Reports of Practical Oncology and Radiotherapy最新文献

Background: Stereotactic body radiotherapy (SBRT) is a well-accepted treatment for metastatic and primary lung cancer; however, an optimal regimen is still unclear for ultra central thoracic lesions. The objective of this manuscript is to report the toxicity of SBRT in patients with ultra-central tumors treated with 50 Gy in 5 fractions.

Materials and methods: We performed a retrospective review of patients with ultra-central lung lesions treated with SBRT in our institution at the dose of 50 Gy in 5 fractions, delivered every other day. Lesions were defined as ultra-central when the planning target volume (PTV) overlapped the trachea, proximal bronchial tree, great vessels, heart and esophagus. Constraints for organ at risk (OAR) were the ones used in the RTOG-0813 trial.

Results: 86 patients were included in this review. The median age was 74 years. The overlapping OAR were: the great vessels in 46 patients (53.4%), heart in 20 (23.2%), tracheobronchial tree in 18 (20.9%) and esophagus in 2 (2.3%). Median follow up was 17 months. The median overall survival was 39 months. There was no SBRT related grade 3 or greater acute or late toxicity.

Conclusion: In this cohort of patients with ultra-central thoracic lesions treated with 50 Gy in 5 fraction SBRT, no grade 3-5 acute or late toxicity was observed.

Background: To evaluate the predictive performance differences for postoperative 5-year survival risk for early-stage non-small cell lung cancer (NSCLC) patients with two image analysis methods based on ground-glass opacity (GGO) status and radiomics analysis. Moreover, we improve the accuracy of stratifying survival risk by combining radiomics with GGO status.

Materials and methods: Computed tomography (CT) images for 113 NSCLC patients were analyzed. The patients were divided into four groups according to %GGO step by 25%. The GGO model was built with the optimal cutoff %GGO value to categorize patients into high-risk or low-risk groups. The radiomics features were selected by the least absolute shrinkage and selection operator (LASSO)-Cox regression and these were incorporated into the Rad-score model. The combined model was created by integrating the GGO and Rad-score models. The survival rates between these groups were compared using Kaplan-Meier analysis, supplemented by log-rank tests.

Results: From LASSO-Cox regression, 5 features were selected. Multivariate Cox regression analysis in the Combined model identified GGO and Rad-score as independent predictive factors. The combined model (C-index: 0.664) performed best compared to the GGO model (C-index: 0.521) and the rad-score model (C-index: 0.642). The 5-year survival Kaplan-Meier curves for the rad-score and combined models were also able to stratify the patient population into low-risk and high-risk groups (p-values < 0.05).

Conclusion: A combined model, integrating the GGO status and Rad-score may help predict the prognosis of patients with early NSCLC more accurately, with a higher probability of outcome than a GGO model.

Background: The quality of volumetric-modulated arc therapy (VMAT) plans depends on the planner's expertise. A feasibility dose-volume histogram (FDVH) may help reduce planning variability.

Materials and methods: This study evaluated the impact of two linear accelerators - Halcyon and TrueBeam - on FDVH in prostate VMAT planning and their effectiveness in reducing doses to organs at risk (OARs). VMAT plans were generated for 30 patients with prostate cancer, with planning target volume excluding the rectum (PTV-R) and OAR contours created by three planners. An FDVH was created, and plans were classified as "difficult" (0 < F ≤ 0.1) based on OAR dose reduction.

Results: The D98% and D2% of PTV-R were analyzed, showing that TrueBeam had a higher mean dose at D98% and a lower mean dose at D2% compared to Halcyon, but these differences were not statistically significant (D98%: p = 0.123, D2%: p = 0.167). For the rectum, TrueBeam resulted in significantly lower doses for all dose constraints compared to Halcyon (p < 0.001). In the bladder, TrueBeam showed a significantly lower dose at V40Gy (p < 0.001). The upper limits of feasible F-values were 0.00-0.12 (TrueBeam) and 0.00-0.17 (Halcyon) for the rectum, and 0.01-0.20 (TrueBeam) and 0.00-0.20 (Halcyon) for the bladder, depending on dose parameters.

Conclusions: These findings highlight that the choice of the linear accelerator significantly impacts OAR dose reduction. In prostate VMAT, TrueBeam demonstrated superior rectal and bladder dose reduction compared to Halcyon, underscoring the importance of selecting the appropriate device to optimize treatment planning and minimize variability.

Background: Patients with hormone-dependent breast cancer (HDBC) are prescribed adjuvant endocrine therapy (AET) in the form of tamoxifen or aromatase inhibitors (AI), either as single-agent endocrine therapy (SAET) or with a switch between them. However, the decision to maintain either strategy remains controversial. We aimed to compare breast cancer-free survival (BCFS) and overall survival (OS) in Mexican patients with HDBC under AET, be it as SAET or switching mode.

Materials and methods: We retrospectively analyzed a cohort of 300 patients diagnosed between 2009 and 2014. The association of BCFS and OS with clinical variables was analyzed with Cox and binary logistic regression models.

Results: In the univariate Cox models, compared to AI-based SAET, only tamoxifen-based SAET [hazard ratio (HR): 1.93, 95% confidence interval (CI): 1.13-3.3] exhibited association with BCFS; this became non-significant in the multivariate model. In the multivariate logistic models, compared to AI-based SAET, both tamoxifen-based SAET [odds ratio (OR): 2.2, 95% CI: 1.2-4.2] and switching (OR: 2.8, 95% CI: 1.3--.9) schemes were associated with recurrence or death events. Additionally, patients with an AET duration longer than 36 (OR: 0.18, 95% CI: 0.06-0.54) and 60 (OR: 0.26, 95% CI: 0.09-0.75) months had 82% and 74% lower odds of experiencing recurrence/death, respectively.

Conclusions: The data revealed discrepancies between the logistic and Cox regression models regarding the administered AET. These findings may reflect differences in patient selection, and treatment adherence or duration. The data also underscore the relevance of considering AET duration, as extended treatment (> 36 and > 60 months) consistently demonstrated protective effects regardless of regimen.

Background: Radiotherapy (RT) dramatically reduces the risk of prostate cancer (PCa) recurrence and extends patient lifespans. Recent studies have begun identifying gene signatures and biomarkers that may predict and monitor RT responses. Hence, we investigated the effects of radiotherapy (RT) on competing endogenous RNA (ceRNA) networks, including long non-coding rinonucleic acid (lncRNA), microRNA (miRNA), and messenger RNA (mRNA), in high-risk prostate cancer (HrPCa) patients.

Materials and methods: The Gene Expression Omnibus (GEO) database was used to identify mRNAs with significant expression differences. The analysis largely followed the packages outlined in GEO2R. The TargetScan, miRanda, and LncRNA2Target databases were utilized to identify lncRNAs and miRNAs. Protein-protein interactions identified hub genes, and Gene Ontology terms revealed their critical pathways. Finally, 28 patients with HrPCa and 28 healthy subjects were included in the study. Whole blood samples were collected from all participants before and after RT. RNA extraction and cDNA synthesis were then performed, followed by real-time polymerase chain reaction (PCR) to determine the expression of candidate biomarkers. Due to the small sample size (n = 28), Hedges' g was used instead of Cohen's d to minimize bias.

Results: We identified 3,452 genes, including 1,951 up-regulated and 1,501 down-regulated genes, exhibiting significant differential expression in patients with HrPCa. Ultimately, three lncRNAs, seven miRNAs, and nine mRNAs were selected as candidates for comparison between HrPCa patients and healthy subjects. Unlike a significant increase in tumor suppressors, the expression levels of candidate onco-miRNAs, onco-lncRNAs, and oncogenes in HrPCa patients showed a substantial decrease after RT.

Conclusions: The ceRNA network monitoring might be emerging as a valuable tool for assessing treatment responses. However, future studies with larger cohorts are needed to validate these results.

Background: Cervical cancer (CC) is a leading cause of cancer-related deaths worldwide, emphasizing the need for accurate and efficient diagnostic tools. Traditional methods of cervical cell classification are time-consuming and susceptible to human error, highlighting the need for automated solutions.

Materials and methods: This study introduces the modified hierarchical deep feature fusion (HDFF) method for cervical cell classification using the SIPaKMeD and Herlev datasets. The novelty of this research lies in the integration of hierarchical deep learning features, which allows for more accurate and robust classification. By enhancing the feature extraction process and combining multiple layers of deep learning models, the Modified HDFF method improves classification performance across various tasks, ranging from binary to multi-class problems.

Results: Our results demonstrate that the Modified HDFF method significantly outperforms existing models. In the 2-class task, it achieves an impressive accuracy of 98.88%, surpassing other approaches such as RF-based hierarchical classification (98.43%). Additionally, it maintains high precision, recall, and F1-scores in multi-class tasks, with 98.8% accuracy in the 3-class problem and 98.5% in the 7-class problem.

Conclusions: Overall, the Modified HDFF method shows great promise as a reliable and efficient diagnostic tool for cervical cancer screening. Its superior accuracy across multiple classification tasks highlights its potential for improving early detection and public health outcomes. Further refinement and expanded training datasets can further enhance its performance, making it an invaluable asset in automated cervical cancer detection.

Background: To compare doses deposited to the liver during right breast radiotherapy with static and dynamic radiotherapy techniques. The second aim was to introduce the liver load index (LLI), a novel index developed to estimate radiation exposure to the liver prior to treatment selection.

Materials and methods: We prepared radiotherapy treatment plans for ten patients with right breast cancer. Plans were created for conventional 3D conformal radiation therapy (3D-CRT), intensity-modulated radiation therapy (IMRT) with and without dose optimisation to liver, and hybrid 3D-CRT/volumetric modulated arc therapy (VMAT). Dosimetric evaluation was based on dose-volume histogram (DVH) parameters. The Wilcoxon test was used to assess differences between treatment plans. Spearman's rank correlation was used to determine the correlation between the LLI and the radiation dose to the liver.

Result: IMRT plans resulted in significantly higher D_mean (p = 0.0051), V_5Gy (p = 0.0051), and V_10Gy (p = 0.0051) liver values than 3D-CRT. Compared to non-optimised IMRT [liver not included as an organ at risk (OAR)], liver parameters: V_5Gy, V_10Gy, V_20Gy (p = 0.0051) andV_30Gy (p = 0.0152) were significantly lower when the IMRT plan was optimised (IMRT_opt), with no increase in doses to other OAR. Compared to standard 3D-CRT, hybrid 3D-CRT/VMAT significantly reduced the V_30Gy (p = 0.0209), V_40Gy (p = 0.0077). The LLI was significantly correlated with liver D_mean for 3D-CRT (r_S = 0.8909, p = 0.0005) and IMRT (r_S = 0.8303, p = 0.0029), and also with liver D₂₀₀ for 3D-CRT (r_S = 0.8024, p = 0.0052) and IMRT (r_S = 0.8545, p = 0.0016).

Conclusion: The LLI provides an accurate estimation of liver exposure to radiation during right breast radiotherapy. This index, which is calculated prior to treatment planning, is highly accurate, as evidenced by the strong correlation between the LLI and the mean liver dose.

Long non-coding ribonucleic acids (lncRNAs) form a subclass of non-coding RNAs (ncRNAs), they are quite long and as their name non-coding suggests they do not have a role in protein coding. lncRNAs are vital in all the key steps of tumorigenesis, such as epithelial-mesenchymal transition, cancer stem cells formation, invasion, migration, and formation of the tumor vasculature. lncRNAs are classified into oncogenic or anti-tumor lncRNAs based on their functions. Moreover, cancer stem cells show an extremely specific pattern of expression of lncRNAs, which can be used for early detection of cancer. Similarly, their pre-treatment expression levels correlate with prognosis as they participate in key tumor biology processes like metastasis and recurrence. This chapter seeks to explore both the association between lncRNA genes and cancer and the role of lncRNAs in cancer initiation and progression. Future questions would focus on what the accepted normal ranges of lncRNA expression will be, where they are present in body fluids, which could help with non-invasive tests. But for now, one thing is clear that lncRNAs could pave the way for novel cancer therapies.

Background: The rising burden of colorectal cancer with a high prevalence of advanced stages of new-onset is reported worldwide. While applied, chemotherapy can extend patients' survival, and proper tailoring is paramount. Based on computed tomography results, the study aimed to point out potential prognostic factors of complete or partial response to the initial three months of chemotherapy in palliative colorectal (CRC) cancer.

Materials and methods: There were 133 (82 (62%) male and 51 (38%) female) consecutive patients with a median age of 70 (64-74) years who underwent palliative treatment due to the advanced stage of oncological gastrointestinal tract disease between 2022-2024 at the Clinical Oncology and Immuno-Oncology Department. After propensity score matching, 83 (52 (63%) males) colorectal cancer (CRC) patients with a median age of 69 (64-74) years were enrolled in the retrospective analysis. The chemotherapy was based on computed tomography (CT) imaging confirming the end-stage cancer disease.

Results: The multivariable model revealed chemotherapy combined with anti-epidermal growth factors receptor drug (EGFR-CTH) as the lone predictive factor for metastasis regression [odds ratio (OR): 3.59, 95% confidence interval (CI): 1.18-10.91, p = 0.024]. The receiver operating characteristic curve revealed a predictive value of EGFR-CTH with the area under the curve of 0.663, yielding a sensitivity of 58.1%, specificity of 72.5%, and precision of 0.694.

Conclusions: The EGFR-CTH protocol can be regarded as an effective palliative therapy for terminal colon and rectal cancer disease. The EGFR-CTH protocol contributes to 3.6 times higher probability of CT-proven tumor regression within three months of treatment. Large-volume studies are required to confirm the outcomes presented.

Neuroblastoma is the most common extracranial solid tumor in children, requiring multidisciplinary treatment, including radiotherapy, which is primarily applied in the high-risk group to prevent disease progression. The review highlights indications for radiotherapy, its role in multimodal treatment, and addresses aspects of radiotherapy planning, including target volume definition, prescribed radiation doses, optimal timing for radiotherapy implementation, and potential side effects. Particular attention is drawn to the lack of consensus regarding the necessity of an additional radiation dose for persistent residual disease in the primary tumor and the irradiation of metastatic sites remaining after induction therapy. To conclude, monitoring quality assurance in radiotherapy planning and delivering processes based on unified standards appears to be crucial.