This study aimed to devise a diagnostic algorithm, termed the Refined Radiomics and Deep Learning Features-Guided CatBoost Classifier (RRDLC-Classifier), and evaluate its efficacy in predicting pathological high-grade patterns in patients diagnosed with clinical stage I solid lung adenocarcinoma (LADC).

Since the response of patients with rectal cancer (RC) to neoadjuvant therapy is highly variable, there is an urgent need to develop accurate methods to predict the post-treatment T (pT) stage. The purpose of this study was to evaluate the utility of multi-parametric MRI radiomics models and identify the most accurate machine learning (ML) algorithms for predicting pT stage of RC.

This study evaluated the efficacy of radiomic analysis with optimal volumes of interest (VOIs) on computed tomography images to preoperatively differentiate invasive mucinous adenocarcinoma (IMA) from non-mucinous adenocarcinoma (non-IMA) in patients with incidental pulmonary nodules (IPNs).

A clinical challenge in esophageal squamous cell carcinoma (ESCC) remains the lack of applicable plasma biomarkers for screening and diagnosis. Circular RNAs (circRNAs) hold great potential as biomarkers for cancer. The study aims to explore a circRNA as a potential plasma biomarker for screening strategies and diagnostic approaches to ESCC.

Ultrasound (US) based radiomics is susceptible to variations in scanners, sonographers. To retrospectively investigate the feasibility of an adapted cycle generative adversarial networks (CycleGAN) in the style transfer to improve US based radiomics in the prediction of lymph node metastasis (LNM) with images from multiple scanners for patients with early cervical cancer (ECC). The CycleGAN was firstly trained to transfer paired US phantom images from one US device to another one; the model was then further trained and tested with clinical US images of ECC by transferring images from four US devices to one specific device; finally, the adapted model was tested with its effects on the radiomics feature harmonization and accuracy of LNM prediction in US based radiomics for ECC patients. Phantom study demonstrated an increased radiomics harmonization using CycleGAN with an average Pearson correlation coefficient of 0.60 and 0.81 for radiomics features extracted from original and generated images in correlation with the target phantom images, respectively. Additionally, the image quality metric Peak Signal-to-Noise Ratio (PSNR) was increased from 11.18 for the original images to 15.45 for the generated image. Clinical US images of 169 ECC patients were enrolled for style transfer model training and validation. The area under curve (AUC) of LNM prediction radiomics models with features extracted from generated images of different style transfer models ranged from 0.73 to 0.85. The AUC was improved from 0.78 with features extracted from original images to 0.85 with style transferred images. The adapted CycleGAN network is able to increase the radiomics feature harmonization for images from different ultrasound equipment based on image domain and improve the LNM prediction accuracy for ECC.

The management of early-stage colon cancer involves surgical resection of the primary tumor with or without chemotherapy, depending on pathological staging. The benefit of adjuvant chemotherapy for stage II and III colon cancer is approximately 5% and 15%, indicating the need for optimization for risk stratification and patient selection. Several studies have revealed that current clinicopathological factors lack precision. Circulating tumor DNA (ctDNA) is cell-free DNA originating from cancer cells and can be detected even in the absence of radiologically detectable disease among patients with colon cancer. Recent cohort studies revealed that ctDNA is one of the most significant prognostic factors for patients with early-stage colon cancer, surpassing pathological and clinical risk factors. Prospective cohort studies also suggest there may be a predictive role for ctDNA on the decision for consideration of adjuvant therapy. Currently, randomized clinical trials are enrolling to better define this role. In this review article, we review recent literature on ctDNA and its role in patients with colon cancer. We also elaborate on the future clinical utility of ctDNA in clinical practice and the unmet need for research to optimize currently available ctDNA assays.

We conducted a systematic review to compile the findings of all published studies on the use of percutaneous laser ablation (PLA) in the treatment of early-stage breast cancer. We aimed to identify appropriate methodology as well as parameters for the selection of suitable patients to optimize outcomes with the use of PLA. Additionally, we aimed to analyze whether this method is a viable alternative to current surgical treatments employed. The PRISMA 2020 method was applied. The terms "laser ablation" AND "breast cancer" were used to select all articles published up to January 2024 on the PubMed and Embase platforms. Articles in English were included. Only original articles were considered for this systematic review. Review articles, editorials, letters, and studies ex-vivo or not performed in humans were excluded. Seventeen articles, including 308 patients were analyzed. Among the studies describing the complete response rate to assess treatment success, there was no residual tumor after ablation in 74.4% of the patients. MRI was the best exam to evaluate the effectiveness of the ablative procedure with a NPV of 92% to 100%. Skin burn was the most commonly observed complication, occurring in 6% of patients. Other less frequent complications were hematoma/bleeding, pain, nodulation, erythema, seroma, and fat necrosis. The use of PLA remains restricted to cases with specific indications or within the context of research protocols. However, future studies may validate this promising technique for the local treatment of early-stage breast cancer. This study was registered at INPLASY (registration number: INPLASY2024100045).

Non-subungual glomus tumor in the fingers is very rare. To explore the insights gained from diagnosing and treating non-subungual glomus tumors in the finger, we collected 19 cases in the last ten years, which were only reported as isolated cases in the previous literature. This was a retrospective study of 19 surgical patients between May 2012 and January 2022 with preoperative MRI, ultrasound, and their final pathological diagnosis is glomus tumor, while the lesions were located not under the nail bed. Immunohistochemistry indicated that SMA(+)100%, CD34(+)89.5%, Ki-67(+1∼3%)68.4%, CD31(vessel+)26.3%, Desmin(+)21%, Calponin(+) 10.5%, Vimentin(+)5.2%, Caldesmon(+)5.2%. The sensitivity of preoperative MRI was 100%, while the sensitivity of ultrasound was 63.2%. And the diagnosing accuracy rate of preoperative MRI was 36.8%. Preoperative MRI is helpful in the diagnosis of non-subungual glomus tumor in fingers. Ultrasound can be used as a supplemental examination technique, and the results depend on the operator and tumor location. Surgical excision is an effective therapy for non-subungual GT in the fingers.

Metastasis remains a major cause of death among patients with malignant tumors. Radiotherapy is one of the main modalities of cancer treatment. The rapid development of radiotherapy technology has enabled the widespread application of hypofractionated radiotherapy (HFRT) in clinical practice. This study aimed to evaluate the effect of HFRT on the survival and safety of patients with oligometastatic tumors.

The contemporary concept of carcinogenesis summarizes the role of hypoxia, neoangiogenesis, and hemostasis, including in the stage of progression and metastasis of the tumor process. Metastatic disease is a serious therapeutic challenge for any oncological condition. The purpose of this study was to evaluate the dynamics of specific indicators of neoangiogenesis and hypoxia as potential biomarkers for therapeutic efficacy or risk of disease progression in patients with brain metastases (BM) undergoing robotic stereotactic radiosurgery. Two groups of patients (lung cancer and other types of cancers) with oligometastatic disease and brain metastases were included. The patients (n = 66) were treated CyberKnife system. Human Angiopoietin-2, Hypoxia inducible factor 1 α (HIF-1α) and human Vascular Endothelial Growth Factor-А (VEGF-А) were measured in this prospective longitudinal study. Analysis of human Angiopoietin-2, HIF-1α, human VEGF-A in the post-treatment period showed a statistically significant decrease between the baseline and the 6 months post-treatment time point in both patient groups. The baseline value of serum VEGF-А in the group with lung cancer decreased by 40%, Аngiopoietin-2-by 48%, HIF-1α -by 43%. In the group with other types of cancers, VEGF-А decreased by 54.75%, Аngiopoietin-2-by 52%, HIF-1α -by 39.5%. Despite the significant reduction, the levels remained significantly higher in both groups than in healthy controls. This study underscores the potential of integrating molecular markers like VEGF-A, Angiopoietin-2, and HIF-1α into clinical decision-making to enhance outcomes for patients with brain metastases undergoing RSRS.

To evaluate the impact of patient setup errors on the dosimetry and radiobiological models of intensity-modulated radiotherapy (IMRT) for esophageal cancer.

MR-guided radiotherapy (MRgRT) is novel treatment modality in Radiation Oncology that could allow a higher precision and tolerability of Radiation Treatments. This modality is possible due to dedicated systems consisting of a MR scanner mounted on a conventional linac and software that permit daily online treatment plan adaptation. Prostate cancer (PC) is one of the most common malignancies in RO clinical practice and currently under investigation with this new technology. The focus of this review is to describe the current state of the art and clinical results of MRgRT in the treatment of PC. The available technology are briefly described, as well as the published literature and possible future applications.

Long non-coding RNAs (lncRNAs) are known to play vital roles in human cancers. LncRNA TRPM2-AS has been found to be upregulated in various types of cancers. The elevated levels of TRPM2-AS are associated with important clinicopathological parameters such as tumor size, tumor stage, and lymph node metastasis, revealing that TRPM2-AS could be a potential target for cancer diagnosis, prognosis and treatment. Moreover, TRPM2-AS is involved in regulating the cell proliferation, migration, invasion, apoptosis, drug or radio resistance by serving as a competing endogenous RNA, directly bounding to proteins and regulating multiple signaling pathways. In this review, we comprehensively summarize the latest knowledge on the aberrant expression of TRPM2-AS, the relationship between TRPM2-AS and clinical features, and the detailed mechanisms of potential functions of TRPM2-AS in various cancer types. The current study highlights the potential of TRPM2-AS as a prognostic and therapeutic target in cancers.

For advanced hepatocellular carcinoma (HCC), sorafenib remains the established therapy. PD-1/PD-L1 inhibitors plus antiangiogenic drugs (PIAD) as a new therapeutic approach for advanced HCC is still a subject of clinical debate regarding whether they offer improved treatment outcomes. This study was conducted to compare the two treatments in terms of antitumor efficacy and safety.

This study developed a drug delivery system (DDS) using folic acid (FA)-functionalized chitosan (CS) and poly (lactic-co-glycolic acid) (PLGA) nanocarriers for targeted sodium butyrate (NB) delivery to leukemia cells (NALM6). The goal was to enhance NB's therapeutic efficacy while reducing its cytotoxicity to non-malignant cells.

To evaluate the diagnostic performance of CT radiomic features extracted from tumor and peritumoral regions in identifying pathological subtypes of T1-stage lung adenocarcinoma presenting as pure ground-glass nodules (pGGNs). A retrospective analysis was conducted on the data of T1-stage lung adenocarcinoma patients who underwent surgical resection and whose preoperative CT scans revealed pGGNs from June 2020 to June 2023 in our hospital. 3D Slicer was used to extract radiomic features of the intratumoral (VOI entire) and peritumoral regions (VOI +2 mm), and Rad-scores were calculated from the coefficients of features obtained after dimensionality reduction with LASSO regression. A total of 131 patients with T1-stage lung adenocarcinoma presenting as pGGNs were included in this study; of these, 84 were pathologically diagnosed with the lepidic-predominant (LPA) subtype, and 47 were diagnosed with non-LPA. The diagnostic performance of the VOI entire and VOI +2 mm features for the pathological subtype of pGGN was superior to that of conventional features, with the VOI +2 mm features showing the best performance: the area under the curve, sensitivity, specificity, and accuracy in the training set were 0.883, 0.964, 0.667, and 0.761, respectively. Intra- and especially peritumoral-based radiomic features have high diagnostic performance for the pathological subtype of T1-stage lung adenocarcinoma presenting as pGGNs.

Thyroid cancer, a prevalent endocrine malignancy, often presents as thyroid nodules, whose benign or malignant nature is challenging to determine. This study aims to identify circulating miRNA panels that may distinguish between benign nodules, papillary thyroid cancer, and normal thyroid conditions, building on extensive research into miRNAs as potential thyroid cancer biomarkers.

Mitochondrial fusion is vital for cellular function and has been increasingly linked to cancer development. Kidney renal papillary cell carcinoma (KIRP), the second most common renal cell carcinoma, presents diverse prognostic outcomes. Identifying novel biomarkers is critical for improving prognosis and treatment response in KIRP.

Clear cell renal cell carcinoma (ccRCC) is a highly lethal urinary malignancy with poor overall survival (OS) rates. Integrating computer vision and machine learning in pathomics analysis offers potential for enhancing classification, prognosis, and treatment strategies for ccRCC. This study aims to create a pathomics model to predict OS in ccRCC patients. In this study, data from ccRCC patients in the TCGA database were used as a training set, with clinical data serving as a validation set. Pathological features were extracted from H&E-stained slides using PyRadiomics, and a pathomics model was constructed using the non-negative matrix factorization (NMF) algorithm. The model's predictive performance was assessed through Kaplan-Meier (KM) survival curves and Cox regression analysis. Additionally, differential gene expression, gene ontology (GO) enrichment analysis, immune infiltration, and mutational analysis were conducted to investigate the underlying biological mechanisms. A total of 368 pathomics features were extracted from H&E-stained slides of ccRCC patients, and a pathomics model comprising two subtypes (Cluster 1 and Cluster 2) was successfully constructed using the NMF algorithm. KM survival curves and Cox regression analysis revealed that Cluster 2 was associated with worse OS. A total of 76 differential genes were identified between the two subtypes, primarily involving extracellular matrix organization and structure. Immune-related genes, including CTLA4, CD80, and TIGIT, were highly expressed in Cluster 2, while the VHL and PBRM1 genes, along with mutations in the PI3K-Akt, HIF-1, and MAPK signaling pathways, exhibited mutation rates exceeding 40% in both subtypes. The machine learning-based pathomics model effectively predicts the OS of ccRCC patients and differentiates between subtypes. The critical roles of the immune-related gene CTLA4 and the PI3K-Akt, HIF-1, and MAPK signaling pathways offer new insights for further research on the molecular mechanisms, diagnosis, and treatment strategies for ccRCC.

This review article aims to synthesize existing data on radiation-induced heart diseases in patients undergoing chest radiation therapy and also explores cardiac-sparing techniques to mitigate cardiotoxic effects. We conducted a comprehensive database search to review and consolidate data regarding chest radiotherapy and effects on the heart as well as techniques to minimize exposure to the heart. The research findings demonstrate associations between radiation exposure to cardiac substructures and subsequent cardiotoxicity. This review also stresses the importance of identifying patients at high-risk for cardiotoxicity as well as advocates for the adoption of stringent cardiac dose constraints in these patients. Advanced cardiac-sparing techniques, notably respiratory motion management, have emerged as pivotal strategies to minimize the likelihood of cardiac events. This narrative review emphasizes the critical role of these innovations in optimizing cardiac health during radiation treatment.

Doxorubicin (DOX) is a potent chemotherapeutic agent for breast cancer, but its effectiveness is often diminished by resistance mechanisms, particularly through p-glycoprotein (P-gp) mediated drug efflux. Clarithromycin (CAM), a macrolide antibiotic, inhibits multiple metabolic pathways including CYP3A and P-gp, potentially countering DOX resistance.