results. Proposed methodology is evaluated on twenty four images of a retina acquired on Topcon 3D OCT-1000 scanner, and twenty images of a retina acquired on Big Vision BV1000 3D OCT scanner. For the first dataset, statistical significance analysis shows that for CR ≤ 35, all low ML rank approximations and Schatten-0 (S 0) norm constrained low TT rank approximation can be useful for machine learning-based diagnostics by using segmented retina layers. Also for CR ≤ 35, S 0-constrained ML rank approximation and S 0-constrained low TT rank approximation can be useful for visual inspection-based diagnostics. For the second dataset, statistical significance analysis shows that for CR ≤ 60 all low ML rank approximations as well as S 0 and S 1/2 low TT ranks approximations can be useful for machine learning-based diagnostics by using segmented retina layers. Also, for CR ≤ 60, low ML rank approximations constrained with S p , p ∊ {0, 1/2, 2/3} and one surrogate of S 0 can be useful for visual inspection-based diagnostics. That is also true for low TT rank approximations constrained with S p , p ∊ {0, 1/2, 2/3} for CR ≤ 20. Significance. Studies conducted on datasets acquired by two different types of scanners confirmed capabilities of proposed framework that, for a wide range of CRs, yields de-speckled 3D OCT images suitable for clinical data archiving and remote consultation, for visual inspection-based diagnosis and for machine learning-based diagnosis by using segmented retina layers.

Non-Melanoma Skin Cancer Detection in the Age of Advanced Technology: A Review.

Skin cancer is the most common cancer diagnosis in the United States, with approximately one in five Americans expected to be diagnosed within their lifetime. Non-melanoma skin cancer is the most prevalent type of skin cancer, and as cases rise globally, physicians need reliable tools for early detection. Artificial intelligence has gained substantial interest as a decision support tool in medicine, particularly in image analysis, where deep learning has proven to be an effective tool. Because specialties such as dermatology rely primarily on visual diagnoses, deep learning could have many diagnostic applications, including the diagnosis of skin cancer. Furthermore, with the advancement of mobile smartphones and their increasingly powerful cameras, deep learning technology could also be utilized in remote skin cancer screening applications. Ultimately, the available data for the detection and diagnosis of skin cancer using deep learning technology are promising, revealing sensitivity and specificity that are not inferior to those of trained dermatologists. Work is still needed to increase the clinical use of AI-based tools, but based on the current data and the attitudes of patients and physicians, deep learning technology could be used effectively as a clinical decision-making tool in collaboration with physicians to improve diagnostic efficiency and accuracy.

Symptoms: Sudden Sensorineural Hearing Loss and Aural Fullness

Symptoms: Sudden Sensorineural Hearing Loss and Aural Fullness

Pathologists aren't pigeons: exploring the neural basis of visual recognition and perceptual expertise in pathology.

Visual (perceptual) reasoning is a critical skill in many medical specialties, including pathology, diagnostic imaging, and dermatology. However, in an ever-compressed medical curriculum, learning and practicing this skill can be challenging. Previous studies (including work with pigeons) have suggested that using reward-feedback-based activities, novices can gain expert levels of visual diagnostic accuracy in shortened training times. But is this level of diagnostic accuracy a result of image recognition (categorization) or is it the acquisition of diagnostic expertise? To answer this, the authors measured electroencephalographic data (EEG) and two components of the human event-related brain potential (reward positivity and N170) to explore the nature of visual expertise in a novice-expert study in pathology visual diagnosis. It was found that the amplitude of the reward positivity decreased with learning in novices (suggesting a decrease in reliance on feedback, as in other studies). However, this signal remained significantly different from the experts whose reward positivity signal did not change over the course of the experiment. There were no changes in the amplitude of the N170 (a reported neural marker of visual expertise) in novices over time. Novice N170 signals remained statistically and significantly lower in amplitude compared to experts throughout task performance. These data suggest that, while novices gained the ability to recognize (categorize) pathologies through reinforcement learning as quantified by the change in reward positivity, increased accuracy, and decreased time for responses, there was little change in the neural marker associated with visual expertise (N170). This is consistent with the multi-dimensional and complex nature of visual expertise and provides insight into future training programs for novices to bridge the expertise gap.

A novel aptamer-G-quadruplex/hemin self-assembling color system: rapid visual diagnosis of invasive fungal infections

BackgroundThe clinical symptoms of invasive fungal infections (IFI) are nonspecific, and early clinical diagnosis is challenging, resulting in high mortality rates. This study reports the development of a novel aptamer-G-quadruplex/hemin self-assembling color system (AGSCS) based on (1 → 3)-β-D-glucans’ detection for rapid, specific and visual diagnosis of IFI.MethodsWe screened high affinity and specificity ssDNA aptamers binding to (1 → 3)-β-D-glucans, the main components of cell wall from Candida albicans via Systematic Evolution of Ligands by EXponential enrichment. Next, a comparison of diagnostic efficiency of AGSCS and the (1 → 3)-β-D-glucans assay (“G test”) with regard to predicting IFI in 198 clinical serum samples was done.ResultsWater-soluble (1 → 3)-β-D-glucans were successfully isolated from C. albicans ATCC 10,231 strain, and these low degree of polymerization glucans (< 1.7 kD) were targeted for aptamer screening with the complementary sequences of G-quadruplex. Six high affinity single stranded DNA aptamers (A1, A2, A3, A4, A5 and A6) were found. The linear detection range for (1 → 3)-β-D-glucans stretched from 1.6 pg/mL to 400 pg/mL on a microplate reader, and the detection limit was 3.125 pg/mL using naked eye observation. Using a microplate reader, the sensitivity and specificity of AGSCS for the diagnosis of IFI were 92.68% and 89.65%, respectively, which was higher than that of the G test.ConclusionThis newly developed visual diagnostic method for detecting IFI showed promising results and is expected to be developed as a point-of-care testing kit to enable quick and cost effective diagnosis of IFI in the future.

Visual diagnosis of female genital schistosomiasis in Zambian women from hand-held colposcopy: agreement of expert image review and association with clinical symptoms.

Background:Female genital schistosomiasis (FGS) can occur in S. haematobiuminfection and is caused by egg deposition in the genital tract. Confirming a diagnosis of FGS is challenging due to the lack of a diagnostic reference standard. A 2010 expert-led consensus meeting proposed visual inspection of the cervicovaginal mucosa as an adequate reference standard for FGS diagnosis. The agreement of expert human reviewers for visual-FGS has not been previously described. Methods: In two Zambian communities, non-menstruating, non-pregnant, sexually-active women aged 18-31 years participating in the HPTN 071 (PopART) Population-Cohort were enrolled in a cross-sectional study. Self-collected genital swabs and a urine specimen were collected at a home visit; trained midwives performed cervicovaginal lavage (CVL) and hand-held colposcopy at a clinic visit. S. haematobiumeggs and circulating anodic antigen (CAA) were detected from urine. Twosenior physicians served asexpert reviewers and independently diagnosed visual-FGS as the presence of sandy patches, rubbery papules or abnormal blood vessels in cervicovaginal images obtained by hand-held colposcopy. PCR-FGS was defined as SchistosomaDNA detected by real-time PCR in any genital specimen (CVL or genital swab). Results: Of 527 women with cervicovaginal colposcopic images, 468/527 (88.8%) were deemed interpretable by Reviewer 1 and 417/527 (79.1%) by Reviewer 2. Visual-FGS was detected in 35.3% (165/468) of participants by expert review of colposcopic images by Reviewer 1 and in 63.6% (265/417) by Reviewer 2.Cohen's kappa statistic for agreement between the two reviewers was 0.16, corresponding to "slight" agreement. The reviewers made concordant diagnoses in 38.7% (204/527) participants (100 negative, 104 positive) and discordant diagnoses in 31.8% (168/527) participants. Conclusions:The unexpectedly low level of correlation between expert reviewers highlights the imperfect nature of visual diagnosis for FGS based on cervicovaginal images. This finding is a call to action for improved point-of-care diagnostics for female genital schistosomiasis.

Weighting and thresholding-based detail preserving image enhancement of gastrointestinal images with noise suppression

Endoscopy is a widely practiced technique across the globe, utilized to envision the gastrointestinal (GI) tract of the human body without causing harm. In GI endoscopy, images affected by noise may not be helpful to support a visual diagnosis of the mucosal surface at good quality. In such advanced imaging systems, image quality enhancement becomes particularly beneficial. In this study, a non-invasive numerical method of image enhancement is examined to improve the image quality metrics as is critical in GI imaging. A unique approach of weighting and thresholding is examined in this study, where the weighting and thresholding play a significant role in image enhancement. Deviations from the proposed weighting scheme results in the reduction of the peak signal to noise ratio (PSNR) among other key metrics. The proposed method evaluated on eight datasets are expounded to produce optimal performance, particularly in that of the PSNR, entropy and contrast over the state-of-the-art (SOA) enhancement algorithms. The proposed method yields a universal image quality index of 93 %, a structural similarity of 86 % and that of 25 %, 11 %, 19 % and 30 % of PSNR, entropy, contrast, and distortion metric enhancements on average in comparison with the SOA, contributing to the improved quality of the resultant frame aiding to view image features at higher detail and overall quality, both quantitively and qualitatively. This in conjunction with higher optical magnification and faster graphics processing units (GPU’s) may be beneficial for a real-time examination of the mucosal surface of the GI tract at superior quality.

A Study of the Interpretability of Fundus Analysis with Deep Learning-Based Approaches for Glaucoma Assessment

Earlier studies focused on training ResNet50 deep learning models on a dataset of fundus images from the National Taiwan University Hospital HsinChu Branch. The study aimed to identify class-specific discriminative areas related to various conditions of ganglion cell complex (GCC) thickness, center focus areas, cropped patches from the fundus, and dataset partitions. The study utilized two visualization methods to evaluate and explain the areas of interest of the network model and determine if they aligned with clinical diagnostic knowledge. The results of the experiments demonstrated that incorporating GCC thickness information improved the accuracy of glaucoma determination. The deep learning models primarily focused on the optic nerve head (ONH) for glaucoma diagnosis, which was consistent with clinical rules. Nonetheless, the models achieved high prediction accuracy in detecting glaucomatous cases using only cropped images of macular areas. Moreover, the model’s focus on regions with GCC impairment in some cases indicates that deep learning models can identify morphologically detailed alterations in fundus photographs that may be beyond the scope of visual diagnosis by experts. This highlights the significant contribution of deep learning models in the diagnosis of glaucoma.

Few‐shot learning for dermatological conditions with Lesion Area Aware Swin Transformer

AbstractSkin is the largest organ of the human body and participates in the functional activities of the human body all the time. Therefore, human beings have a large risk of getting skin diseases. The diseased skin lesion image shows visually different characteristics from the normal skin image, and sometimes unusual skin color may indicate human viscera or autoimmune issues. However, the current recognition and classification of dermatological conditions still rely on expert visual diagnosis rather than a visual algorithm. This is because there are many kinds of lesion features of skin diseases, and the lesion accounts for a small proportion of the skin image, so it is difficult to learn the required lesion features; meanwhile, some dermatology images have too few samples to deal with the problem of small samples. In view of the above limitations, we propose a model named Lesion Area Aware Shifted windows Transformer for dermatological conditions classification rely on the powerful performance and excellent result of Swin transformer recently proposed. For brief notation, we use its abbreviation later. Our main contributions are as follows. First, we modify the Swin transformer and use it in the automatic classification of dermatological conditions. Using the self‐attention mechanism of the transformer, our method can mine more long‐distance correlations between diseased tissue image features. Using its shifting windows, we can fuse local features and global features, so it is possible to get better classification results with a flexible receptive field. Second, we use a skip connection to grasp and reinforce global features from the previous block and use Swin transformer to extract detailed local features, which will excavate and merge global features and local features further. Third, considering Swin transformer is a lightweight model compared with traditional transformers, our model is compact for deployment and more favorable to resource‐strict medical devices.

Visual Diagnosis: Time is tongue! How to rescue an ischemic tongue due to carotid artery stenosis?

Visual Diagnosis: Time is tongue! How to rescue an ischemic tongue due to carotid artery stenosis?

Triad of Microcephaly, Pedal Lymphedema, and Pigmentary Eye Changes: A Visual Diagnosis.

Triad of Microcephaly, Pedal Lymphedema, and Pigmentary Eye Changes: A Visual Diagnosis.

The Novel Digital Therapeutics Sensor and Algorithm for Pressure Ulcer Care Based on Tissue Impedance.

Visual diagnosis and rejuvenation are methods currently used to diagnose and treat pressure ulcers, respectively. However, the treatment process is difficult. We developed a biophotonic sensor to diagnose pressure ulcers and, subsequently, developed a pressure ulcer care device (PUCD.) We conducted animal and clinical trials to investigate the device's effectiveness. We confirmed the accuracy of the pressure ulcer diagnosis algorithm to be 91% and we observed an 85% reduction in immune cells when using the PUCD to treat pressure ulcer-induced mice. Additionally, we compared the treatment group to the pressure ulcer induction group to assess the PUCD's effectiveness in identifying immune cells through its nuclear shape. These results indicate a positive effect and suggest the use of PUCD as a recovery method for pressure ulcer diagnosis and treatment.

Symptom: Vertigo After Labyrinthectomy

Symptom: Vertigo After Labyrinthectomy

Особливості диференціювання хірургічної патології органів черевної порожнини і тазових органів у дівчат за допомогою ультразвукового дослідження

The issue of acute appendicitis remains extremely relevant today, as it is the most common inflammatory disease of the abdominal cavity. Despite significant advances in pediatric surgery in recent decades, when mortality from acute appendicitis is an exceptional event, the number of complicated forms in children is observed in 26.4% of cases, and morphologically unconfirmed appendectomies in 8.8% of cases. In girls, the rates are higher at the age of ≤10 years. Acute appendicitis has been and remains a very common disease in underdeveloped countries. In industrialized countries, the incidence of acute appendicitis ranges from 4-6% to 12-23%, in Ukraine - 20-21 cases per 10 thousand population, mostly young people. Purpose - to state the peculiarities of differentiation of surgical pathology of the abdominal cavity and pelvic organs in girls using ultrasound examination; to develop an algorithm for diagnosing surgical pathology in girls. Materials and methods. The study was conducted on the basis of the at the Vinnytsia Regional Children's Clinical Hospital, National Pirogov Memorial Medical University (Vinnytsia, Ukraine) for the period 2019-2021. For visual differential diagnosis, girls aged 4-16 years were involved in the study: 100 healthy children (the Group 1), 100 children diagnosed with acute phlegmonous appendicitis (the Group 2), 100 children with bulky uterine appendages of various types of pathology (the Group 3). Results and conclusions. The following advantages of ultrasound have been established: high specificity of the study, low cost and absence of ionizing radiation. Ultrasound of the abdominal cavity makes it possible to diagnose acute surgical and gynecological pathology, as well as to carry out differential diagnosis of diseases simulating acute appendicitis. An algorithm for diagnosing surgical pathology in girls has been developed. Such an algorithm increases the effectiveness of ultrasound of acute appendicitis and neoplasms of the pelvic cavity, and this allows the doctor to establish the correct diagnosis in time and choose the appropriate treatment tactics. The research was carried out in accordance with the principles of the Helsinki Declaration. The study protocol was approved by the Local Ethics Committee of the participating institution. The informed consent of the patient was obtained for conducting the studies. No conflict of interests was declared by the authors.

TOLERANCE OF MARANDU GRASS TO EXCESS IRON AND MANGANESE

In soaked soils there is an increase in the availability of iron and manganese. Thus, it becomes important to investigate the tolerance levels of plants to excess of these nutrients. The objective was to evaluate the tolerance of Urochloa brizantha cv. Marandu cultivated in nutrient solution with different levels of iron and manganese. The experimental design was completely randomized with seven treatments and four replications. The treatments consisted of a nutrient solution and consisted of: 1- adequate concentration of Fe (8.22 mM) and Mn (2.05 mM); 2– Fe, four times the adequate concentration; 3– Fe, eight times the adequate concentration; 4– Mn, four times the adequate concentration; 5– Mn, eight times the adequate concentration; 6– Fe and Mn, four times the appropriate concentration, and; 7– Fe and Mn, eight times the appropriate concentration. The variables evaluated were visual diagnosis (symptomatology), shoot height, root volume, Fe and Mn content in shoots and dry mass production. Grass plants were not tolerant to excess Fe and Mn. The excess of nutrients promoted less development of the root system, with a reduction in volume and dry mass, and the treatment with the highest dose of nutrients resulted in the lowest values. Grass plants were sensitive to the increase in nutrient concentrations, showing reductions in total dry mass production of 55% for treatment with the application of the highest concentration of nutrients in relation to the adequate dose of Fe and Mn.

A versatile AIE probe with mitochondria targeting for dual-channel detection of superoxide anion and viscosity

Abnormal viscosity and excessive superoxide anion (O2•-) levels in living cells often cause a series of biological dysfunction and oxidative damage. However, a great challenge remains in quickly and conveniently detecting the viscosity and O2•- levels in living cells. Herein, we fabricated a versatile aggregation-induced emission (AIE) probe with mitochondria targeting, DTPB, for dual-imaging of viscosity and O2•- level in living cells with two different channels. The obtained DTPB contained a diphenyl phosphinic acid unit responsive to O2•-, a unit with twisted intramolecular charge trans (TICT) function responsive to viscosity, and a pyridine cation unit with mitochondria targeting. The results showed that DTPB exhibited a remarkable response to viscosity with a near-infrared emission peak at 671 nm and was highly sensitive to O2•- levels with an emission peak at 587 nm. The dual-channel probe has great application prospects in the visual diagnosis of cancer and related diseases.

Influence of Calcium on the Development of Corn Plants Grown in Hydroponics

This work aimed to evaluate the effect of calcium on the development of corn plants grown with the omission and excess of calcium in a nutrient solution. The experiment was conducted in a greenhouse from March to May 2012. Three concentrations of calcium (0, 200, and 600 mg Ca L−1) were added to the nutrient solution, which was renewed weekly, for a total of 40 days. The following variables were measured weekly: the number of leaves, average stem diameter, dry weight of the plant shoots and roots, and visual leaf diagnosis. The results showed that when the plants were deprived of calcium, their root systems were significantly reduced, as determined by the Tukey test (p ≤ 0.05). The plants with calcium deprivation had shorter roots and a dark brown color and displayed initial symptoms of chlorosis in their young leaves, which eventually led to necrosis and tipping. Hydroponics is promising and has shown satisfactory production results, contributing to the improvement of the environment, job creation, and increased profit for rural producers.

The change of Roussouly classification after posterior lumbar fusion surgery.

Roussouly classification is an important morphologic classification which can help to determine high local stress zones of the spine. Different lumbar morphologies of Roussouly type suggest different biomechanics leading to degenerative evolution. This study aimed both to describe the change of the Roussouly classification of the human spine after posterior lumbar fusion surgery and to explore the influencing factors of postoperative Roussouly type. The study is a retrospective case-control study on preoperative and postoperative Roussouly types. A total of 167 patients with lumbar degenerative disease who had undergone short-level transforaminal lumbar interbody fusion surgery between January 2014 and December 2017 in the Department of Orthopedic Surgery, First Affiliated Hospital, Air Force Medical University, were recruited. Preoperative and postoperative general data including gender, age, follow-up time, Oswestry disability index (ODI) score, visual analogue scale (VAS) score, diagnosis, and surgical segment were recorded. Clinical parameters including pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), lumbar lordosis (LL), thoracic kyphosis (TK), and sagittal vertical axis (SVA) were measured using Surgimap software, and the Roussouly classification was assessed. This study included 86 male patients and 81 female patients with a mean age of 52.0±12.4 [14-88] years. The mean follow-up time for these patients was 11.5±6.9 months. The value of sagittal alignment parameters changed after the posterior lumbar fusion surgery, except for the PI value (P=0.591). Roussouly classification changed after surgery. The preoperative Roussouly values of preoperative PI, SS, and LL were significantly different in patients of 4 postoperative Roussouly types. The Roussouly classification changes after posterior lumbar fusion surgery. This change is independent of gender, age, follow-up time, and the number of surgical segments. The preoperative Roussouly type and PI value are essential in predicting one's postoperative Roussouly type.

Photoacoustic imaging of hidden dental caries using visible-light diode laser.

Hidden caries is a type of tooth decay that is difficult to identify through visual diagnosis because teeth with hidden caries appear normal on the tooth surface but are damaged underneath. A photoacoustic imaging system based on visible light using a diode laser with a wavelength of 532nm was developed to detect hidden caries in teeth. The results indicate that the average of acoustic intensity level for healthy teeth is -74.2±0.1dB, and the average of acoustic intensity range for teeth with hidden caries is -81.2±0.5dB. The intensity level for the caries area varies depending on the severity of caries. Based on the acoustic intensity level measured by the interaction of teeth with laser light, the photoacoustic imaging system in the study can accurately detect the presence of hidden caries and recognizethe difference between caries teeth and healthy teeth. This research can be developed into a prototype of a simple device that makes it easy to operate in dental practice.