Dosimetric comparison of gamma knife and linear accelerator (VMAT and IMRT) plans of SBRT of Lung tumours.

This study evaluates dosimetric differences in Stereotactic Body Radiation Therapy (SBRT) for lung tumors using plans of Gamma Knife, and Volumetric Modulated Arc Therapy (VMAT), Intensity-Modulated Radiation Therapy (IMRT) plans based on Linear Accelerator, aiming to inform the reader of appropriate treatment strategy selection. Ten patients with 23 lung tumor lesions treated with SBRT at Zhongshan Hospital of Dalian University were analyzed. Plans of Gamma Knife, and VMAT, IMRT plans based on Linear Accelerator were created for each lesion, totaling 18 plans per type. Lesions were treated with 30-50 Gy in 5-10 fractions. Dosimetric parameters, including gradient index (GI), heterogeneity index (HI), conformity index (CI), and doses to the plan target volumes (PTVs), the gross tumor volumes (GTVs) and organs at risk (OARs) were compared. Plans of Gamma Knife showed superior HI and GI, higher PTV and GTV doses, and reduced doses to the ipsilateral and contralateral lungs, esophagus, spinal cord, and heart compared to VMAT and IMRT plans (p < 0.05). However, Plans of Gamma Knife required longer delivery times. When comparing VMAT and IMRT plans, VMAT plans had shorter delivery times than IMRT plans, but required more monitor units (MUs). Additionally, IMRT plans delivered a lower mean dose to the ipsilateral lung compared to VMAT plans. Gamma Knife SBRT plans achieves steeper dose falloff and minimizes radiation to normal lung tissue compared to VMAT and IMRT plans, but with longer delivery times. VMAT and IMRT plans displayed similar dose distributions for lung SBRT.

Application of postoperative adjuvant radiotherapy in limited-stage small cell lung cancer: A systematic review and meta-analysis.

BACKGROUND AND PURPOSE: One of the most important treatments for small cell lung cancer (SCLC) is radiation therapy. Currently, the criteria for administering postoperative adjuvant radiotherapy (PORT) in SCLC remain uncertain. Therefore, we conducted a meta-analysis to investigate the influence of PORT on the prognosis of limited-stage SCLC (LS-SCLC). METHODS: We conducted a comprehensive search across three databases, PubMed, Embase, and the Cochrane Library. Data analysis involved utilizing both random-effects and fixed-effects models for pooling the results. A comparative analysis was performed to assess the prognostic outcomes of patients with LS-SCLC who did and did not undergo PORT. The primary outcome assessed was overall survival (OS), while the secondary outcome was disease-free survival (DFS). RESULTS: This analysis included 11 retrospective studies comprising 7694 eligible participants. Among the entire population of LS-SCLC patients, the OS was superior in those receiving PORT than in those not receiving it (hazard ratio [HR]: 0.79, 95 % confidence interval [CI]: 0.71-0.87; P < 0.0001). In pN0 stage LS-SCLC patients, PORT was associated with a detrimental effect on OS (HR: 1.22, 95 % CI: 1.04-1.43; P = 0.01). In pN1 stage LS-SCLC patients, additionally administering PORT did not provide a significant OS advantage as compared to not administering it (HR: 0.82, 95 % CI: 0.60-1.12; P = 0.21). In pN2 stage LS-SCLC patients, those receiving PORT demonstrated a significant improvement in OS (HR: 0.59; 95 % CI: 0.50-0.70; P < 0.0001) as compared to those not receiving it. Regarding DFS in LS-SCLC patients, the difference in the protective effect with and without the administration of PORT was less pronounced (HR: 0.76, 95 % CI: 0.58-1.00; P = 0.053). CONCLUSIONS: With respect to OS, PORT is not advisable in patients with pN0 or pN1 stage LS-SCLC but is highly recommended in pN2 stage LS-SCLC. Further research is warranted to confirm these findings.

Radiomics in Nasopharyngeal Carcinoma.

Nasopharyngeal carcinoma (NPC) is one of the most common head and neck malignancies, and the primary treatment methods are radiotherapy and chemotherapy. Radiotherapy alone, concurrent chemoradiotherapy, and induction chemotherapy combined with concurrent chemoradiotherapy can be used according to different grades. Treatment options and prognoses vary greatly depending on the grade of disease in the patients. Accurate grading and risk assessment are required. Recently, radiomics has combined a large amount of invisible high-dimensional information extracted from computed tomography, magnetic resonance imaging, or positron emission tomography with powerful computing capabilities of machine-learning algorithms, providing the possibility to achieve an accurate diagnosis and individualized treatment for cancer patients. As an effective tumor biomarker of NPC, the radiomic signature has been widely used in grading, differential diagnosis, prediction of prognosis, evaluation of treatment response, and early identification of therapeutic complications. The process of radiomic research includes image segmentation, feature extraction, feature selection, model establishment, and evaluation. Many open-source or commercial tools can be used to achieve these procedures. The development of machine-learning algorithms provides more possibilities for radiomics research. This review aimed to summarize the application of radiomics in NPC and introduce the basic process of radiomics research.

The diagnostic performance of the Gynecologic Imaging Reporting and Data System (GI-RADS) in adnexal masses.

BACKGROUND: Adnexal masses, mostly benign, are common in the female genital system. However, adnexal masses are the leading cause of death among women with gynecologic cancer. Ultrasound is a common imaging method for diagnosing adnexal masses. Gynecologic Imaging Reporting and Data System (GI-RADS) is a useful diagnostic tool based on objective ultrasound features to diagnose the malignancy of the female genital system. Therefore, we conducted a meta-analysis to evaluate the ability of GI-RADS to differentiate adnexal masses. METHODS: Published articles were searched in PubMed, Medline, and Embase from 1990 to February 2020. Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio, and area under the curve (AUC) were estimated via the extracted data from the selected studies. RESULTS: Ten studies and 2,474 patients were included in this meta-analysis. The pooled sensitivity of selected studies was 0.95 [95% confidence intervals (CI): 0.94-0.97], and the pooled specificity was 0.86 (95% CI: 0.84-0.88). The pooled NLR and PLR were 0.06 (95% CI: 0.04-0.10), and 8.30 (95% CI: 4.93-13.97), respectively. Moreover, the pooled diagnostic odds ratio for GI-RADS was 174.59 (95% CI: 76.70-397.42), and the AUC was 0.9806. CONCLUSIONS: This research indicates that GI-RADS might be a valuable tool to distinguish malignancies from adnexal masses.