Diagnosis Of Precancerous Lesions Research Articles

Usability of a smartphone-compatible, confocal micro-endoscope for cervical cancer screening in resource-limited settings

BackgroundMore efficient methods to detect and treat precancerous lesions of the cervix at a single visit, such as low-cost confocal microscopy, could improve early diagnosis and hence outcomes. We piloted a prototype smartphone-compatible confocal micro-endoscope (SCME) among women presenting to a public cervical cancer screening clinic in Kampala, Uganda. We describe the piloting of the SCME device at an urban clinic used by lower cadre staff.MethodsWe screened women aged 18 and 60 years, who presented for cervical cancer screening at the Kawempe National Referral Hospital Kampala, and evaluated the experience of their providers (nurses). Nurses received a 2-day training by the study doctors on how to use the SCME, which was added to the standard Visual Inspection with Acetic acid (VIA)-based cervical cancer screening. The SCME was used to take colposcopy images before and after VIA at positions 12 and 6 O’clock if VIA negative, and on precancer-suspicious lesions if VIA positive. We used questionnaires to assess the women’s experiences after screening, and the experience of the nurses who operated the SCME.ResultsBetween November 2021 and July 2022, we screened 291 women with a median age of 36 years and 65.7% were HIV positive. Of the women screened, 146 were eligible for VIA, 123 were screened with the SCME, and we obtained confocal images from 103 women. Of those screened with the SCME, 60% found it comfortable and 81% were willing to screen again with it. Confocal images from 79% of the women showed distinguishable cellular features, while images from the remaining 21% were challenging to analyze. Nurses reported a mean score of 85% regarding the SCME’s usefulness to their work, 71% regarding their satisfaction and willingness to use it again, 63% in terms of ease of use, and 57% concerning the ease of learning how to operate the SCME.ConclusionOur findings demonstrate the feasibility of using the SCME by lower cadre staff in low-resource settings to aid diagnosis of precancerous lesions. However, more work is needed to make it easier for providers to learn how to operate the SCME and capture high-quality confocal images.

DIFFERENCES IN CHANGES IN KNOWLEDGE OF WOMEN ABOUT EARLY DETECTION OF CERVICAL CANCER BETWEEN USING PRESENTATION MEDIA COUNSELING AND LEAFLET COUNSELING

Background: Encouraging early detection and prompt treatment of precancerous lesions is the key to preventing cervical cancer in women who are fertile. IVA examinations are used to detect precancerous lesions early on. Thus far, both nationally and at Mojo Health Center, the IVA examination has been achieved. Women of reproductive age may not be as aware of early diagnosis of precancerous lesions as they should be, which could contribute to the low IVA examination achievement. Due to a lack of understanding regarding the early diagnosis of precancerous lesions, women of reproductive age have low awareness. Method: A lecture and leafleting approach were used to conduct this health counseling. This kind of study uses a quasi-experimental pretest-posttest one group design, which is experimental in nature. carried out in Surabaya City at the Mojo Health Center. A straightforward random sampling methodology was used to choose the sample of 84 WUS, who were then split into two groups: the treatment group, which received an intervention counseling lecture style, and the control group, which received a leaflet intervention. A questionnaire was utilized to collect the data, and the Wilcoxon signed rank test was used to evaluate it. Independent Samples Test (p<0.05) and Wilcoxon signed Rank test. Results: The test results showing variations in both groups' knowledge levels produced the result p = 0.000 (p <0.05). P = 0.268 (p>0.05) was the outcome of the test to determine the value of differences in knowledge factors between the treatment group and the control group. Conclusion: There is no difference in WUS knowledge between the lecture method and leaflet media distribution when it comes to counseling, but there is a shift in the outcomes of WUS knowledge about early detection of cervical cancer before and after receiving counseling.

Detection of chromosomal instability using ultrasensitive chromosomal aneuploidy detection in the diagnosis of precancerous lesions of gastric cancer.

The diagnosis of Precancerous Lesions of Gastric Cancer (PLGC) is challenging in clinical practice. We conducted a clinical study by analyzing the information of relevant chromosome copy number variations (CNV) in the TCGA database followed by the UCAD technique to evaluate the value of Chromosomal Instability (CIN) assay in the diagnosis of PLGC. Based on the screening of gastric cancer related data in TCGA database, CNV analysis was performed to explore the information of chromosome CNV related to gastric cancer. Based on the gastroscopic pathology results, 12 specimens of patients with severe atrophy were screened to analyze the paraffin specimens of gastric mucosa by UCAD technology, and to explore the influence of related factors on them. The results of CNV in TCGA database suggested that chromosome 7, 8, and 17 amplification was obvious in patients with gastric cancer. UCAD results confirmed that in 12 patients with pathologic diagnosis of severe atrophy, five of them had positive results of CIN, with a positive detection rate of 41.7%, which was mainly manifested in chromosome seven and chromosome eight segments amplification. We also found that intestinalization and HP infection were less associated with CIN. And the sensitivity of CIN measurement results was significantly better than that of tumor indicators. The findings suggest that the diagnosis of PLGC can be aided by UCAD detection of CIN, of which Chr7 and 8 may be closely related to PLGC.

Correlation of VIA Positive Cases with Colposcopic and Histopathological Findings in Diagnosis of Precancerous Lesion of Cervix in A Tertiary Care Hospital

Background: Cervical cancer prevention strategies are evolving by integrating new screening modalities such as human papillomavirus (HPV) DNA testing and visual inspection with acetic acid (VIA). Colposcopy, as a diagnostic tool, plays a crucial role in the management of abnormal cytology smears, especially in developed countries. However, its utilization and efficacy in resource-limited settings like Bangladesh remain underexplored. Objective: This study aimed to assess the correlation between VIA positivity and colposcopic/histopathological findings in diagnosing precancerous cervical lesions among women in Bangladesh. Method: A cross-sectional study was conducted among 200 women aged 30-60 attending the Gynecology OPD of Dhaka Medical College and Hospital. VIA positivity was determined, and all positive cases underwent colposcopic evaluation. Histopathological examination was performed for tissue samples obtained during colposcopy. Result: Among the participants, 21% were VIA-positive. Colposcopic evaluation revealed inflammation (26.2%), CIN I (38.1%), CIN II (11.1%), CIN III (9.5%), and invasive carcinoma (9.5%). Histopathology findings included inflammation (28.6%), CIN I (40.5%), CIN II (7.1%), and invasive carcinoma (16.7%). True positive and false positive cases were identified, with percentages calculated accordingly. Conclusion: Detailed colposcopic evaluation with guided biopsy is crucial for detecting pre-invasive and early cervical cancer. Integrating colposcopy into screening programs in Bangladesh could significantly reduce morbidity and mortality among young women.

Gastric Section Correlation Network for Gastric Precancerous Lesion Diagnosis.

Goal: Diagnosing the corpus-predominant gastritis index (CGI) which is an early precancerous lesion in the stomach has been shown its effectiveness in identifying high gastric cancer risk patients for preventive healthcare. However, invasive biopsies and time-consuming pathological analysis are required for the CGI diagnosis. Methods: We propose a novel gastric section correlation network (GSCNet) for the CGI diagnosis from endoscopic images of three dominant gastric sections, the antrum, body and cardia. The proposed network consists of two dominant modules including the scaling feature fusion module and section correlation module. The front one aims to extract scaling fusion features which can effectively represent the mucosa under variant viewing angles and scale changes for each gastric section. The latter one aims to apply the medical prior knowledge with three section correlation losses to model the correlations of different gastric sections for the CGI diagnosis. Results: The proposed method outperforms competing deep learning methods and achieves high testing accuracy, sensitivity, and specificity of 0.957, 0.938 and 0.962, respectively. Conclusions: The proposed method is the first method to identify high gastric cancer risk patients with CGI from endoscopic images without invasive biopsies and time-consuming pathological analysis.

Surgical Treatment for Early Cervical Cancer in the HPV Era: State of the Art.

Cervical cancer (CC) is the fourth most common cancer among women worldwide. The aim of this study is to focus on the state of the art of CC prevention, early diagnosis, and treatment and, within the latter, the role of surgery in the various stages of the disease with a focus on the impact of the LACC study (Laparoscopic Approach to Cervical Cancer trial) on the scientific debate and clinical practice. We have discussed the controversial application of minimally invasive surgery (MIS) for tumors < 2 cm and the possibility of fertility-sparing surgery on young women desirous of pregnancy. This analysis provides support for surgeons in the choice of better management, including patients with a desire for offspring and the need for sentinel node biopsy (SNB) rather than pelvic lymphadenectomy for tumors < 4 cm, and without suspicious lymph nodes' involvement on imaging. Vaccines and early diagnosis of pre-cancerous lesions are the most effective public health tool to tackle cervical cancer worldwide.

Characterization of an OCT probe for use in the diagnosis of precancerous lesions of the cervix

The development of an auxiliary diagnostic tool (OCT probe) for application in the assessment of cervical cancer is being carried out and may have an impact on the diagnostic process and, consequently, on the reduction of the incidence of female mortality from cervical cancer, by allowing a more accurate assessment of the extent of the lesion and by enabling the expansion of this assessment within the endocervical canal. In addition to the scientific result, the use of available equipment will boost the quality of clinical care currently available for diagnosis. Combining technical development with a precise methodology and clinical application, the probe developed will have a scientific impact of socio-economic relevance for society. As it is an optical measurement, it is necessary to evaluate the optical characteristics of the developed probes and the choice of one of them was made taking into account the measurements carried out and the application of metrological concepts.

OP12.01: Application of the novel predicting model in the auxiliary diagnosis of precancerous lesions of the cervix

OP12.01: Application of the novel predicting model in the auxiliary diagnosis of precancerous lesions of the cervix

Early Screening of Colorectal Precancerous Lesions Based on Combined Measurement of Multiple Serum Tumor Markers Using Artificial Neural Network Analysis.

Many patients with colorectal cancer (CRC) are diagnosed in the advanced stage, resulting in delayed treatment and reduced survival time. It is urgent to develop accurate early screening methods for CRC. The purpose of this study is to develop an artificial intelligence (AI)-based artificial neural network (ANN) model using multiple protein tumor markers to assist in the early diagnosis of CRC and precancerous lesions. In this retrospective analysis, 148 cases with CRC and precancerous diseases were included. The concentrations of multiple protein tumor markers (CEA, CA19-9, CA 125, CYFRA 21-1, CA 72-4, CA 242) were measured by electrochemical luminescence immunoassays. By combining these markers with an ANN algorithm, a diagnosis model (CA6) was developed to distinguish between normal healthy and abnormal subjects, with an AUC of 0.97. The prediction score derived from the CA6 model also performed well in assisting in the diagnosis of precancerous lesions and early CRC (with AUCs of 0.97 and 0.93 and cut-off values of 0.39 and 0.34, respectively), which was better than that of individual protein tumor indicators. The CA6 model established by ANN provides a new and effective method for laboratory auxiliary diagnosis, which might be utilized for early colorectal lesion screening by incorporating more tumor markers with larger sample size.

Current Concepts of Precancerous Lesions of Hepatocellular Carcinoma: Recent Progress in Diagnosis

The most common cause of hepatocellular carcinoma (HCC) is chronic hepatitis and cirrhosis. It is proposed that precancerous lesions of HCC include all stages of the disease, from dysplastic foci (DF), and dysplastic nodule (DN), to early HCC (eHCC) and progressed HCC (pHCC), which is a complex multi-step process. Accurately identifying precancerous hepatocellular lesions can significantly impact the early detection and treatment of HCC. The changes in high-grade dysplastic nodules (HGDN) were similar to those seen in HCC, and the risk of malignant transformation significantly increased. Nevertheless, it is challenging to diagnose precancerous lesions of HCC. We integrated the literature and combined imaging, pathology, laboratory, and other relevant examinations to improve the accuracy of the diagnosis of precancerous lesions.

POSSIBILITIES OF CYTOLOGICAL DIAGNOSIS OF LUNG CANCER. REVIEW

Lung cancer (LC) occupies a leading place in the structure of morbidity and mortality among patients with cancer worldwide, which determines LC as an important medical and social problem for health systems. LC is detected in more than two thirds of patients at a late stage, which determines the low success of therapy and low survival rates, and also actualizes the need to use effective methods (including morphological) for the diagnosis of LC in the early stages. Due to the development of the minimally invasive vector of morphological diagnostics in recent decades, cytological examination of the material from the bronchopulmonary system is of leading importance, since it is characterized not only by low traumatism in obtaining cellular material, but also by high information content, cost-effectiveness, accessibility and speed of obtaining results. The effectiveness of cytological examination for the diagnosis of precancerous lesions and LC has been proven in numerous studies, and the importance and necessity of its use are reflected in the new edition of the WHO classification of tumors of thoracic localization (2021) and the WHO reporting system for lungs Cytopathology (2022).

Automatic classification of gastric lesions in gastroscopic images using a lightweight deep learning model with attention mechanism and cost-sensitive learning

Magnification endoscopy with narrow-band imaging (ME-NBI) technology is widely used in the early diagnosis of precancerous lesions and gastric cancer, which is critical to reducing the incidence of gastric cancer and improving the survival rate of gastric cancer patients. The diagnosis based on ME-NBI image is mostly in manual way in clinics. In order to improve its objectivity and efficiency, here we proposed a lightweight attention mechanism deep learning model to automatically classify ME-NBI images for artificial intelligence (AI) diagnosis of early gastric cancer, low-grade intraepithelial neoplasia, and non-neoplasm. We collected 4,098 images from 990 patients for model training and validation and evaluated the performance of our model by comparisons with that of other models, such as the benchmark model. An additional 587 images from 296 patients were collected as an independent test set to further evaluate our method’s performance. The validation set showed that the overall accuracy, recall, precision, F1 score, and the area under the curve of our method were higher than those of other methods. The independent test set showed that our method achieved state-of-the-art classification for low-grade intraepithelial neoplasia (accuracy = 93.9%, sensitivity = 92.6%). Our method displayed the advantages of lightweight and high effectiveness in classifying effectiveness, which is the potential for AI diagnosis of early gastric cancer, low-grade intraepithelial neoplasia, and non-neoplasm.

Optimization of examination methods in the diagnosis of precancerous and malignant oral mucosal lesions

Relevance. The prevalence of oral mucosal diseases among the Russian population varies from 3% to 20% [7]. Precancerous and malignant diseases are a particular problem. More than nine thousand new cases of malignant oral mucosal lesions are registered annually in the Russian Federation, and yearly mortality rates reach 34%. Unfortunately, despite being externally located, the rate of late-diagnosed malignant oral mucosal neoplasms reaches 60%-70% in various regions of the Russian Federation [2]. Thus, one of the most urgent problems in dentistry and oncology is the early diagnosis of precancerous and malignant oral mucosal lesions. As a rule, precancerous lesions are not diagnosed at an early stage since there are no visible clinical signs, and therefore patients do not seek medical attention [8]. An accurate diagnosis requires both basic and additional examination methods. In turn, the conventional methods include traditional inspection, which largely depends on the clinician's experience. Besides the clinical examination, additional techniques are used, namely, fluorescence examination and biopsy [9-11]. Subsequently, optimizing the diagnosis of oral mucosal lesions is the most promising direction in practical healthcare, both in the dental and oncology practice, for early detection and reduction of advanced stages of malignant oral mucosal lesions. Thus, the study confirmed that the development and application of modern approaches are necessary for the early diagnosis of oral mucosal lesions. Purpose. The study aimed to improve the outcome of oral mucosal precancerous and malignant lesion diagnosis by upgrading examination methods. Material and methods. The study included 147 patients with oral mucosal lesions, referred to the oncologists of Samara regional clinical oncology centre by the city polyclinics. The patients were divided into two groups according to the examination methods. The control group patients, 63 people, had a conventional examination by a dentist (patient interview, inspection, palpation) and an incisional biopsy by an oncologist. The main group consisted of 84 patients, who, besides conventional dental examination, were evaluated by a new – developed and put into practice – technique with point and index score and subsequent incisional biopsy performed by an oncologist. The studied patients were comparable by gender, age and localization. The study assessed the effectiveness of the new method for the diagnosis of precancerous lesions (PL) and malignant lesions (ML) by matching the Need for Histology Verification Index (NHVI) value equal to 5 points or more and histopathology results.Results. In the main group, 71 out of 84 patients scored 5 or more according to the new method, and 13 patients scored less than 5. Patients with a low score had a non-surgical treatment, 11 patients reached remission, and two patients were referred to an oncologist for a biopsy, which confirmed oral mucosa PL and ML. The patient complaints in both groups demonstrated that pain and bleeding were more frequent in the control group compared to the main one. The evaluation of clinical examination data revealed more erosions in the control group and nonremovable plaque and hyperplasia in the main group. The incisional biopsy detected more PL and ML in the main group (p = 0.001), and early malignant lesions were in 23% versus 5% in the control group. The new method specificity in oral mucosal PL and ML diagnosis was 55%, sensitivity – 97%, accuracy – 87%, whereas the conventional examination specificity was 28%, sensitivity – 84%, and accuracy – 60%.Conclusion. The administered improved method for examination of patients with oral mucosal lesions and the compulsory use of autofluorescence examination and risk factor score assessment allowed us to identify PL and ML in 88% and to diagnose more PL and ML at early stages, which explains the need to use this method in the clinical practice for the early diagnosis of lesions.

Diagnostic Value of Endoscopic Narrow-Band Imaging Technique in Early Gastric Cancer and Precancerous Lesions.

Objective To investigate the diagnostic value of endoscopic narrow-band imaging technique in early gastric cancer and precancerous lesions. Methods A total of 100 patients with recurrent upper gastrointestinal symptoms in our hospital from January 2017 to January 2022 were selected and divided into group A and group B according to the random number table method, with 50 cases in each group. Group A received white light endoscopy, and group B received narrow-band imaging technology combined with endoscopy. Narrow-band imaging combined with magnifying endoscopy was used to stain the area with suspicious mucosal lesions with indigo carmine and magnified observation. Results The endoscopic image clarity of group B was significantly better than that of group A in terms of lesion outline, gastric pit, and microvascular morphology (P < 0.05). There were 10 cases of early gastric cancer, 18 cases of benign lesions, and 9 cases of gastric cancer (nonearly stage); 17 cases of precancerous lesions, 12 cases of early gastric cancer, 13 cases of benign lesions, and 6 cases of gastric cancer (nonearly stage) were diagnosed by ordinary white light endoscopy. Pathological results confirmed that among the 50 patients in group B, there were 15 cases of precancerous lesions, 11 cases of early gastric cancer, 17 cases of benign lesions, and 7 cases of gastric cancer (nonearly stage). Among the 50 patients in group A, 16 were precancerous lesions, 11 were early gastric cancer, 15 were benign lesions, and 8 were gastric cancer (non early stage). In the diagnosis of precancerous lesions and early gastric cancer, the diagnostic consistency, sensitivity, and specificity of group B were better than those of group A (P < 0.05); NBI combined with endoscopy in the diagnosis of precancerous lesions and early gastric cancer (kappa = 0.860, kappa = 0.883) was more consistent with pathological diagnosis than common white light endoscopy (kappa = 0.433, kappa = 0.535). Conclusion The value of narrow-band imaging technology combined with endoscopy in the diagnosis of precancerous lesions and early gastric cancer is better than that of ordinary white light endoscopy, and it can be widely used in clinical practice.

A hyperspectral dataset of precancerous lesions in gastric cancer and benchmarks for pathological diagnosis.

Gastric cancer (GC) is one of the most common cancers worldwide. A lot of studies have found that early GC has good prognosis. Unfortunately, the diagnosis rate of early GC is suboptimal due to inadequate disease screening and the insidious nature of early lesions. Pathological diagnosis is usually regarded as the "gold standard" for the diagnosis of GC. However, traditional pathological diagnosis is tedious and time-consuming. With the development of deep learning, computer-aided diagnosis is widely used to assist pathologists for diagnosis. As conventional pathology, diagnosis is based on color images, it is not as informative as hyperspectral imaging, which introduces spectroscopy into imaging techniques. This article combines microscopic hyperspectral image (HSI) with deep learning networks to assist in the diagnosis of precancerous lesions in gastric cancer (PLGC). A large scale microscopic hyperspectral PLGC dataset with 924 effective scenes is built and self-supervised learning is adopted to provide pretrained models for HSI. These pretrained models effectively improve the performance of downstream classification tasks. Furthermore, a symmetrically deep connected network is proposed to train with images from different imaging modalities and improve the diagnostic accuracy to 96.59%.

Micronucleus assay in the exfoliated cells of buccal mucosa of gasoline station workers in Tehran.

One of the most critical landmarks of DNA damage is the micronucleus assay. Enumeration of micronuclei contributes to the early diagnosis of precancerous lesions and cancers; however, there are few studies on the frequency of micronucleus in gasoline station workers. To the best of our knowledge, no study has addressed this issue in Iran. The present study aimed to determine the role of working in the gasoline stations of Tehran city on micronucleus frequency in buccal mucosa. In this historical cohort study, buccal mucosa samples were collected from 110 individuals working at gasoline stations and 100 unemployed persons using wet tongue depressors. After Papanicolaou staining, the percentage of cells containing micronucleus as well as the mean number of micronucleus in the micronucleated cells was reported. Student's t-test, Mann-Whitney test, and regression analyses were used to specify the effect of other variables on the frequency and mean number of micronucleus per cell. The mean frequency of micronucleus in the case and control group was 29.8 ± 8.2 and 9.3 ± 3.2, respectively, which was statistically significant (P = 0.0001). Furthermore, the mean number of micronucleus in the micronucleated cells of buccal mucosa was significantly higher in individuals who were exposed to gasoline than the control group (P = 0.0001). The results indicated that exposure to gasoline could increase the frequency of micronucleus. It was also revealed that cigarette and hookah smoking and alcohol consumption, together with working in gasoline stations, increase micronucleus abundance, implying the cumulative carcinogenic effect of these factors.

Diagnostic test of dynamic computed tomography in early gastrointestinal lymphoma and precancerous lesions.

BackgroundIn recent years, with the development of imaging technology, the accurate diagnosis of precancerous lesions of digestive system and early lymphoma has attracted wide attention in the medical field.MethodsIn this study, 82 patients with gastrointestinal diseases, including 32 patients with early gastrointestinal lymphoma and 50 patients with gastrointestinal precancerous lesions, underwent dynamic contrast-enhanced computed tomography (CT) scanning. The difference (δ1, δ2) and ratio (Q1, Q2) of density between arterial phase, portal phase and plain scan were measured and compared, and the receiver operating characteristic (ROC) curve of the subjects was drawn.ResultsThe results showed no statistically significant differences in the general condition of patients or a difference for the results of the arterial phase δ1 and Q1 between the two groups (P>0.05). However, the portal venous phase δ2 and Q2 in the early lymphoma group and in precancerous lesion group were 29.50±6.05, 41.55±10.10 Hounsfield units (HU), and 1.70±0.05, 2.06±0.31, respectively. The area under the ROC curve (AUC) values for δ2 and Q2 to identify the two diseases were 0.755 and 0.878, respectively. When δ2 and Q2 were 35.63 and 1.86 HU, the specificity was 89.60% and 67.50%, and sensitivity was 89.60% and 64.90%, respectively. When the two indexes, δ2 and Q2, were combined, the specificity and sensitivity of diagnosis were 98.99% and 56.80%, respectively.ConclusionsDynamic contrast-enhanced CT can effectively distinguish early gastrointestinal lymphoma from precancerous lesions and improve the diagnostic accuracy.

Using Quantitative Imaging for Personalized Medicine in Pancreatic Cancer: A Review of Radiomics and Deep Learning Applications

Simple SummaryWith a five-year survival rate of only 3% for the majority of patients, pancreatic cancer is a global healthcare challenge. Radiomics and deep learning, two novel quantitative imaging methods that treat medical images as minable data instead of just pictures, have shown promise in advancing personalized management of pancreatic cancer through diagnosing precursor diseases, early detection, accurate diagnosis, and treatment personalization. Radiomics and deep learning methods aim to collect hidden information in medical images that is missed by conventional radiology practices through expanding the data search and comparing information across different patients. Both methods have been studied and applied in pancreatic cancer. In this review, we focus on the current progress of these two methods in pancreatic cancer and provide a comprehensive narrative review on the topic. With better regulation, enhanced workflow, and larger prospective patient datasets, radiomics and deep learning methods could show real hope in the battle against pancreatic cancer through personalized precision medicine.As the most lethal major cancer, pancreatic cancer is a global healthcare challenge. Personalized medicine utilizing cutting-edge multi-omics data holds potential for major breakthroughs in tackling this critical problem. Radiomics and deep learning, two trendy quantitative imaging methods that take advantage of data science and modern medical imaging, have shown increasing promise in advancing the precision management of pancreatic cancer via diagnosing of precursor diseases, early detection, accurate diagnosis, and treatment personalization and optimization. Radiomics employs manually-crafted features, while deep learning applies computer-generated automatic features. These two methods aim to mine hidden information in medical images that is missed by conventional radiology and gain insights by systematically comparing the quantitative image information across different patients in order to characterize unique imaging phenotypes. Both methods have been studied and applied in various pancreatic cancer clinical applications. In this review, we begin with an introduction to the clinical problems and the technology. After providing technical overviews of the two methods, this review focuses on the current progress of clinical applications in precancerous lesion diagnosis, pancreatic cancer detection and diagnosis, prognosis prediction, treatment stratification, and radiogenomics. The limitations of current studies and methods are discussed, along with future directions. With better standardization and optimization of the workflow from image acquisition to analysis and with larger and especially prospective high-quality datasets, radiomics and deep learning methods could show real hope in the battle against pancreatic cancer through big data-based high-precision personalization.

Cervical precancerous lesions at the Tchibanga Regional Hospital and the University Hospital in Gabon in 2018: smartphone as a screening tool for diagnosis.

Cervical precancerous lesions are disorders that can induce discolouration changes. Their detection is difficult in remote areas in the absence of adequate equipment. The objectives were to evaluate Smartphone performance in diagnosing cervical precancerous lesions in Tchibanga, Gabon. It was an interventional cross-sectional study to evaluate the validity and reliability of the smartphone as a tool for diagnosing atypical changes in the cervix. Study period was between July 1, 2017 to February 28, 2018 at the Tchibanga Regional Hospital (CHRT) and the University Hospital (CHU). The variability between examiners was determined according to Cohen's Kappa formula. The Gold standard test was the cytology. Compared to the examiner -1, the examiner - 2 found a high percentage of inflammations as atypical transformations : 15.3% versus 9%. With regard to smartphonic impressions, the examiner-1 found the normal impressions almost equal to that of the examiner-2, 72.9% versus 72.2%. The concordance between positive smartphonic impressions was 93.8% and 95.5% between negative smartphonic impressions, with k = 0.86. In view of the above, the concordance between positive and negative smart phonic impressions was 93.8 and 95.5% with k = 0.86. The performance parameters being good, there is a need to use the smartphone as a tool for the diagnosis of precancerous lesions.

Human papillomavirus E6E7 mRNA and TERC lncRNA in situ detection in cervical scraped cells and cervical disease progression assessment

BackgroundHuman papillomavirus screen in female cervical cells has demonstrated values in clinical diagnosis of precancerous lesions and cervical cancers. Human papillomavirus tests of cervical cells by utilizing Polymerase Chain Reaction (PCR) method provides human papillomavirus infection status however no further virus in situ information. Although it is well known that the tests of human papillomavirus E6/E7 RNA location in infected cervical cells and cell internal malignancy molecular will provide clues for gynecologists to evaluate disease progression, there are technique difficulties to preserve RNAs in cervical scraped cells for in situ hybridization.MethodsIn current study, after developing a cervical cell collection and preparation method for RNA in situ hybridization, we captured the chance to screen 98 patient cervical cell samples and detected human papillomavirus E6/E7 mRNAs of high-risk subtypes, low-risk subtypes and long non-coding RNA (lncRNA) TERC in the cells.ResultsThere were 69 samples exhibited consistence between human papillomavirus PCR and human papillomavirus RNA in situ hybridization results in cervical collected cells. Among them, 23 were both positive and 46 were both negative. In the rest 29 samples, 8 were HPV RNAscope positive, either high risk or low risk subtypes, however HPV PCR negative. Another 9 samples were HPV PCR results positive whereas RNAscope negative. The last 12 samples were HPV positive detected by both RNAscope and PCR methods, however inconsistent between high-risk and low-risk subtypes. In RNAscope positive samples, viral E6/E7 mRNAs were observed to distribute in cervical scraped cell nucleus and cytoplasm. Moreover, HPV viral RNA gathered clusters were observed outside of cells through human papillomavirus RNA in situ hybridization detection. Varied numbers of human papillomavirus infective cells were detected by RNAscope assay in different patients even though they were all human papillomavirus high-risk subtype positive discovered by human papillomavirus PCR results. A cell malignancy related long non-coding RNA, TERC, has been detected in seven patient samples. The patient follow-up information was further analyzed with RNAscope results which indicated a combination of RNAscope positive signals of TERC and human papillomavirus high risk signals in more than 10 cells (cytoplasm or nucleus) may connect with cervical lesion fast progression which deserves further studies in the future.CConclusionsTaken together, current study has provided an observable clue for gynecologists to evaluate human papillomavirus infection stage and cell malignancy status which may contribute for assessment of cervical disease progression.