Detection Of Malignant Tumors Research Articles

Evaluation of 99m Tc-3PRGD2 SPECT imaging on angiogenesis in animal models of lung cancer.

The main purpose of the study was to evaluate the activity and selectivity of 99m Tc-3PRGD2 SPECT/CT and 18 F-FDG PET-CT in order to detect the neovascularization of A549 cell subcutaneously transplanted tumors, and clarify the relationship among tumor vasculature, hypoxia and cell proliferation in the tumor microenvironment. We established a subcutaneous tumor model, and used 99m Tc-3PRGD2 SPECT/CT and 18 F-FDG PET-CT when the average tumor size reached 0.3-0.5cm3 . The mice were anesthetized and sacrificed and the tumors were completely removed for frozen section analysis. We subsequently evaluated the status of neovascularization, hypoxia, as well as cell proliferation via immunofluorescence staining (IF) by detecting CD31, pimonidazole and EdU, respectively. There was a significant positive correlation (r=0.88, p < 0.05) between the microvascular density (41.20 ± 18.60) and tumor to nontumor ratio (T/M), which was based on the value of 99m Tc-3PRGD2 (4.20 ± 1.33); meanwhile, no significance (r=-0.16, p > 0.05) was found between the T/M and hypoxic area (116.71 ± 9.36). Neovascular proliferation was particularly vigorous in the parenchymal region of the tumor, while the cells around the cavity were generally hypoxic. 99m TC-3PRGD2 SPECT/CT was more specific than 18 F-FDG PET-CT in detecting malignant tumors. Both 99m TC-3PRGD2 and 18 F-FDG PET-CT can be used for the detection of malignant tumors, but the specificity and accuracy of 99m TC-3PRGD2 are better. The subcutaneous tumors showed a heterogeneous microenvironment as a result of neovascularization, a high proliferation rate of cancer cells as well as subsequent hypoxia, while most of the hypoxic areas appeared around the cavities of the vessels.

The application of PET/CT with 18F-FDG in the differential diagnosis of lung solitary lesions

Purpose of the study. The study was aimed to investigate the effectiveness of PET / CT with 18 fluoro‑2 deoxy-D-glucose (18F-FDG) in the differential diagnosis of focal lung neoplasms.Materials and methods. Patients (n = 108) with newly diagnosed lung focal lesions were enrolled in the study. All patients underwent PET / CT with 18fluoro‑2deoxy-D-glucose in the "whole body" mode in accordance with the standard protocol. The next step was surgical treatment with morphological verification. According to the results of the morphological conclusion, malignant neoplasm was not diagnosed in 11 (10.2 %) patients, while post-inflammatory changes were detected in 7 patients (SUVmax from 2.3 to 15.15), hamartoma was verified in 3 patients (SUVmax from 1.1 to 4.2) and anthracosis was detected in 1 patient.Results. The median radiopharmaceutical accumulation (SUVmax) was 6.0 (ICR 3.9–8.4, n = 108). In turn, in patients with diagnosed lung cancer this indicator was 7.0 (ICR 5.8–10.9, n = 60), in patients with metastatic lesions 4.3 (ICR 2.5–7.1, n = 37). The threshold for SUVmax was 5.4 for the detection of malignant tumors. PET/CT with 18F-FDG demonstrated high data variability regarding the size of lung focal lesion. An error within 35 % was observed in 76 % of cases, underestimating small lesions (up to 40 mm) but overestimating the major neoplasms. Application of a linear model for adjustment of neoplasm size assessment allows to estimate the actual size of neoplasms with parameters 5.862 + 0,817 × х (х – PET / CT size) in 84.5 % of cases with an error of 50 %. The optimal diagnosing size for metastatic lesions is in the range between 16.4 and 19 mm.Conclusion. Taken together the results of the study show that PET / CT with 18F-FDG gives a relatively accurate estimation of the tumor size. Application of the linear model corrects a radiological size measurements and helps to predict an actual size of a neoplasm in 84.5 % of cases with an error of 50 %. The prospective threshold for SUVmax was at least 5.4 for the detection of malignant neoplasms.

Small-Molecule Fluorescent Probes for Detecting Several Abnormally Expressed Substances in Tumors.

Malignant tumors have always been the biggest problem facing human survival, and a huge number of people die from cancer every year. Therefore, the identification and detection of malignant tumors have far-reaching significance for human survival and development. Some substances are abnormally expressed in tumors, such as cyclooxygenase-2 (COX-2), nitroreductase (NTR), pH, biothiols (GSH, Cys, Hcy), hydrogen sulfide (H2S), hydrogen sulfide (H2O2), hypochlorous acid (HOCl) and NADH. Consequently, it is of great value to diagnose and treat malignant tumors due to the identification and detection of these substances. Compared with traditional tumor detection methods, fluorescence imaging technology has the advantages of an inexpensive cost, fast detection and high sensitivity. Herein, we mainly introduce the research progress of fluorescent probes for identifying and detecting abnormally expressed substances in several tumors.

Nonenzymatic Multiamplified Electrochemical Detection of Medulloblastoma-Relevant MicroRNAs from Cerebrospinal Fluid.

The sensitive analysis of microRNAs (miRNAs) in cerebrospinal fluid (CSF) holds promise for the minimally invasive early diagnosis of brain cancers such as pediatric medulloblastoma but remains challenging due partially to a lack of facile yet sensitive sensing methods. Herein, an enzyme-free triple-signal amplification electrochemical assay for miRNA was developed by integrating the target-triggered cyclic strand-displacement reaction (TCSDR), hybridization chain reaction (HCR), and methylene blue (MB) intercalation. In this assay, the presence of target miRNA (miR-9) initiated the TCSDR and produced primers that triggered the subsequent HCR amplification to generate copious double-stranded DNAs (dsDNAs) on the electrode surface. Intercalation of a large number of MB reporters into the long nicked double helixes of dsDNAs yielded a more enhanced signal of differential pulse voltammetry. The enzyme-free multiple-amplification approach allowed for highly sensitive (detection limit: 6.5 fM) and sequence-specific (single-base mismatch resolution) detection of miR-9 from tumor cells and human CSF with minimal sample consumption (10 μL). Moreover, the clinical utilization of this method was documented by accurate discrimination of five medulloblastoma patients from the nontumoral controls. In light of its sensitivity, specificity, and convenience of use, this electrochemical method was expected to facilitate the early detection of malignant brain tumors.

Molecular assessment of endoscopically collected pancreatic juice and duodenal fluid from patients with pancreatic diseases.

One concern associated with pancreatic diseases is the poor prognosis of pancreatic cancer. Even with advances in diagnostic modalities, risk stratification of premalignant lesions and differentiation of pancreatic cysts are challenging. Pancreatic lesions of concern include intraductal papillary mucinous neoplasms, mucinous cystic neoplasms, serous cystadenomas, pseudocysts, and retention cysts, as well as cystic degeneration of solid tumors such as solid pseudopapillary neoplasms and pancreatic neuroendocrine neoplasms. Pancreatic juice obtained during endoscopic retrograde cholangiopancreatography has previously been used for the detection of KRAS mutation. Recently, duodenal fluid, which can be obtained during the relatively minimally invasive procedures of endoscopic ultrasound (EUS) and esophagogastroduodenoscopy, and cyst fluid collected by EUS-guided fine-needle aspiration (FNA) were used for molecular biological analysis. Furthermore, advanced analytic methods with high sensitivity were used for the detection of single and multiple markers. Early detection of malignant pancreatic tumors and risk stratification of premalignant tumors can be performed using duodenal fluid samples with a single marker with high sensitivity. Technological advances in simultaneous detection of multiple markers allow for the differentiation of cystic pancreatic tumors. One thing to note is that the clinical guidelines do not recommend pancreatic cyst fluid and pancreatic juice (PJ) sampling by EUS-FNA and endoscopic retrograde cholangiopancreatography, respectively, in actual clinical practice, but state that they be performed at experienced facilities, and duodenal fluid sampling is not mentioned in the guidelines. With improved specimen handling and the combination of markers, molecular markers in PJ samples may be used in clinical practice in the near future.

Feasibility of a Deep Learning approach to estimate Shear Wave Speed using the framework of Reverberant Shear Wave Elastography: A numerical simulation study.

Reverberant Shear Wave Elastography (RSWE) is an ultrasound elastography technique that offers great advantages, however, current estimators generate underestimations and time-consuming issues. As well, the involvement of Deep Learning into the medical imaging field with new tools to assess complex problems, makes it a great candidate to serve as a new approach for a RSWE estimator. This work addresses the application of a Deep Neural Network (DNN) for the estimation of Shear Wave Speed (SWS) maps from particle velocity using numerically simulated data. The architecture of the proposed network is based on a U-Net, which works with a custom loss function specifically adopted for the reconstruction task. Four DNNs were trained using four different databases: clean, noisy, acquired at variable frequency, and noisy and acquired at variable frequency data. After the training of the DNNs, the predicted SWS maps were evaluated based on different metrics related to segmentation, regression and similarity of images. The model for clean data showed better results with a Mean Absolute Error (MAE) of 0.011, Mean Square Error(MSE) of 0.001, modified Intersection over Union (mIoU) of 98.4%, Peak Signal to Noise Ratio (PSNR) of 32.925 and a Structural Similarity Index Measure (SSIM) of 0.99, for 250 (size of Testing Sets); while the other models delivered SSIM in the range of 0.87 to 0.96. It was concluded that noisy and clean data could be effectively handled by the model, while the other ones still need enhancement. Clinical Relevance- This work is focused on the application of a Deep Learning approach to accurately asses the Shear Wave Speed in numerical simulations of Reverberant Shear Wave Elastography approach. This novel estimator could be useful for future clinical experiments specially with real time applications to determine the status of living tissue such as detection of malignant or benign tumors located in breast cervix prostate or skin and in the diagnosis of other pathologies such us liver fibrosis.

Graphene-based electrochemical immunosensors for early detection of oncomarker carcinoembryonic antigen

The detection of pre-invasive tumors prior to the appearance of advanced clinical symptoms will enhance the effect of medical intervention at the earliest stage and reduce premature cancer deaths. Tumor biomarkers detection represents a powerful alternative to taking invasive biopsies; hence, biosensing technology is emphasized. Cancer diagnostics have evolved from the macroscopic detection of malignant tumors to the facile assessment of tumor biomarkers using miniaturized detection devices, such as immunosensors. Innovative immunosensors have become the most eminent candidate for analyzing oncomarkers to meet the requirements of medical diagnostics. Hence the development of highly selective immunosensors for the sensitive detection of oncomarker paves new directions for personal and medical supervision. Graphene and its derivatives are emerging carbon materials employed in developing sensors, in view of their exceptional physicochemical properties that amplify the device's sensitivity. Therefore, this review was designed to present a comprehensive interpretation of the recently developed graphene-based electrochemical immunosensors for detecting broad-spectrum oncomarker carcinoembryonic antigen (CEA). The article highlights the recent advances in signal amplification strategies accomplished utilizing graphene and its nanomaterials (2017 to mid-2022). Different electroanalytical techniques employed for CEA sensing have been discussed, and the sensor's performances are substantiated. The readers are also provided with significant statistical information on the reported immunosensors and their performance comparison: a technique used, working range, detection limit, real sample recoveries, reproducibility, and stability. Finally, the review concludes with the associated challenges and outlines the approach required to realize their successful translation into clinical settings.

ANALYSIS OF SPECIFIC PARAMETERS FOR SKIN TUMOR CLASSIFICATION

During the last years, computer vision-based diagnosis systems have been widely used in several hospitals and dermatology clinics, aiming mostly at the early detection of malignant melanoma tumor, which is among the most frequent types of skin cancer, versus other types of nonmalignant cutaneous diseases. They grow in melanocytes, the cells responsible for pigmentation. This type of cancer is increasing rapidly and its related mortality rate is increasing more modestly, and inversely proportional to the tumor’s thickness. The mortality rate can be decreased by earlier detection of suspicious lesions and better prevention. In this work, we are interested in extracting all specific attributes which can be used for computer-aided diagnosis of melanoma. In the first step of the proposed work, we applied the Dull Razor [Lee T et al., Dullrazor: A software approach to hair removal from images, Cancer Control Research, British Columbia Cancer Agency, Vancouver, Canada, Vol. 21, No. 6, pp. 533–543, 1997] technique to images to reduce the influence of small structures, hairs, bubbles, light reflection. In the second step, a new fuzzy level set algorithm is proposed in order to facilitate the medical image segmentation task. It is able to directly evolve from the initial segmentation proposed that uses a spatial fuzzy clustering approach. The controlling parameters of the level set evolution are also estimated from the results of the fuzzy clustering step. This step is essential to characterize the shape of the lesion and also to locate the tumor to be analyzed. In this paper, we have also treated the necessity to extract all the specific attributes used to develop a characterization methodology that enables specialists to take the best possible diagnosis. For this purpose, our proposal relies largely on visual observation of the tumor while dealing with some characteristics as color, texture or form. The method used in this paper is called ABCD. It requires calculating four factors: Asymmetry ([Formula: see text], Border ([Formula: see text], Color ([Formula: see text], and Diversity ([Formula: see text]. Finally, these parameters are used to construct a classification module based on artificial neural network for the recognition of malignant melanoma.

Detection of Benign and Malignant Tumors in Skin Empowered with Transfer Learning.

Skin cancer is a major type of cancer with rapidly increasing victims all over the world. It is very much important to detect skin cancer in the early stages. Computer-developed diagnosis systems helped the physicians to diagnose disease, which allows appropriate treatment and increases the survival ratio of patients. In the proposed system, the classification problem of skin disease is tackled. An automated and reliable system for the classification of malignant and benign tumors is developed. In this system, a customized pretrained Deep Convolutional Neural Network (DCNN) is implemented. The pretrained AlexNet model is customized by replacing the last layers according to the proposed system problem. The softmax layer is modified according to binary classification detection. The proposed system model is well trained on malignant and benign tumors skin cancer dataset of 1920 images, where each class contains 960 images. After good training, the proposed system model is validated on 480 images, where the size of images of each class is 240. The proposed system model is analyzed using the following parameters: accuracy, sensitivity, specificity, Positive Predicted Values (PPV), Negative Predicted Value (NPV), False Positive Ratio (FPR), False Negative Ratio (FNR), Likelihood Ratio Positive (LRP), and Likelihood Ratio Negative (LRN). The accuracy achieved through the proposed system model is 87.1%, which is higher than traditional methods of classification.

Main directions of detection of malignant neoplasms of leading localizations in rural municipal districts

Introduction. The leading localizations of malignant neoplasms in terms of detection frequency in Russia are breast cancer (BC) and uterine cancer by women (RTM) — 51.8 and 18.3%, accordingly, by men — lung cancer (RL) and prostate cancer (PC) — 47.4 and 41.4%, respectively. Study objective was the identification of the main reasons of the high level of neglect of cancer of the leading localizations among residents of rural municipalities of the Chelyabinsk region. Material and methods. The study was carried out on the general population of people living in 5 rural municipal districts of the Chelyabinsk region, included by the Ministry of Health of the region in the Magnitogorsk oncological cluster, with malignant neoplasms of the mammary gland and the body of the uterus, lung and prostate gland (total 1696 observation units). Results. During medical examinations in basic rural municipal areas, the detection of breast cancer and RTM is in the range from 0.1 to 0.3 cases and 0.04 to 0.1 cases per 100 examined women, prostate cancer — 0.04-0.1 per 100 examined men. In medical examination suits, the detection is even lower — from 0.005 to 0.03 cases and 0.007 to 0.02 cases per 100 women and 0.01 to 0.05 cases per 100 men. The levels of cancer detection in rural areas are substantially lower than similar indicators among the urban population. Only when RL is detected, medical examinations of the rural population do not lag behind the indicators of the townspeople in their effectiveness. Discussion. The oncological epidemiological situation in municipal areas of the Magnitogorsk oncological cluster can be characterized as extremely unsatisfactory, due to a lower level of registered morbidity than in the city and to the low efficiency of active methods for detecting cancer. Conclusion. The lower incidence of malignant neoplasms in rural areas compared to urban indicators is due to the low efficiency of active methods for detecting neoplasms. The main way to identify malignant neoplasms of the leading localizations, with the exception of individual years of follow-up, is the independent appeal of rural patients to an oncologist, which causes a high level of neglect.

3-Hydroxyquinazoline derivatives, analogues of erastin, induced ferroptosis in breast cancer cells

Introduction. Early malignant tumor detection programs have significantly increased the survival rate of breast cancer patients but the results of drug therapy for this pathology are not always highly effective. Recently discovered iron-dependent cell death, ferroptosis, makes it a promising therapeutic target to reduce the recurrence rates.Objective – to study the induction of ferroptosis in breast cancer cells MCF-7 by quinazoline derivatives synthesized at the Research Institute of Experimental Diagnostics and Therapy of Tumors of the N.N. Blokhin National Medical Research Center of Oncology, Ministry of Health of Russia and to evaluate its antitumor activity on transplanted breast carcinoma Ca-755.Materials and methods. Derivatives of 3-hydroxyquinazoline were obtained by chemical synthesis and have a purity of at least 95 %. In this study 2D cultivation of MCF7 cells, phase-contrast and fluorescence microscopy, and a model of experimental growth of breast carcinoma Ca-755 in female hybrids of immunocompetent mice F1 (C57Bl/6 × DBA/2) were used.Results. Five derivatives of 3-hydroxyquinazoline, analogues of erastine, were studied in this work. The ferroptotic cell death was identified by the level of lipid peroxidation at the concentrations of 1/3 and 1/5 IC50. The level of lipid peroxidation induced by compound 3 was comparable with the activity of erastin in MCF7 cells at both 1/3 and 1/5 of IC50, the activity of the other four quinazoline derivatives was 50–70 % of the activity of erastin. In in vivo experiments at a dose of 30 mg/kg the antitumor efficacy of the compound 3 was higher than that of erastin at the same dose.Conclusion. The data obtained suggest that quinazoline derivative 3 might be considered as a promissisng antitumor agent to treat breast cancer.

Detection of malignant peripheral nerve sheath tumors in patients with neurofibromatosis using aneuploidy and mutation identification in plasma.

Malignant peripheral nerve sheath tumors (MPNST) are the deadliest cancer that arises in individuals diagnosed with neurofibromatosis and account for nearly 5% of the 15,000 soft tissue sarcomas diagnosed in the United States each year. Comprised of neoplastic Schwann cells, primary risk factors for developing MPNST include existing plexiform neurofibromas (PN), prior radiotherapy treatment, and expansive germline mutations involving the entire NF1 gene and surrounding genes. PN develop in nearly 30-50% of patients with neurofibromatosis type 1 (NF1) and most often grow rapidly in the first decade of life. One of the most important aspects of clinical care for NF1 patients is monitoring PN for signs of malignant transformation to MPNST that occurs in 10-15% of patients. We perform aneuploidy analysis on ctDNA from 883 ostensibly healthy individuals and 28 patients with neurofibromas, including 7 patients with benign neurofibroma, 9 patients with PN and 12 patients with MPNST. Overall sensitivity for detecting MPNST using genome wide aneuploidy scoring was 33%, and analysis of sub-chromosomal copy number alterations (CNAs) improved sensitivity to 50% while retaining a high specificity of 97%. In addition, we performed mutation analysis on plasma cfDNA for a subset of patients and identified mutations in NF1, NF2, RB1, TP53BP2, and GOLGA2. Given the high throughput and relatively low sequencing coverage required by our assay, liquid biopsy represents a promising technology to identify incipient MPNST.

Artificial intelligence to detect malignant eyelid tumors from photographic images

Malignant eyelid tumors can invade adjacent structures and pose a threat to vision and even life. Early identification of malignant eyelid tumors is crucial to avoiding substantial morbidity and mortality. However, differentiating malignant eyelid tumors from benign ones can be challenging for primary care physicians and even some ophthalmologists. Here, based on 1,417 photographic images from 851 patients across three hospitals, we developed an artificial intelligence system using a faster region-based convolutional neural network and deep learning classification networks to automatically locate eyelid tumors and then distinguish between malignant and benign eyelid tumors. The system performed well in both internal and external test sets (AUCs ranged from 0.899 to 0.955). The performance of the system is comparable to that of a senior ophthalmologist, indicating that this system has the potential to be used at the screening stage for promoting the early detection and treatment of malignant eyelid tumors.

Study on the Effect of MRI in the Diagnosis of Benign and Malignant Thoracic Tumors.

In order to investigate the effectiveness and accuracy of magnetic resonance imaging (MRI) in the diagnosis of benign and malignant thoracic tumors, the research retrospectively selected 80 patients with thoracic tumors admitted from May 2019 to May 2020 as the study subject and all patients were underwent MRI detection. Using pathological diagnostic results as the gold standard, the research analyzed the detection of benign and malignant thoracic tumors by MRI, as well as the diagnostic sensitivity and specificity. After pathological diagnosis, there were 35 malignant tumors and 45 benign tumors. 41 cases of malignant tumors and 39 cases of benign tumors were diagnosed by MRI, with a diagnostic sensitivity of 80.00%, a diagnostic specificity of 71.11%, and a diagnostic compliance rate of 75.00%. In the MRI diagnosis of tumors in different parts of the chest, the diagnostic sensitivity for lung tumors, mediastinal tumors, chest wall tumors, and esophageal tumors was 83.33%, 71.43%, 83.33%, 75.00%, and 87.50%, respectively, and the specificity was 66.67%, 77.78%, 57.14%, 50.00%, and 91.67% according to and breast tumors, respectively. And the accuracy was 73.33%, 75.00%, 69.23, 62.50%, and 90.00%, respectively, with the highest diagnostic sensitivity, specificity, and accuracy for breast tumors. MRI has a good effect on the diagnosis of benign and malignant thoracic tumors and has a high diagnostic value, which is helpful to identify the location, nature, source, and lesion scope of the tumor. It is safe and worthy of promotion.

Region-Growing Algorithm on CT Angiography Images for Detection of Gynecological Malignant Tumor

This paper aimed to explore pelvic lymphadenectomy for gynecological malignant tumors guided by computed tomography angiography (CTA) images under region-growing algorithm (RGA). 100 cases of malignant tumor patients who received pelvic lymphadenectomy in hospital from January 2018 to January 2020 were analyzed. Patients were classified into control group (CTA image) and experimental group (RGA-based CTA image), each with 50 cases. The overall accuracy (OA) of the pelvic CT image segmentation parameters under RGA, the watershed segmentation algorithm (WA), and the swarm intelligence optimization algorithm (SIOA) was compared. Comparisons of segmentation parameters, denoising performance, and CT imaging of patients as well as diagnosis rate and total efficiency rate were carried out. The results showed that overall accuracy (OA) of RGA was considerably higher versus watershed segmentation algorithm (WA) and swarm intelligence optimization algorithm (SIOA). However, false positive rate (FPR) and false negative rate (FNR) of RGA were greatly lower than those of other algorithms. RGA greatly improved the accuracy of pelvic tumor detection. The peak signal-to-noise ratio (PSNR) of RGA was superior to that of WA and SIOA, but differences in edge preservation index (EPI) value were not significant. The diagnosis rate of the experimental group was 48/50 (96%), while the diagnosis rate by manual means was 38/50 (76%). For the diagnosis rate and total efficiency, results of the experimental group were evidently higher in contrast to the control group ( P &lt; 0.05 ). In conclusion, under RGA, CTA image-guided pelvic lymphadenectomy had good segmentation accuracy and denoising performance, and it was superior in total efficiency and diagnosis rate, which was worthy of clinical promotion.

Accumulation of Uroporphyrin I in Necrotic Tissues of Squamous Cell Carcinoma after Administration of 5-Aminolevulinic Acid.

5-aminolevulinic acid (5-ALA)-induced protoporphyrin IX (PpIX) fluorescence is widely used for the intraoperative detection of malignant tumors. However, the fluorescence emission profiles of the accompanying necrotic regions of these tumors have yet to be determined. To address this, we performed fluorescence and high-performance liquid chromatography (HPLC) analyses of necrotic tissues of squamous cancer after 5-ALA administration. In resected human lymph nodes of metastatic squamous cell carcinoma, we found a fluorescence peak at approximately 620 nm in necrotic lesions, which was distinct from the PpIX fluorescence peak at 635 nm for viable cancer lesions. Necrotic lesions obtained from a subcutaneous xenograft model of human B88 oral squamous cancer also emitted the characteristic fluorescence peak at 620 nm after light irradiation: the fluorescence intensity ratio (620 nm/635 nm) increased with the energy of the irradiation light. HPLC analysis revealed a high content ratio of uroporphyrin I (UPI)/total porphyrins in the necrotic cores of murine tumors, indicating that UPI is responsible for the 620 nm peak. UPI accumulation in necrotic tissues after 5-ALA administration was possibly due to the failure of the heme biosynthetic pathway. Taken together, fluorescence imaging of UPI after 5-ALA administration may be applicable for the evaluation of tumor necrosis.

Optical Brain Biopsy with a Fluorescence and Vessel Tracing Probe.

BACKGROUNDAccurate stereotactic biopsies of brain tumors are imperative for diagnosis and tailoring of the therapy. Repetitive needle insertions enhance risks of brain lesioning, hemorrhage, and complications due to prolonged procedure.OBJECTIVETo investigate clinical benefits of a combined 5-aminolaevulinic acid (5-ALA) fluorescence and laser Doppler flowmetry system for the detection of malignant brain tumor and blood vessels in stereotactic biopsies.METHODSPlanning of targets and trajectories was followed by optical measurements in 20 patients, using the Leksell Stereotactic System and a manual insertion device. Fluorescence spectra, microvascular blood flow, and tissue grayness were recorded each millimeter along the paths. Biopsies were taken at preplanned positions. The diagnoses were compared with the fluorescence signals. The recordings were plotted against measurement positions and compared. Sites indicating a risk of hemorrhage were counted as well as the time for the procedures.RESULTSSignals were recorded along 28 trajectories, and 78 biopsies were collected. The final diagnosis showed 17 glioblastomas, 2 lymphomas, and 1 astrocytoma grade III. Fluorescence was seen along 23 of the paths with 4 having the peak of 5-ALA fluorescence 3 mm or more from the precalculated target. There was increased microcirculation in 40 of 905 measured positions. The measurement time for each trajectory was 5 to 10 min.CONCLUSIONThe probe provided direct feedback of increased blood flow along the trajectory and of malignant tissue in the vicinity of the target. The method can increase the precision and the safety of the biopsy procedure and reduce time.

Metabolic changes in colorectal carcinomas are key factors for the early detection of neoplastic change

Potential metabolic biomarkers have been developed by the use of modern analytical techniques and nanotechnology in metabolomics, providing insight into the pathophysiological basis and changes, tumorigenesis, and molecular mechanisms that underpin better therapeutic, monitoring, and prognostic evaluations of colon malignancies. This would allow early detection and characterization of malignant colon tumors and could reduce the risk of mortality and morbidity of colorectal carcinomas. Based on their association with certain metabolic pathways linked to malignancies, a number of tumor markers have been designed. Whereas some have been associated with only one cancer type, while others are associated with many different forms of cancer. No tumor marker has been found to have universal application as a metabolism-related marker; although some are circulating tumor markers found in blood, urine, stool, or other body fluids, others may be found in the specific tumors themselves. This paper addresses a number of associated metabolic changes linked to colorectal cancers and potential applications for disease condition diagnosis, monitoring, treatment, and prognosis.

Abstract 2842: 6-gingerol attenuates metastasis in aged mice model of colorectal cancer through modulation of epithelial-mesenchymal transition mediators genes and e-cadherin upregulation

Abstract Colorectal cancer (CRC) is the third most common cancer in America, and the third cause of cancer related death. Metastasis is the major cause of death in patient with CRC. Many CRC are likely to spread from primary site to the other parts of the body before and after detection of malignant tumor. 6-gingerol, the bioactive component of fresh ginger have been reported to have myriad of biological activities including anti-inflammatory and antioxidant properties. We have previously reported the anti-CRC effect of 6-gingerol. However there is dearth of information on the anti-metastatic effect 6-gingerol in CRC. Thus, the effect of 6-gingerol on epithelial-mesenchymal transition mediators' genes and E-Cadherin repression in aged mice model of CRC was assessed in this study. Following institutional ethical approval. Aged male BALB/c mice (10 months) were divided into four groups of 10 mice each. Mice were fed with AIN-93 diet and allowed access to water ad libitum. Group 1 mice serve as control, group 2 mice received 6-gingerol 10mg/kg/day by oral gavage for 10 weeks. Group 3 mice received a single dose of azoxymethane (AOM) 10mg/kg (iP) and on the seventh day they received three cycles of dextran sulfate sodium (DSS) 2% (W/V) in drinking water ( each cycle is define as one week of DSS followed by two weeks of plain drinking water) Group 4 mice received 6-gingerol 10mg/kg/day by oral gavage in combination with single dose of azoxymethane 10mg/kg (iP) and on the seventh day they received three cycles of dextran sulfate sodium salt 2% (W/V) in drinking water. Mice were humanely sacrificed under anesthesia and colon tissues were processed for RT-PCR and multiplex immunohistochemistry analysis. Mice that received both 6-gingerol and AOM and DSS showed a significant decreased expression of Lymphocyte function-associated antigen-1, N-cadherin, SNAIL 1, ZEB 1, AP4 and HMGA1 with concomitant Upregulation miR-34, miR-15a, miR-218 and miR-302 expression as compared with the AOM and DSS only group. The result obtained from this study showed 6-gingerol inhibited metastasis through modulation of epithelial-mesenchymal transition mediators' genes and E-Cadherin upregulation, and as such 6-gingerol could be a promising anti-metastatic agent in CRC treatment. Citation Format: Babajide Oluwaseun Ajayi, Ayomiposi Adenigba, Anuoluwapo Adeshina. 6-gingerol attenuates metastasis in aged mice model of colorectal cancer through modulation of epithelial-mesenchymal transition mediators genes and e-cadherin upregulation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2842.

Prediction of Malignancy in Lung Nodules Using Combination of Deep, Fractal, and Gray-Level Co-Occurrence Matrix Features.

Accurate detection of malignant tumor on lung computed tomography scans is crucial for early diagnosis of lung cancer and hence the faster recovery of patients. Several deep learning methodologies have been proposed for lung tumor detection, especially the convolution neural network (CNN). However, as CNN may lose some of the spatial relationships between features, we plan to combine texture features such as fractal features and gray-level co-occurrence matrix (GLCM) features along with the CNN features to improve the accuracy of tumor detection. Our framework has two advantages. First it fuses the advantage of CNN features with hand-crafted features such as fractal and GLCM features to gather the spatial information. Second, we reduce the overfitting effect by replacing the softmax layer with the support vector machine classifier. Experiments have shown that texture features such as fractal and GLCM when concatenated with deep features extracted from DenseNet architecture have a better accuracy of 95.42%, sensitivity of 97.49%, and specificity of 93.97%, and a positive predictive value of 95.96% with area under curve score of 0.95.