Diagnosis Of Tumors Research Articles

Synchronous multiple primary malignancies or transdifferentiation?-A diagnostic challenge in a case of Xeroderma pigmentosum.

A diagnosis of synchronous tumors is always questionable when they show similar histology. We present a case of synchronous tumors, i.e. melanoma (MM) arising from the scalp and angiosarcoma (AS) from the cheek in a patient of Xeroderma pigmentosum (XP). The presence of melanin in AS of the cheek led to a differential diagnosis and a possibility of transdifferentiation of malignant melanoma in the first instance. Immunohistochemistry (IHC) was negative for melanoma markers (Melan A, SOX-10 & S 100) and positive for vascular markers (ERG, CD31 & CD34) ruling out transdifferentiation and concluding the cheek swelling as angiosarcoma. The presence of non-cutaneous malignancies is rare in XP and the presence of MM in a nearby site and the melanin pigment in the cutaneous malignancy mislead the diagnosis. The morphology of the tumor was the key which led to the further workup of the case.

Role of Cryobiopsy in Diagnosis of Pleural Tumors

Role of Cryobiopsy in Diagnosis of Pleural Tumors

Small Intestine Metastasis Leads to the Diagnosis of Thoracic SMARCA4-Deficient Undifferentiated Tumor: A Case Report

Small Intestine Metastasis Leads to the Diagnosis of Thoracic SMARCA4-Deficient Undifferentiated Tumor: A Case Report

Can incorporating image resolution into neural networks improve kidney tumor classification performance in ultrasound images?

Deep learning has been widely used in ultrasound image analysis, and it also benefits kidney ultrasound interpretation and diagnosis. However, the importance of ultrasound image resolution often goes overlooked within deep learning methodologies. In this study, we integrate the ultrasound image resolution into a convolutional neural network and explore the effect of the resolution on diagnosis of kidney tumors. In the process of integrating the image resolution information, we propose two different approaches to narrow the semantic gap between the features extracted by the neural network and the resolution features. In the first approach, the resolution is directly concatenated with the features extracted by the neural network. In the second approach, the features extracted by the neural network are first dimensionally reduced and then combined with the resolution features to form new composite features. We compare these two approaches incorporating the resolution with the method without incorporating the resolution on a kidney tumor dataset of 926 images consisting of 211 images of benign kidney tumors and 715 images of malignant kidney tumors. The area under the receiver operating characteristic curve (AUC) of the method without incorporating the resolution is 0.8665, and the AUCs of the two approaches incorporating the resolution are 0.8926 (P < 0.0001) and 0.9135 (P < 0.0001) respectively. This study has established end-to-end kidney tumor classification systems and has demonstrated the benefits of integrating image resolution, showing that incorporating image resolution into neural networks can more accurately distinguish between malignant and benign kidney tumors in ultrasound images.

A Comprehensive Review: Versatile Imaging Probe Based on Chemical Materials for Biomedical Applications.

Imaging probe and contrast agents play significant role in combating cancer. Based on special chemical materials, imaging probe can convert cancer symptoms into information-rich images with high sensitivity and signal amplification, accompanying with detection, diagnosis, drug delivery and treatment. In the paper, some inorganic and organic chemical materials as imaging probe, including Ultrasound imaging (US), Optical imaging (OP), Photoacoustic imaging (PA), X-ray Computed Tomography (CT), Magnetic Resonance imaging (MRI), Radionuclide imaging (RNI) probe, as well as multi-modality imaging probe for diagnosis and therapy of tumour were introduced. The sophisticated and comprehensive chemical materials as imaging probe were highlighted in detail. Meanwhile, the advantages and disadvantages of the imaging probe were compared. In order to provide some reference and help researchers for construction imaging probe for tumour diagnosis and treatment, it attempts to exhaustively cover the whole field. Finally, the prospect and challenge for imaging probe were discussed.

High-Resolution Magnetic Resonance Angiography of Tumor Vasculatures with an Interlocking Contrast Agent.

The comprehensive evaluation of tumor vasculature that is crucial for the development, expansion, and spread of cancer still remains a great challenge, especially the three-dimensional (3D) evaluation of vasculatures. In this study, we proposed a magnetic resonance (MR) angiography strategy with interlocking stratagem of zwitterionic Gd-chelate contrast agents (PAA-Gd) for continuous monitoring of tumor angiogenesis progression in 3D. Owing to the zwitterionic structure and nanoscale molecular diameter, the longitudinal molar relaxivity (r1) of PAA-Gd was 2.5 times higher than that of individual Gd-chelates on a 7.0 T MRI scanner, resulting in the higher-resolution visualization of tumor vasculatures. More importantly, PAA-Gd has the appropriate blood half-life (69.2 min), emphasizing the extended imaging window compared to the individual Gd-chelates. On this basis, by using PAA-Gd as the contrast agent, the high-resolution, 3D depiction of the spatiotemporal distribution of microvasculature in solid tumors formed by different cell lines over various inoculation times has been obtained. This method offers an effective approach for early tumor diagnosis, development assessment, and prognosis evaluation.

MiR-21, miR-29a, and miR-106b: serum and tissue biomarkers with diagnostic potential in metastatic testicular cancer.

The imperative need for sensitive and precise tools is underscored in cancer diagnostics, with biomarkers playing a pivotal role in facilitating early detection and tumor diagnosis. Despite their classical pathological classification, testicular tumors lack valuable markers, emphasizing the necessity to identify and apply serum tumor markers in clinical management. Unfortunately, existing biomarkers exhibit limited sensitivities and specificities. Recent years have witnessed the discovery of novel RNA molecules, presenting a potential breakthrough as diagnostic tools and promising biomarkers. This report presents compelling evidence supporting the detection of early testicular cancer by applying a set of nine microRNAs (miRNAs), establishing them as valuable serum biomarkers for diagnosis. We developed a standardized serum-based measurement protocol and conducted comprehensive statistical analyses on the dataset to underscore the diagnostic accuracy of the miRNA pool. Notably, with a sensitivity exceeding 93%, miR-21, miR-29a, and miR-106b surpass classical serum tumor markers in the context of testicular cancer. Specifically, these miRNAs are poised to enhance clinical decision-making in testicular cancer detection and hold the potential for assessing tumor growth in monitoring chemotherapy outcomes.

The role of stathmin expression in the differential diagnosis, prognosis, and potential treatment of ovarian sex cord-stromal tumors.

Stathmin, a cytosolic microtubule-destabilizing phosphoprotein involved in the regulation of mitosis, is widely expressed in various malignancies and acts as an adverse prognostic factor. Our research analyzed its immunohistochemical expression on a large cohort of ovarian sex cord-stromal tumors, evaluating its potential utility in differential diagnosis, prognosis, and therapeutic application. We examined 390 cases of ovarian sex cord-stromal tumors including 281 adult granulosa cell tumors (AGCT), 5 juvenile granulosa cell tumors (JGCT), 33 Sertoli-Leydig cell tumors (SLCT), 50 fibromas/thecomas (F/T), 11 Leydig cell tumors/steroid cell tumors (LCT/SterCT), 5 sex-cord stromal tumors NOS (SCST-NOS), 3 Sertoli cell tumors (SCT), and 2 sclerosing stromal tumors (ScST). Immunohistochemical analysis was performed using TMAs. Strong expression (> 50%) was observed in all cases of AGCT, JGCT, SLCT, SCST-NOS, SCT and 1 ScST. The other case of ScST exhibited mild expression (5-10%). The negative cases included exclusively F/T and LCT/SterCT, with F/T showing 24% of negative cases and LCT/SterCT comprising 64% of negative cases. The results of our study indicate that stathmin is neither a prognostic marker nor suitable for the differential diagnosis of challenging cases of ovarian sex cord-stromal tumors. However, its predictive value may be theoretically significant, as a decrease in stathmin expression potentialy influences response to chemotherapy treatment.

Identification of a serum proteomic biomarker panel using diagnosis specific ensemble learning and symptoms for early pancreatic cancer detection.

The grim (<10% 5-year) survival rates for pancreatic ductal adenocarcinoma (PDAC) are attributed to its complex intrinsic biology and most often late-stage detection. The overlap of symptoms with benign gastrointestinal conditions in early stage further complicates timely detection. The suboptimal diagnostic performance of carbohydrate antigen (CA) 19-9 and elevation in benign hyperbilirubinaemia undermine its reliability, leaving a notable absence of accurate diagnostic biomarkers. Using a selected patient cohort with benign pancreatic and biliary tract conditions we aimed to develop a data analysis protocol leading to a biomarker signature capable of distinguishing patients with non-specific yet concerning clinical presentations, from those with PDAC. 539 patient serum samples collected under the Accelerated Diagnosis of neuro Endocrine and Pancreatic TumourS (ADEPTS) study (benign disease controls and PDACs) and the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS, healthy controls) were screened using the Olink Oncology II panel, supplemented with five in-house markers. 16 specialized base-learner classifiers were stacked to select and enhance biomarker performances and robustness in blinded samples. Each base-learner was constructed through cross-validation and recursive feature elimination in a discovery set comprising approximately two thirds of the ADEPTS and UKCTOCS samples and contrasted specific diagnosis with PDAC. The signature which was developed using diagnosis-specific ensemble learning demonstrated predictive capabilities outperforming CA19-9, the only biomarker currently accepted by the FDA and the National Comprehensive Cancer Network guidelines for pancreatic cancer, and other individual biomarkers and combinations in both discovery and held-out validation sets. An AUC of 0.98 (95% CI 0.98-0.99) and sensitivity of 0.99 (95% CI 0.98-1) at 90% specificity was achieved with the ensemble method, which was significantly larger than the AUC of 0.79 (95% CI 0.66-0.91) and sensitivity 0.67 (95% CI 0.50-0.83), also at 90% specificity, for CA19-9, in the discovery set (p = 0.0016 and p = 0.00050, respectively). During ensemble signature validation in the held-out set, an AUC of 0.95 (95% CI 0.91-0.99), sensitivity 0.86 (95% CI 0.68-1), was attained compared to an AUC of 0.80 (95% CI 0.66-0.93), sensitivity 0.65 (95% CI 0.48-0.56) at 90% specificity for CA19-9 alone (p = 0.0082 and p = 0.024, respectively). When validated only on the benign disease controls and PDACs collected from ADEPTS, the diagnostic-specific signature achieved an AUC of 0.96 (95% CI 0.92-0.99), sensitivity 0.82 (95% CI 0.64-0.95) at 90% specificity, which was still significantly higher than the performance for CA19-9 taken as a single predictor, AUC of 0.79 (95% CI 0.64-0.93) and sensitivity of 0.18 (95% CI 0.03-0.69) (p = 0.013 and p = 0.0055, respectively). Our ensemble modelling technique outperformed CA19-9, individual biomarkers and indices developed with prevailing algorithms in distinguishing patients with non-specific but concerning symptoms from those with PDAC, with implications for improving its early detection in individuals at risk.

Regulating Aggregation-Induced Emission Luminogen for Multimodal Imaging-Navigated Synergistic Therapy Involving Anti-Angiogenesis.

As a new avenue for cancer research, phototheranostics has shown inexhaustible and vigorous vitality as it permits real-time diagnosis and concurrent in situ therapy upon non-invasive light-initiation. However, construction of an advanced material, allowing prominent phototheranostic outputs and synchronously surmounting the inherent deficiency of phototheranostics, would be an appealing yet significantly challenging task. Herein, an aggregation-induced emission (AIE)-active luminogen (namely DBD-TM) featured by intensive electron donor-acceptor strength and twisted architecture with finely modulated intramolecular motion, is tactfully designed and prepared. DBD-TM simultaneously possessed fluorescence emission in the second near-infrared (NIR-II) region and high-efficiency photothermal conversion. By integrating DBD-TM with anti-angiogenic agent sorafenib, a versatile nanomaterial is smoothly fabricated and utilized for trimodal imaging-navigated synergistic therapy involving photothermal therapy and anti-angiogenesis toward cancer. This advanced approach is capable of affording accurate tumor diagnosis, complete tumor elimination, and largely restrained tumor recurrence, evidently denoting a prominent theranostic formula beyond phototheranostics. This study will offer a blueprint for exploiting a new generation of cancer theranostics.

MicroRNA-98 as a novel diagnostic marker and therapeutic target in cancer patients.

The progress of cancer treatment methods in the last decade has significantly reduced mortality rate among these patients. Nevertheless, cancer is still recognized as one of the main causes of human deaths. One of the main reasons for the high death rate in cancer patients is the late diagnosis in the advanced tumor stages. Therefore, it is necessary to investigate the molecular biology of tumor progressions in order to introduce early diagnostic markers. MicroRNAs (miRNAs) have an important role in regulating cellular processes associated with tumor progression. Due to the high stability of miRNAs in body fluids, they are widely used as non-invasive markers in the early tumor diagnosis. Since, deregulation of miR-98 has been reported in a wide range of cancers, we investigated the molecular mechanisms of miR-98 during tumor progression. It has been reported that miR-98 mainly inhibits the tumor growth by the modulation of transcription factors and signaling pathways. Therefore, miR-98 can be introduced as a tumor marker and therapeutic target among cancer patients.

Glomus tumor of gastric antrum: A rare differential

Introduction: Gastric glomus tumor is a rare clinical entity. Surgical excision could be avoided in selected patients if the diagnosis of glomus tumor could be made preoperatively. Cross-sectional imaging and endoscopic ultrasound (EUS) provide vital clues to nudge us in the right direction; however, these are inconclusive. Histopathology remains the gold standard for diagnosis of this condition. Case Report: We report a case of a man in his 60s who presented to the surgical outpatient clinic with long-standing history of abdominal bloating and discomfort. Upper gastrointestinal endoscopy revealed a submucosal lesion, and contrast-enhanced computed tomography (CECT) of the abdomen revealed a homogeneously enhancing lesion in the antrum of the stomach. Following successful surgical excision, histopathological examination established the diagnosis of gastric glomus tumor. This case presentation elaborates on the clinical features of this rare clinical entity and the various options available for diagnosis and management. Conclusion: Glomus tumors are rare mesenchymal tumors that need to be differentiated from other submucosal lesions and should be considered as a differential for submucosal lesions in the distal stomach. Endoscopic ultrasound and CT findings may provide clues to guide us toward the diagnosis; however, diagnosis can be confirmed only with histopathology. Surgical excision with negative margins either by laparoscopic or open operation is the treatment of choice.

Top 100 cited articles related to EUS: A bibliometric analysis

ABSTRACT Background and Objectives Citation analysis is a fundamental method in bibliometrics for quantifying the impact and contribution of articles on a specific biomedical field. The purpose of our study was to identify and analyze the top 100 cited articles in the field of EUS. Methods All published articles in the field of EUS were searched by using “endoscopic ultrasound” and its synonyms as the search terms without time limit. The Institute for Scientific Information Web of Science Core database was searched to determine the citations. The top 100 cited articles were identified and further evaluated for characteristics including publication year, authors, journals, impact factor, countries, institutions, article type, topic term, and evidence grade, among others. Results A total of 430 articles were cited more than 100 times. The 100 most-cited articles were published between 1988 and 2018, and the medium citation was 240.5 (104.25). The top 100 cited articles mainly focused on diagnostic performance (80%) and interventional therapy (20%). The numbers of articles studying the diagnostic accuracy of FNA (n = 29) and tumor diagnosis (n = 29) were the highest among research articles on FNA and EUS of diagnostic categories, and EUS transluminal drainage (n = 14) was the most frequently used EUS technique for therapy. The focus of the majority of the articles was on diseases of pancreas (n = 55), and among the 55 articles related to pancreatic diseases, pancreatic cancer (n = 17) and solid pancreatic masses (n = 13) were the most researched topics. In addition, we found that the proportions of diagnostic and treatment-related articles at different time periods have statistical significance (P &lt; 0.05). Conclusions Our analysis provides an insight into the top 100 articles in the field of EUS, revealing EUS-guided FNA, tumor staging, and transluminal drainage as the major advances in the past 35 years. Pancreatic diseases were the most researched, especially pancreatic cancer or solid pancreatic masses. Our research has found that the number of articles on the application of EUS treatment has significantly increased.

Liquid Biopsy-Based Accurate Diagnosis and Genomic Profiling of Hard-to-Biopsy Tumors via Parallel Single-Cell Genomic Sequencing of Exfoliated Tumor Cells.

Liquid biopsy provides a convenient and safer procedure for the diagnosis and genomic profiling of tumors that are inaccessible to biopsy by analyzing exfoliated tumor cells (ETCs) or tumor-derived cell-free DNA (cfDNA). However, its primary challenge lies in its limited accuracy in comparison to tissue-based approaches. We report a parallel single-ETC genomic sequencing (Past-Seq) method for the accurate diagnosis and genomic profiling of hard-to-biopsy tumors such as cholangiocarcinoma (CCA) and upper tract urothelial carcinoma (UTUC). For CCA, a prospective cohort of patients with suspicious biliary strictures (n = 36) was studied. Parallel single-cell whole genome sequencing and whole exome sequencing were performed on bile ETCs for CCA diagnosis and resolving mutational profiles, respectively, along with bile cfDNA sequenced for comparison. Concordant single-cell copy number alteration (CNA) profiles in multiple ETCs provided compelling evidence for generating a malignant diagnosis. Past-Seq yielded bile-based accurate CCA diagnosis (96% sensitivity, 100% specificity, and positive predictive value), surpassing pathological evaluation (56% sensitivity) and bile cfDNA CNA analysis (13% sensitivity), and generated the best performance in the retrieval tissue mutations. To further explore the applicability of Past-Seq, 10 suspicious UTUC patients were investigated with urine specimens, and Past-Seq exhibited 90% sensitivity in diagnosing UTUC, demonstrating its broad applicability across various liquid biopsies and cancer types.

A Linear time shrinking-SL(t)-ViT approach for brain tumor identification and categorization

Automated brain tumor detection and classification systems have gained popularity in recent years because traditional diagnosis procedures are time-consuming and costly in nature. Deep learning(DL) methods, specifically pre-trained convolutional neural networks (CNNs), have shown promising results in accurately and rapidly classifying brain tumors. However, the lack of diverse magnetic resonance imaging (MRI) datasets has hindered the ability of DL algorithms to generalize effectively. To address this issue, this paper proposes a DL model using generative adversarial networks (GANs) in conjunction with data augmentation strategies and a structural similarity loss function employed for generating annotated images. A novel DL model inspired from Vision Transformer, Shrinking Linear Time Vision Transformer (SL(t)-ViT) network model is proposed for disease data classification. The model underwent extensive evaluation across multiple datasets, employing standard performance metrics to assess its efficacy in brain tumor identification. The proposed model achieved remarkable testing accuracies of 0.995, 0.996, 0.9954, 0.998, and 0.997 for binary classification tasks across multiple datasets, and 0.986, 0.982, 0.985, and 0.993 for multi-class classification tasks. These results underscore the superior performance of our proposed model, showcasing its capability to outperform state-of-the-art techniques. Specifically, it demonstrated a substantial margin of improvement, ranging from 1-2% for binary classification and 9-10% for multi-class classification, solidifying its position as a leading approach in brain tumor identification. Results demonstrate the efficacy of the proposed model, outperforming other models. Overall, this study highlights the potential of SL(t)-ViT and GANs in improving the accuracy, resource consumption, and efficiency of brain tumor diagnosis.

The Current State of Regionalization in Otolaryngologic Specialized Tumor Care for Tumor Diagnoses.

The current extent of otolaryngologic cancer care regionalization is unclear. This study characterizes case volume regionalization patterns for 4 distinct otolaryngologic tumors-head and neck squamous cell carcinomas (HNSCCs), thyroid cancers (TCs), vestibular schwannomas, and pituitary adenomas (PAs). The 2010-2016 National Cancer Database was queried for patients with HNSCCs, TCs, vestibular schwannomas, and PAs. Facility geographic locations were divided into 4 geographical quadrants. High-volume facilities (HVFs) were defined as top 100 by volume facility for ≥1 pathology. A total of 191/1342 facilities (4.2%) were defined as an HVF. Vestibular schwannoma was the most regionalized, with 65.9% of patients treated at an HVF. Thyroid cancer (37.4%) and HNSCC (38.8%) were the least commonly treated at HVFs. Forty-one/191 (21.5%) were classified as HVFs for all 4 pathologies. Factors predictive of treatment at HVFs included age <65, higher income, and private insurance, larger tumor size, and lower American Joint Committee on Cancer stage. Over 20% of HVFs were considered high-volume for all 4 pathologies. Vestibular schwannomas were the most regionalized compared with PAs, TCs, and HSNCCs.

Complexities and challenges in the diagnosis and management of borderline thyroid tumors

Complexities and challenges in the diagnosis and management of borderline thyroid tumors

Complex TV and complex feminism: Laure Berthaud and co. in Engrenages/Spiral

ABSTRACT The long-running French detective series Engrenages/Spiral (2005–2020) anticipates and participates in the changing ecosystem of French TV, one that transnationalises and hybridises content in a global marketplace. Laure Berthaud (Caroline Proust) is one of many female detectives who emerge in this era. Through carefully crafting realist settings for its convoluted narratives, Engrenages enmeshes Berthaud into a professional web of dependency and rivalry, working not only with fellow detectives but also magistrate François Roban (Philippe Duclos) and lawyer Joséphine Karlsson (Audrey Fleurot). Berthaud and Karlsson are representative of considerable feminist influence in French popular culture in its representation of female characters in profes sional roles. However, in S06 they both undergo experiences which pit their female embodiment against their professional success. The series thus both celebrates and punishes its female protagonists for their transgressions, echoing and constituting the complex position of feminism in French popular culture. Roban’s brain tumour diagnosis during this season furthers its critical stance on the French justice system and its inability to truly account for human vulnerability in its myth of the autonomous French citizen.

Clinical fluorescence-guide surgery: Tracking leucine aminopeptidase for assisting head and neck squamous cell carcinoma surgery via a near-infrared fluorescent probe

The complete excision of tumors is critical for surgical treatment and the most used for intraoperative margin control method is frozen section analysis (FSA). However, due to its subjective and time-intensive property, there is still a lack of a rapid and effective means to clearly delineate the boundaries between normal and tumor tissues. In this work, we first demonstrated that leucine aminopeptidase (LAP) is highly expressed in clinical head and neck squamous cell carcinoma (HNSCC) and could be used as a biomarker of HNSCC. Based on this, we reported a LAP-activated fluorescent probe, SiR-LAP, and showed its effectiveness in identifying HNSCC. Importantly, we also demonstrated that the fluorescence imaging results of the probe in human tumor tissues are highly consistent with pathological staining results, highlighting its potential as an adjunct to surgical resection. In addition, intraoperative pathology section detection by fluorescent probe technology took half the time required for H&E staining. This research is poised to advance the application of fluorescent probes in tumor diagnosis and surgical excision assistance.

Decoding the microbiota metabolome in hepatobiliary and pancreatic cancers: Pathways to precision diagnostics and targeted therapeutics

We delve into the critical role of the gut microbiota and its metabolites in the pathogenesis and progression of hepatobiliary and pancreatic (HBP) cancers, illuminating an urgent need for breakthroughs in diagnostic and therapeutic strategies. Given the high mortality rates associated with HBP cancers, which are attributed to aggressive recurrence, metastasis, and poor responses to chemotherapy, exploring microbiome research presents a promising frontier. This research highlights how microbial metabolites, including secondary bile acids, short-chain fatty acids, and lipopolysaccharides, crucially influence cancer cell behaviors such as proliferation, apoptosis, and immune evasion, significantly contributing to the oncogenesis and progression of HBP cancers. By integrating the latest findings, we discuss the association of microbial alterations with HBP cancers, key metabolites, and their implications, and how metabolomics and microbiomics can enhance diagnostic precision. Furthermore, the paper explores strategies for targeted therapies through microbiome metabolomics, including the direct therapeutic effects of microbiome metabolites and potential synergistic effects on conventional therapies. We also recognize that the field of microbial metabolites for the diagnosis and treatment of tumors still has a lot of problems to be solved. The aim of this study is to pioneer microbial metabolite research and provide a reference for HBP cancer diagnosis, treatment, and prognosis.