Precise and automated lung cancer cell classification using deep neural network with multiscale features and model distillation.

Lung diseases globally impose a significant pathological burden and mortality rate, particularly the differential diagnosis between adenocarcinoma, squamous cell carcinoma, and small cell lung carcinoma, which is paramount in determining optimal treatment strategies and improving clinical prognoses. Faced with the challenge of improving diagnostic precision and stability, this study has developed an innovative deep learning-based model. This model employs a Feature Pyramid Network (FPN) and Squeeze-and-Excitation (SE) modules combined with a Residual Network (ResNet18), to enhance the processing capabilities for complex images and conduct multi-scale analysis of each channel's importance in classifying lung cancer. Moreover, the performance of the model is further enhanced by employing knowledge distillation from larger teacher models to more compact student models. Subjected to rigorous five-fold cross-validation, our model outperforms existing models on all performance metrics, exhibiting exceptional diagnostic accuracy. Ablation studies on various model components have verified that each addition effectively improves model performance, achieving an average accuracy of 98.84% and a Matthews Correlation Coefficient (MCC) of 98.83%. Collectively, the results indicate that our model significantly improves the accuracy of disease diagnosis, providing physicians with more precise clinical decision-making support.

Purulent Pericarditis as the First Manifestation of Esophageal Carcinoma.

INTRODUCTION: Purulent pericarditis secondary to esophago-pericardial fistula is a serious complication that has been previously reported in patients with esophageal cancer treated with radio/chemotherapy and esophageal stenting. However, the presence of esophago-pericardial fistula as the first manifestation of advanced carcinoma of the esophagus is exceedingly infrequent. We report the case of a 61-year-old male who presented with sepsis, cardiac tamponade and septic shock who was found to have an esophago-pericardial fistula secondary to squamous carcinoma of the esophagus. Emergency pericardiocentesis was performed with subsequent hemodynamic improvement. The drained pericardial fluid was purulent in nature and cultures were positive for Streptococcus anginosus. A CT scan followed by upper gastrointestinal endoscopy with tissue biopsy confirmed the diagnosis of squamous cell carcinoma of the esophagus. A self-expanding covered stent was endoscopically placed to exclude the fistula and restore the esophageal lumen. In this report, we discuss some aspects related to the diagnosis and management of this serious clinical entity.

Cutaneous squamous cell carcinoma characterized by MALDI mass spectrometry imaging in combination with machine learning.

Cutaneous squamous cell carcinoma (SCC) is an increasingly prevalent global health concern. Current diagnostic and surgical methods are reliable, but they require considerable resources and do not provide metabolomic insight. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) enables detailed, spatially resolved metabolomic analysis of tissue samples. Integrated with machine learning, MALDI-MSI could yield detailed information pertaining to the metabolic alterations characteristic for SCC. These insights have the potential to enhance SCC diagnosis and therapy, improving patient outcomes while tackling the growing disease burden. This study employs MALDI-MSI data, labelled according to histology, to train a supervised machine learning model (logistic regression) for the recognition and delineation of SCC. The model, based on data acquired from discrete tumor sections (n = 25) from a mouse model of SCC, achieved a predictive accuracy of 92.3% during cross-validation on the labelled data. A pathologist unacquainted with the dataset and tasked with evaluating the predictive power of the model in the unlabelled regions, agreed with the model prediction for over 99% of the tissue areas. These findings highlight the potential value of integrating MALDI-MSI with machine learning to characterize and delineate SCC, suggesting a promising direction for the advancement of mass spectrometry techniques in the clinical diagnosis of SCC and related keratinocyte carcinomas.

The role of seven tumor-associated autoantibodies in the diagnosis, staging and treatment guidance of lung cancer.

BACKGROUND: This study assessed the diagnosis, staging and treatment guidance of lung cancer (LC) based on seven tumor-associated autoantibodies (TAAbs) -p53, PGP9.5, SOX2, GBU4-5, MAGE A1, CAGE, and GAGE7. METHODS: ELISA was used to determine the TAAb serum levels in 433 patients diagnosed with LC (161 surgical patients) and 76 patients with benign lung disease (16 surgical patients). The statistical characteristic of the TAAbs was compared among patients with different clinicopathological features. Pre- to postoperative changes in TAAb levels were analyzed to determine their value of LC. RESULTS: Among all patients, the positive rate of the seven TAAbs was 23.4%, sensitivity was 26.3%, accuracy was 36.3%, specificity was 93.4%, positive predictive value was 95.8%, and negative predictive value was 18.2%; the positive rate for the LC group (26.3%) was significantly higher than that for the benign group (6.6%; P < 0.001). Significant differences in the positive rate of the seven autoantibodies according to age (P < 0.001), smoking history (P = 0.009) and clinical LC stage (P < 0.001) were found. Smoking was positively associated with the positive of TAAbs (Τ = 0.118, P = 0.008). The positive rates of the seven TAAbs for squamous carcinoma (54.5%), other pathological types (44.4%) and poorly differentiated LC (57.1%) were significantly higher than those for the other types. The positive rate of GBU4-5 was highest among all TAAbs, and the SOX2 level in stage III-IV patients was much higher than that in other stages. For patients undergoing surgery, compared with the preoperative levels, the postoperative levels of the 7 markers, particularly p53 (P = 0.027), PGP9.5 (P = 0.007), GAGE7 (P = 0.014), and GBU4-5 (P = 0.002), were significantly different in the malignant group, especially in stage I-II patients, while no clear pre- to postoperative difference was observed in the benign group. CONCLUSIONS: When the seven TAAbs was positive, it was very helpful for the diagnosis of LC. The 7 TAAbs was valuable for staging and guiding treatment of LC in surgical patients.

Enhancing oral squamous cell carcinoma detection: a novel approach using improved EfficientNet architecture.

PROBLEM: Oral squamous cell carcinoma (OSCC) is the eighth most prevalent cancer globally, leading to the loss of structural integrity within the oral cavity layers and membranes. Despite its high prevalence, early diagnosis is crucial for effective treatment. AIM: This study aimed to utilize recent advancements in deep learning for medical image classification to automate the early diagnosis of oral histopathology images, thereby facilitating prompt and accurate detection of oral cancer. METHODS: A deep learning convolutional neural network (CNN) model categorizes benign and malignant oral biopsy histopathological images. By leveraging 17 pretrained DL-CNN models, a two-step statistical analysis identified the pretrained EfficientNetB0 model as the most superior. Further enhancement of EfficientNetB0 was achieved by incorporating a dual attention network (DAN) into the model architecture. RESULTS: The improved EfficientNetB0 model demonstrated impressive performance metrics, including an accuracy of 91.1%, sensitivity of 92.2%, specificity of 91.0%, precision of 91.3%, false-positive rate (FPR) of 1.12%, F1 score of 92.3%, Matthews correlation coefficient (MCC) of 90.1%, kappa of 88.8%, and computational time of 66.41%. Notably, this model surpasses the performance of state-of-the-art approaches in the field. CONCLUSION: Integrating deep learning techniques, specifically the enhanced EfficientNetB0 model with DAN, shows promising results for the automated early diagnosis of oral cancer through oral histopathology image analysis. This advancement has significant potential for improving the efficacy of oral cancer treatment strategies.

Assessing outcomes of topical 5-fluorouracil as primary and adjuvant therapy for squamous cell carcinoma in-situ.

Cutaneous squamous cell carcinoma in-situ (SCCis) is an intraepithelial tumor with a good prognosis. Standard treatment includes both surgical and non-surgical interventions. We determined the clearance rate for SCCis and residual SCCis identified on frozen section during Mohs micrographic surgery (MMS) after treatment with topical fluorouracil 5% cream (5-FU). All MMS cases were initiated for biopsy-proven invasive squamous cell carcinoma (SCC). A retrospective chart review was conducted from January 2017-February 2024 at Columbia University Irving Medical Center (CUIMC) to identify patients with SCCis who were treated with topical 5-FU as primary therapy or adjuvant therapy (AT) for residual SCCis post-MMS for invasive SCC. 41 patients were included (80% males, 70.1 ± 11.8 years). The average follow-up time for the primary therapy group was 25.4 ± 12.8 months, and for the post-MMS AT group 22.5 ± 11.1 months. In the group treated with topical 5-FU as primary therapy (n = 28), 27 patients (96.43%, 95% confidence interval: 81.65-99.91%) achieved complete clearance. One patient had recurrence at 8 months post-treatment. Of the patients in the post-MMS adjuvant treatment group (n = 13), 12 (92.3% clearance, 95% confidence interval 63.97-99.81%) achieved complete clearance. One patient had recurrence at 8 months post-treatment. This study found that topical 5-FU cream is effective as both primary therapy for SCCis and as adjuvant therapy for residual SCCis following MMS of invasive SCC.

Use of digital strategies in the diagnosis of oral squamous cell carcinoma: a scoping review.

Telediagnosis uses information and communication technologies to support diagnosis, shortening geographical distances. It helps make decisions about various oral lesions. The objective of this scoping review was to map the existing literature on digital strategies to assist in the diagnosis of oral squamous cell carcinoma. this review was structured based on the 5-stage methodology proposed by Arksey and O'Malley, the Joanna Briggs Institute Manual for Evidence Synthesis and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. The methods were registered on the Open Science Framework. The research question was: What digital strategies have been used to assist in the diagnosis of oral squamous cell carcinoma? The search was conducted on PubMed/MEDLINE, Scopus, Web of Science, Embase, and ScienceDirect. Inclusion criteria comprised studies on telediagnosis, teleconsultation or teleconsultation mediated by a professional and studies in English, without date restrictions. The search conducted in June 2023 yielded 1,798 articles, from which 16 studies were included. Telediagnosis was reported in nine studies, involving data screening through applications, clinical images from digital cameras, mobile phones or artificial intelligence. Histopathological images were reported in four studies. Both, telediagnosis and teleconsultation, were mentioned in seven studies, utilizing images and information submission services to platforms, WhatsApp or applications. One study presented teleconsultations involving slides and another study introduced teleconsultation mediated by a professional. Digital strategies telediagnosis and teleconsultations enable the histopathological diagnosis of oral cancer through clinical or histopathological images. The higher the observed diagnostic agreement, the better the performance of the strategy.

PIK3CA Hotspot Mutations in Saliva as a Diagnostic Marker in Oral Squamous Cell Carcinoma Patients.

BACKGROUND/AIM: This study aimed at the analogous detection of PIK3CA mutations, common in oral squamous cell carcinoma (OSCC), in matched tumor and saliva samples. PATIENTS AND METHODS: Tissue and saliva samples were obtained from 29 patients diagnosed with primary OSCC. Saliva samples were obtained preoperatively; tissue specimens were acquired during tumor resection. Tumor DNA was extracted from both tissue and saliva samples. All samples were controlled for DNA quantity and quality and genetic matching of sample pairs was confirmed using the iPlex Pro Exome QC Panel. Variant detection was performed using the MassARRAY® System, a mass-spectrometry based detection system. Mutational analysis in tissue tumor DNA was made using the multiplexed ClearSEEK™ PIK3CA v1.0 Panel covering 20 hotspot mutations in PIK3CA. In saliva samples, variants were analyzed using both the ClearSEEK™ and the UltraSEEK® Lung v1.1 Panel, with a higher limit of detection but covering less PIK3CA variants. RESULTS: Overall, a PIK3CA variant was found in seven of the 29 tumor tissue samples (24%) by ClearSEEK™; UltraSEEK® additionally confirmed the variant in four of these seven positive samples. Of the three variants not detected by UltraSEEK®, two were not included in the panel and one was included but not detected. Of the seven variants found in tissue, five could also be detected in the matching saliva samples (71%), either by utilizing ClearSEEK™ or UltraSEEK® Conclusion: The detection of PIK3CA hotspot mutations in OSCC and their simultaneous occurrence in saliva underline the potential benefit of liquid biopsies for non-invasive cancer detection and follow-up care of OSCC patients.

[Inaugural Scalp Metastasis of Pulmonary Squamous Cell Carcinoma: 
A Rare Case Report and Literature Review].

Distant cutaneous metastasis of primary lung squamous cell carcinoma is an exceedingly rare event, with scalp metastasis as the initial clinical presentation even rarer. Scalp skin metastases are prone to be misdiagnosed as other scalp disorders, yet their appearance signifies the deterioration and poor prognosis of lung cancer. This case report documents a female patient presenting initially with scalp folliculitis in dermatology, who was subsequently diagnosed with malignant lung tumor through radiological imaging and referred to Department of Thoracic Surgery. Pathological examination of the excised lesion from the scalp revealed distant metastasis of lung cancer. A review of similar cases reported in literature was conducted. This article aims to enhance understanding and awareness of skin metastasis in lung cancer, to emphasize the importance of this condition, and to improve early recognition and precise diagnosis. It is crucial to prevent clinical misdiagnosis and ensure appropriate treatment, finally leading to improve the prognosis of the patients.
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BIA-ALCL and BIA-SCC: Updates on Clinical Features and Genetic Mutations for Latest Recommendations.

Breast Implant-Associated Anaplastic Large Cell Lymphoma (BIA-ALCL) and Breast Implant-Associated Squamous Cell Carcinoma (BIA-SCC) are emerging neoplastic complications related to breast implants. While BIA-ALCL is often linked to macrotextured implants, current evidence does not suggest an implant-type association for BIA-SCC. Chronic inflammation and genetics have been hypothesized as key pathogenetic players, although for both conditions, the exact mechanisms and specific risks related to breast implants are yet to be established. While the genetic alterations in BIA-SCC are still unknown, JAK-STAT pathway activation has been outlined as a dominant signature of BIA-ALCL. Recent genetic investigation has uncovered various molecular players, including MEK-ERK, PI3K/AKT, CDK4-6, and PDL1. The clinical presentation of BIA-ALCL and BIA-SCC overlaps, including most commonly late seroma and breast swelling, warranting ultrasound and cytological examinations, which are the first recommended steps as part of the diagnostic work-up. While the role of mammography is still limited, MRI and CT-PET are recommended according to the clinical presentation and for disease staging. To date, the mainstay of treatment for BIA-ALCL and BIA-SCC is implant removal with en-bloc capsulectomy. Chemotherapy and radiation therapy have also been used for advanced-stage BIA-ALCL and BIA-SCC. In-depth characterization of the tumor genetics is key for the development of novel therapeutic strategies, especially for advanced stage BIA-ALCL and BIA-SCC, which show a more aggressive course and poor prognosis.

Mapping Conformational Changes in the Saliva Proteome Potentially Associated with Oral Cancer Aggressiveness.

Diverse proteomics-based strategies have been applied to saliva to quantitatively identify diagnostic and prognostic targets for oral cancer. Considering that these targets may be regulated by events that do not imply variation in protein abundance levels, we hypothesized that changes in protein conformation can be associated with diagnosis and prognosis, revealing biological processes and novel targets of clinical relevance. For this, we employed limited proteolysis-mass spectrometry in saliva samples to explore structural alterations, comparing the proteome of healthy control and oral squamous cell carcinoma (OSCC) patients with and without lymph node metastasis. Thirty-six proteins with potential structural rearrangements were associated with clinical patient features including transketolase and its interacting partners. Moreover, N-glycosylated peptides contribute to structural rearrangements of potential diagnostic and prognostic markers. Altogether, this approach utilizes saliva proteins to search for targets for diagnosing and prognosing oral cancer and can guide the discovery of potential regulated sites beyond protein-level abundance.

Molecular Pathology of Gastroesophageal Cancer.

Upper gastroesophageal carcinomas consist of cancers arising from the esophagus and stomach. Squamous cell carcinomas and adenocarcinomas are seen in the esophagus and despite arising from the same organ have different biology. Gastric adenocarcinomas are categorized into 4 molecular subtypes: high Epstein-Barr virus load, microsatellite unstable cancers, chromosomal unstable (CIN) cancers, and genomically stable cancers. Genomically stable gastric cancers correlate highly with histologically defined diffuse-type cancers. Esophageal carcinomas and CIN gastric cancers often are driven by high-level amplifications of oncogenes and contain a high degree of intratumoral heterogeneity. Targeted therapeutics is an active area of research for gastroesophageal cancers.

Circulating tumour cells predict recurrences and survival in head and neck squamous cell carcinoma patients.

Patients with head and neck squamous cell carcinoma (HNSCC) are at a high risk of developing recurrence and secondary cancers. This study evaluates the prognostic and surveillance utilities of circulating tumour cells (CTCs) in HNSCC. A total of 154 HNSCC patients were recruited and followed up for 4.5 years. Blood samples were collected at baseline and follow-up. CTCs were isolated using a spiral microfluid device. Recurrence and death due to cancer were assessed during the follow-up period. In patients with HNSCC, the presence of CTCs at baseline was a predictor of recurrence (OR = 8.40, p < 0.0001) and death (OR= ∞, p < 0.0001). Patients with CTCs at baseline had poor survival outcomes (p < 0.0001). Additionally, our study found that patients with CTCs in a follow-up appointment were 2.5 times more likely to experience recurrence or death from HNSCC (p < 0.05) prior to their next clinical visit. Our study highlights the prognostic and monitoring utilities of CTCs' in HNSCC patients. Early identification of CTCs facilitates precise risk assessment, guiding treatment choices and ultimately enhancing patient outcomes.

Near-infrared hyperspectral imaging and robust statistics for in vivo non-melanoma skin cancer and actinic keratosis characterisation.

One of the most common forms of cancer in fair skinned populations is Non-Melanoma Skin Cancer (NMSC), which primarily consists of Basal Cell Carcinoma (BCC), and cutaneous Squamous Cell Carcinoma (SCC). Detecting NMSC early can significantly improve treatment outcomes and reduce medical costs. Similarly, Actinic Keratosis (AK) is a common skin condition that, if left untreated, can develop into more serious conditions, such as SCC. Hyperspectral imagery is at the forefront of research to develop non-invasive techniques for the study and characterisation of skin lesions. This study aims to investigate the potential of near-infrared hyperspectral imagery in the study and identification of BCC, SCC and AK samples in comparison with healthy skin. Here we use a pushbroom hyperspectral camera with a spectral range of ≈ 900 to 1600 nm for the study of these lesions. For this purpose, an ad hoc platform was developed to facilitate image acquisition. This study employed robust statistical methods for the identification of an optimal spectral window where the different samples could be differentiated. To examine these datasets, we first tested for the homogeneity of sample distributions. Depending on these results, either traditional or robust descriptive metrics were used. This was then followed by tests concerning the homoscedasticity, and finally multivariate comparisons of sample variance. The analysis revealed that the spectral regions between 900.66-1085.38 nm, 1109.06-1208.53 nm, 1236.95-1322.21 nm, and 1383.79-1454.83 nm showed the highest differences in this regard, with <1% probability of these observations being a Type I statistical error. Our findings demonstrate that hyperspectral imagery in the near-infrared spectrum is a valuable tool for analyzing, diagnosing, and evaluating non-melanoma skin lesions, contributing significantly to skin cancer research.