Automated Brain Tumor Diagnosis Using Deep Residual U-Net Segmentation Model

Automated segmentation and classification of biomedical images act as a vital part of the diagnosis of brain tumors(BT).A primary tumor brain analysis suggests a quicker response from treatment that utilizes for improving patient survival rate.The location and classification of BTs from huge medicinal images database,obtained from routine medical tasks with manual processes are a higher cost together in effort and time.An automatic recognition,place,and classifier process was desired and useful.This study introduces anAutomatedDeepResidualU-Net Segmentation with Classification model(ADRU-SCM)for Brain Tumor Diagnosis.The presentedADRUSCM model majorly focuses on the segmentation and classification of BT.To accomplish this,the presented ADRU-SCM model involves wiener filtering(WF)based preprocessing to eradicate the noise that exists in it.In addition,the ADRU-SCM model follows deep residual U-Net segmentation model to determine the affected brain regions.Moreover,VGG-19 model is exploited as a feature extractor.Finally,tunicate swarm optimization(TSO)with gated recurrent unit(GRU)model is applied as a classification model and the TSO algorithm effectually tunes theGRUhyperparameters.The performance validation of the ADRU-SCM model was tested utilizing FigShare dataset and the outcomes pointed out the better performance of the ADRU-SCM approach on recent approaches.

VIMENTIN AND TUMOR DIAGNOSIS

Vimentin was isolated and purified from the pig eye lens by homogenization, ultracentrifugation, extraction in urea buffer and preparative eletrophor-esis. It was identified with SDS-PAGE and rabbit anti-vimentin was raised against the purified vimen-tin. The specificity of anti-vimentin was examined with immunohistochemical technique and double immune diffusion. Results showed that the vimentin antibody possessed good specificity for mesenchyme-derived cells. Tumor tissue sections from 151 cases were stained with anti-vimentin, anti-keratin, and-desmin, anti-S-100 protein, anti-Factor-FV Ⅲ related anti-gen, and anti-lysozyme. Positive staining was obtained in mesenchyme-derived cells, while the epithelial tumor cells did not react with anti-vimentin. It indicated that vimentin anti-body is effective for tumor differential diagnosis in surgical pathology.

Two-dimensional layered nanomaterials fortumor diagnosis and treatment

With the evolution of nanomedicine,the past decades witnessed diversified nanomaterials as marvelous antitumor tools ushering in a new era of tumor diagnosis and treatment.Among them,two-dimensional layered nano-material as an emerging class of nanomaterials has one dimension less than 100 nm,showing a high specific area and the thinnest sheet-like structure(Liu S,Pan X,Liu H.Twodimensional nanomaterials for photothermal therapy.Angew Chem Int Ed 2020;59:5890–900).The discovery of graphene drove the exploration of various new two-dimensional layered nanomaterials for tumor diagnosis and treatment including graphene-based nanomaterials,black phosphorus(BP),transition metal dichalcogenides(TMDs),layered double hydroxides(LDHs),and bismuth oxyhalides(BiOX,X=F,Cl,Br,I)(Ma H,Xue MQ.Recent advances in the photothermal applications of two-dimensional nanomaterial:photothermal therapy and beyond.J Mater Chem 2021;9:17569).On the one hand,they exhibit strong near-infrared(NIR)absorption and the capacity of optimizing corresponding properties by adjusting the crystal structure.On the other hand,they own unique strengths such as fantastic physicochemical properties(graphene-based nanomaterials),high loading capacity(BP),distinct phase-dependent optical properties(TMDs),a specific chemical response to the tumor microenvironment(LDHs),and large X-ray attenuation coefficient(BiOX).Herein,we briefly introduce three typical two-dimensional layered nanomaterials,their prospects and future research priorities in tumor diagnosis and treatment are concluded.

Laser spectroscopy imaging technique coupled withnanomaterials for cancer diagnosis: A review

Laser spectroscopic imaging techniques have received tremendous attention in the-eld of cancer diagnosis due to their high sensitivity,high temporal resolution,and short acquisition time.However,the limited tissue penetration of the laser is still a challenge for the in vivo diagnosis of deep-seated lesions.Nanomaterials have been universally integrated with spectroscopic imaging techniques for deeper cancer diagnosis in vivo.The components,morphology,and sizes of nanomaterials are delicately designed,which could realize cancer diagnosis in vivo or in situ.Considering the enhanced signal emitting from the nanomaterials,we emphasized their combination with spectroscopic imaging techniques for cancer diagnosis,like the surface-enhanced Raman scattering(SERS),photoacoustic,fluorescence,and laser-induced breakdown spectroscopy(LIBS).Applications ofthe above spectroscopic techniques offer new prospectsfor cancer diagnosis.

Magnetic Resonance Imaging for Diagnosis and Analysis of Bone Tumors and Bone Tuberculosis

The purpose of the study is to explore the diagnostic value of magnetic resonance imaging in bone tuberculosis and bone tumors.Firstly,148 patients with bone tumor and bone tuberculosis were selected,74 cases in each group.Perform magnetic resonance imaging(MRI)examinations on all patients,relevant parameters were set and the changes in the value of the dispersion system were recorded to obtain T1-weighted imaging and T2-weighted imaging.The results showed that among 74 patients,41 cases were bone damage,38 cases were joint swelling,27 cases were sparse bone,10 cases were bone hyperplasia and 5 cases were dead bone and calcification.The imaging manifestations of bone tumors were 45 cases of fractures,26 cases of surrounding soft tissue infiltration,10 cases of hip duct enlargement and 11 cases of sacral foramen enlargement.After MRI diagnosis,the accuracy of diagnosing 74 cases of bone tumor was 100%,and the accuracy of diagnosing 65 cases of bone tuberculosis was 87.84%.The difference between the two groups was statistically significant(P<0.05).The diffusion sensitivity coefficient of MRI weighted imaging was 150 s/mm2,and there was no significant difference in ADC values between the two groups(P>0.05).When the diffusion sensitivity coefficient is 300 s/mm2,and the difference between the two groups was statistically significant(P<0.05).Therefore,MRI had a certain diagnostic value for bone tuberculosis and bone tumors,and MRI had a higher diagnostic value and richer information for bone tumors.Corresponding treatment can be performed to improve the prognosis.

Diagnosis and management of pancreatic neuroendocrine tumor in von Hippel-Lindau disease

The pancreatic manifestations seen in patients with von Hippel-Lindau(VHL) disease are subdivided into 2 categories:pancreatic neuroendocrine tumors(NET),and cystic lesions,including simple cyst and serous cystadenoma.The VHL-associated cystic lesions are generally asymptomatic and do not require any treatment,unless they are indistinguishable from other cystic tumor types with malignant potential.Because pancreatic NET in VHL disease are non-functioning and have malignant potential,it is of clinical importance to find and diagnose these as early as possible.It will be recommended that comprehensive surveillance using dynamic computed tomography for abdominal manifestations,including pancreatic NET,should start from the age of 15 years in VHL patients.Unlike sporadic non-functioning NET without VHL disease,in which surgical resection is generally recommended,VHL patients at lower metastatic risk of pancreatic NET should be spared the risks of operative resection.

Efficient Computer Aided Diagnosis System for Hepatic Tumors Using Computed Tomography Scans

One of the leading causes of mortality worldwide is liver cancer.The earlier the detection of hepatic tumors,the lower the mortality rate.This paper introduces a computer-aided diagnosis system to extract hepatic tumors from computed tomography scans and classify them into malignant or benign tumors.Segmenting hepatic tumors from computed tomography scans is considered a challenging task due to the fuzziness in the liver pixel range,intensity values overlap between the liver and neighboring organs,high noise from computed tomography scanner,and large variance in tumors shapes.The proposed method consists of three main stages;liver segmentation using Fast Generalized Fuzzy C-Means,tumor segmentation using dynamic thresholding,and the tumor’s classification into malignant/benign using support vector machines classifier.The performance of the proposed system was evaluated using three liver benchmark datasets,which are MICCAI-Sliver07,LiTS17,and 3Dircadb.The proposed computer adided diagnosis system achieved an average accuracy of 96.75%,sensetivity of 96.38%,specificity of 95.20%and Dice similarity coefficient of 95.13%.

THE DIAGNOSIS OF MESENTERY TUMOR (CLINIC-PATHOLAGIC ANALYSIS OF 171 CASES)

One hundred and seventy one patients with mesentery tumors confirmed by surgery and/or pathology in five hospitals of Hubei Province from 1966 to 1986 are analyzed retrospectively. The main manifestations were abdominal pain, abdominal mass and emaciation. Cyst and leiomyomas were common in benign tumors. Malignant lymphoma, leiomyosarcoma and liposarcoma were predominant in malignant tumors. The morbidity, clinicopatholo-gic characteristics, diagnosis and differential diagnosis of this group of tumor are discussed.

The practical value of 3-dimensional computed tomography on diagnosis of bladder tumor

Objective To study the practical value of 3-dimensional computed tomography on diagnosis of bladder tumor, Methods Fifteen patients with bladder masses were examined by thin-layer computed tomography. The results of 3-dimensional reconstructed images were compared with the final diagnosis and the pathological stages. Results According to 3-dimensional reconstructed images, among the 15 cases, 12 cases of bladder cancer were diagnosed, and the pathological types were transitional carcinoma. Two cases were diagnosed as benign tumor (leiomyoma), and the other one was colon cancer, which invaded bladder. The accuracy was 100% . The clinical stages were determined. Of the 12 bladder carcinomas,5 was in stage T1, 3 in T2,, 3 in T3 and 1 in T4.The accuracy of staging was up to 83% (10/12) compared with pathological stages. Conclusion The 3-dimensional reconstructed technology may improve the accuracy of staging of bladder carcinoma, and to provide important evidence for surgery options. 3 refs,2 figs.

Diagnosis and treatment of spinal primitive neuroectodermal tumor

Objective To sum up the clinical experience in diagnosis and treatment of spinal primitive neuroectodermal tumor(PNET). Methods Thirteen patients with spinal PNET were included in the study from 1999 to 2009.There were 8 males and 5

Discussion of diagnosis and therapy strategy for pineal region tumors

Objective To define optimal diagnosis and theraputic strategy of pineal region tumors. Methods Clinicalmaterials of 154 cases with pineal region tumors were analyzed retrospectively. Results The patients with pineal region tumors often complained of increased intracranial pressure and ocular movement deficiency.

Next Generation Sequencing in Oncological Diagnostics: Hype or Hope?

The understanding of how genetic and epigenetic factors influence tumorigenesis, progression and invasion, is vastly growing since new technologies allow the analysis of the functional genome namely the exome, the transcriptome and the epigenome, besides enabling genome-wide assessment of genetic variations. With the advent of new drugs that are indicated tissue agnostic, depending on certain mutations, there is a growing demand for fast and cost-effective genetic diagnosis. The method in focus that already became an indispensable tool in viral diagnosis is next-generation sequencing (NGS). This approach allows sequencing of literally every DNA molecule in the sample and can either be used to assess numerous genetic markers of one patient at a time, or to assess fewer markers of many patients in parallel, which reduces costs. We submitted 23 samples of different tumor entities to four diagnostic companies with different analysis profiles. The results as disclosed and discussed in this report indicate that so far, the main application of NGS is rather in cancer research than in diagnosis, as none of the reports had a real impact on the therapeutic scheme. We are perfectly aware that such a small cohort cannot be generalized, but considering the costs vs. benefits, NGS should be engaged upon a very stringent evaluation only. However, in cases where obtaining a tissue biopsy is impossible or unfavorable, analysis of liquid biopsy by NGS provides a vital alternative.

Two-photon excitation fuorescence lifetime imaging microscopy:A promising diagnostic tool for digestive tract tumors

Digestive tract tumors acount for 15%and 19.3%of the cancer incidence and deaths,respec-tively.Early detection of digestive tract tumors is crucial to the reduction of global cancer burden.Two-photon excitation fuorescence lifetime imaging microscopy(TP-FLIM)allows non-invasive,label free,three-dimensional,high-resolution imaging of living tisues with not only histological but also biochemical characterization ability in both qualitative and quantitative way.Benefiting from these advantages,this technology is protmising for clinical diagnosis of digestive tract tumors.In recent years,many efforts have'been made in this field and some remarkable progress has been achieved.In this paper,we overview the recent progress of TP-FLIM-based researches on digestive tract tumor detection.Among them,our latest results on the gastric cancer and esophageal cancer are elaborately depicted.Finally,we outlook and discuss the potential advantages and challenges of TP-FLIM in future clinical applications.

Nature-Inspired Level Set Segmentation Model for 3D-MRI Brain Tumor Detection

Medical image segmentation has consistently been a significant topic of research and a prominent goal,particularly in computer vision.Brain tumor research plays a major role in medical imaging applications by providing a tremendous amount of anatomical and functional knowledge that enhances and allows easy diagnosis and disease therapy preparation.To prevent or minimize manual segmentation error,automated tumor segmentation,and detection became the most demanding process for radiologists and physicians as the tumor often has complex structures.Many methods for detection and segmentation presently exist,but all lack high accuracy.This paper’s key contribution focuses on evaluating machine learning techniques that are supposed to reduce the effect of frequently found issues in brain tumor research.Furthermore,attention concentrated on the challenges related to level set segmentation.The study proposed in this paper uses the Population-based Artificial Bee Colony Clustering(P-ABCC)methodology to reliably collect initial contour points,which helps minimize the number of iterations and segmentation errors of the level-set process.The proposed model measures cluster centroids(ABC populations)and uses a level-set approach to resolve contour differences as brain tumors vary as they have irregular form,structure,and volume.The suggested model comprises of three major steps:first,pre-processing to separate the brain from the head and improves contrast stretching.Secondly,P-ABCC is used to obtain tumor edges that are utilized as an initial MRI sequence contour.The level-set segmentation is then used to detect tumor regions from all volume slices with fewer iterations.Results suggest improved model efficiency compared to state-of-the-art methods for both datasets BRATS 2019 and BRATS 2017.At BRATS 2019,dice progress was achieved for Entire Tumor(WT),Tumor Center(TC),and Improved Tumor(ET)by 0.03%,0.03%,and 0.01%respectively.At BRATS 2017,an increase in precision for WT was reached by 5.27%.

Application of Multimodality Imaging Fusion Technology in Diagnosis and Treatment of Malignant Tumors under the Precision Medicine Plan

Objective： The arrival of precision medicine plan brings new opportunities and challenges for patients undergoing precision diagnosis and treatment of malignant tumors. With the development of medical imaging, information on different modality imaging can be integrated and comprehensively analyzed by imaging fusion system. This review aimed to update the application of multimodality imaging fusion technology in the precise diagnosis and treatment of malignant tumors under the precision medicine plan. We introduced several multimodality imaging fusion technologies and their application to the diagnosis and treatment of malignant tumors in clinical practice. Date Sources： The data cited in this review were obtained mainly from the PubMed database from 1996 to 2016, using the keywords of ＂precision medicine＂, ＂fusion imaging＂, ＂multimodality＂, and ＂tumor diagnosis and treatment＂. Study Selection： Original articles, clinical practice, reviews, and other relevant literatures published in English were reviewed. Papers focusing on precision medicine, fusion imaging, multimodality, and tumor diagnosis and treatment were selected. Duplicated papers were excluded. Results： Multimodality imaging fusion technology plays an important role in tumor diagnosis and treatment under the precision medicine plan, such as accurate location, qualitative diagnosis, tumor staging, treatment plan design, and real-time intraoperative monitoring. Multimodality imaging fusion systems could provide more imaging information of tumors from different dimensions and angles, thereby offing strong technical support for the implementation of precision oncology. Conclusion： Under the precision medicine plan, personalized treatment of tumors is a distinct possibility. We believe that multimodality imaging fusion technology will find an increasingly wide application in clinical practice.

Self-adaptive non-covalent albumin-binding near-infrared probe conjugates enabling precise sentinel lymph node metastasis illumination and primary tumor imaging

Tumor sentinel lymph node(SLN)metastasis plays a vital role in tumor staging and therapeutic decision-making process.However,precise diagnosis of primary tumors and lymphatic metastases is still hindered by low imaging resolution and poor photostability of fluorescent probes.Herein,we report three novel IR820-fatty acid(FA)conjugates(IR-OA,IR-LA,and IR-PA)for precise lymphatic metastasis illumination and primary tumor diagnosis.The IR-FA conjugates are able to non-covalently bound to albumin in vivo,and the fluorescence quantum yield is significantly enhanced after incubation with bovine serum albumin(BSA)in vitro.Moreover,the BSA-IR-FA conjugates display large Stokes shift(>120 nm),dramatically improving in vivo imaging resolution.Among them,IR-PA demonstrates distinct advantage over IR-OA,IR-LA,and IR-maleimide(MAL)(fluorescent probe previously reported by our group)in terms of fluorescence quantum yield,photostability,and imaging resolution.As a result,IR-PA exhibits satisfactory imaging results with high fluorescence intensity and imaging resolution in sentinel lymph node metastasis illumination and primary tumor location.Our findings provide a self-adaptive albumin-binding near-infrared probe conjugate for accurate diagnosis of primary tumors and lymphatic metastases.

Rational design of a turn-on fluorescent probe for visualization of GRP78 protein in tumor models

Fluorescence image for accurate tumor label still faces challenges in cancer detection and diagnostics.Emerging evidence is indicating that glucose-regulated protein 78(GRP78), a stress-inducible protein chaperone, is a great potential biomarker and therapeutic target for cancer. However, currently available probe for image tumor based on GRP78 has not been reported, owning to no obvious strategy in probe design towards this protein. In this paper, a hairpin-shaped peptidyl probe(pep FAM) conjugated with a 5-FAM fluorophore and a dabcyl quencher at both ends was developed, respectively. The probe was designed by performing a traditional fluorescence resonance energy transfer mechanism and employing a GRP78 specifically-binding peptide. Furthermore, the probe was used to specifically image cancer cells,and accurately image xenograft tumors in mice models. The novel fluorescent probe is expected to be a useful tool for the diagnostics of cancer.

Sandwich ELISA for detecting urinary Survivin in bladder cancer

Objective： Survivin as a tumor marker in the diagnosis of bladder cancer has not been completely confirmed yet and there are few reports about using Survivin enzyme-linked immunosorbent assay （ELISA） kit to detect the urine of bladder cancer patients. This study aimed to develop a Survivin ELISA and validate its value in the detection of bladder cancer. Methods： Through square matrix titration, different combinations of coating antibody and detecting antibody, a Survivin ELISA was constructed. This assay was evaluated according to intra-assay precision, inter-assay precision and minimum detectable dose （MDD）. Survivin levels were detected and analyzed in 102 bladder cancer patients and 102 healthy people by established ELISA. Then cutoff value was defined according to the analysis of receiver operating characteristic （ROC） curve. The sensitivity and specificity of detection were calculated on the basis of cutoff value to diagnose bladder cancer patients. Furthermore, the value of Survivin expression detected by ELISA among different clinicopathological characteristics of patients was also compared. Results： Through optimization of different conditions, intra-assay precision was 8.39%, inter-assay precision 8.57% and MDD 0.0625 ng/mL in this assay. When the optical density at 450 nm （OD 450 ） was 0.09, it could get the optimized diagnostic cutoff value. According to this value, the sensitivity and specificity of diagnosis in bladder cancer patients were 70.6% and 89.2%, respectively. The associations between patients＇ clinical variables and OD 450 were not significant except tumor numbers in patients. Conclusions： This experiment has preliminarily developed a Survivin ELISA and confirmed Survivin as a biomarker which owned a practical and significant value in the diagnosis of bladder cancer.

CURRENT MEANS IN THE DIAGNOSIS AND TREATMENT OF ORAL AND MAXILLOFACIAL TUMORS IN CHINA

Oral and maxillofacial tumors (OMT) constitute a great number in tumors of head and neck as a whole. The incidence of OMT in China is rather low. but. owing to our big population, the absolute number of the patients is high. The diagnosis and treatment of OMT in China with special emphasis on malignancies are briefly introduced below.