Predictive and prognostic value of tumor volume and its changes during radical radiotherapy of stage III non-small cell lung cancer : A systematic review.

PURPOSE: Lung cancer remains the leading cause of cancer-related mortality worldwide. Stage III non-small cell lung cancer (NSCLC) includes heterogeneous presentation of the disease including lymph node involvement and large tumour volumes with infiltration of the mediastinum, heart or spine. In the treatment of stage III NSCLC an interdisciplinary approach including radiotherapy is considered standard of care with acceptable toxicity and improved clinical outcome concerning local control. Furthermore, gross tumour volume (GTV) changes during definitive radiotherapy would allow for adaptive replanning which offers normal tissue sparing and dose escalation. METHODS: A literature review was conducted to describe the predictive value of GTV changes during definitive radiotherapy especially focussing on overall survival. The literature search was conducted in a two-step review process using PubMed®/Medline® with the key words "stage III non-small cell lung cancer" and "radiotherapy" and "tumour volume" and "prognostic factors". RESULTS: After final consideration 17, 14 and 9 studies with a total of 2516, 784 and 639 patients on predictive impact of GTV, GTV changes and its impact on overall survival, respectively, for definitive radiotherapy for stage III NSCLC were included in this review. Initial GTV is an important prognostic factor for overall survival in several studies, but the time of evaluation and the value of histology need to be further investigated. GTV changes during RT differ widely, optimal timing for re-evaluation of GTV and their predictive value for prognosis needs to be clarified. The prognostic value of GTV changes is unclear due to varying study qualities, re-evaluation time and conflicting results. CONCLUSION: The main findings were that the clinical impact of GTV changes during definitive radiotherapy is still unclear due to heterogeneous study designs with varying quality. Several potential confounding variables were found and need to be considered for future studies to evaluate GTV changes during definitive radiotherapy with respect to treatment outcome.

A 3D lung lesion variational autoencoder.

In this study, we develop a 3D beta variational autoencoder (beta-VAE) to advance lung cancer imaging analysis, countering the constraints of conventional radiomics methods. The autoencoder extracts information from public lung computed tomography (CT) datasets without additional labels. It reconstructs 3D lung nodule images with high quality (structural similarity: 0.774, peak signal-to-noise ratio: 26.1, and mean-squared error: 0.0008). The model effectively encodes lesion sizes in its latent embeddings, with a significant correlation with lesion size found after applying uniform manifold approximation and projection (UMAP) for dimensionality reduction. Additionally, the beta-VAE can synthesize new lesions of varying sizes by manipulating the latent features. The model can predict multiple clinical endpoints, including pathological N stage or KRAS mutation status, on the Stanford radiogenomics lung cancer dataset. Comparisons with other methods show that the beta-VAE performs equally well in these tasks, suggesting its potential as a pretrained model for predicting patient outcomes in medical imaging.

Disparities in air pollution attributable mortality in the US population by race/ethnicity and sociodemographic factors.

There are large differences in premature mortality in the USA by race/ethnicity, education, rurality and social vulnerability index groups. Using existing concentration-response functions, published particulate matter (PM2.5) air pollution estimates, population estimates at the census tract level and county-level mortality data from the US National Vital Statistics System, we estimated the degree to which these mortality discrepancies can be attributed to differences in exposure and susceptibility to PM2.5. We show that differences in PM2.5-attributable mortality were consistently more pronounced by race/ethnicity than by education, rurality or social vulnerability index, with the Black American population having the highest proportion of deaths attributable to PM2.5 in all years from 1990 to 2016. Our model estimates that over half of the difference in age-adjusted all-cause mortality between the Black American and non-Hispanic white population was attributable to PM2.5 in the years 2000 to 2011. This difference decreased only marginally between 2000 and 2015, from 53.4% (95% confidence interval 51.2-55.9%) to 49.9% (95% confidence interval 47.8-52.2%), respectively. Our findings underscore the need for targeted air quality interventions to address environmental health disparities.

Sociodemographic and geographic variation in mortality attributable to air pollution in the United States.

There are large differences in premature mortality in the USA by racial/ethnic, education, rurality, and social vulnerability index groups. Using existing concentration-response functions, particulate matter (PM2.5) air pollution, population estimates at the tract level, and county-level mortality data, we estimated the degree to which these mortality discrepancies can be attributed to differences in exposure and susceptibility to PM2.5. We show that differences in mortality attributable to PM2.5 were consistently more pronounced between racial/ethnic groups than by education, rurality, or social vulnerability index, with the Black American population having by far the highest proportion of deaths attributable to PM2.5 in all years from 1990 to 2016. Over half of the difference in age-adjusted all-cause mortality between the Black American and non-Hispanic White population was attributable to PM2.5 in the years 2000 to 2011.

A deep-learning algorithm to classify skin lesions from mpox virus infection.

Undetected infection and delayed isolation of infected individuals are key factors driving the monkeypox virus (now termed mpox virus or MPXV) outbreak. To enable earlier detection of MPXV infection, we developed an image-based deep convolutional neural network (named MPXV-CNN) for the identification of the characteristic skin lesions caused by MPXV. We assembled a dataset of 139,198 skin lesion images, split into training/validation and testing cohorts, comprising non-MPXV images (n = 138,522) from eight dermatological repositories and MPXV images (n = 676) from the scientific literature, news articles, social media and a prospective cohort of the Stanford University Medical Center (n = 63 images from 12 patients, all male). In the validation and testing cohorts, the sensitivity of the MPXV-CNN was 0.83 and 0.91, the specificity was 0.965 and 0.898 and the area under the curve was 0.967 and 0.966, respectively. In the prospective cohort, the sensitivity was 0.89. The classification performance of the MPXV-CNN was robust across various skin tones and body regions. To facilitate the usage of the algorithm, we developed a web-based app by which the MPXV-CNN can be accessed for patient guidance. The capability of the MPXV-CNN for identifying MPXV lesions has the potential to aid in MPXV outbreak mitigation.

Role of Dose Intensification for Salvage Radiation Therapy after Radical Prostatectomy.

For primary radiation therapy (RT) of prostate cancer, dose intensification is established as standard of care. Less is known on the role of dose intensification in the postprostatectomy setting for salvage RT. Thus, we aimed to identify and summarize the existing literature. In retrospective analyses, dose-intensified salvage RT showed a superior biochemical control compared to standard dose salvage radiation with favorable acute and late gastrointestinal and genitourinary toxicity rates, especially when modern radiation techniques such as intensity modulated RT were applied. We identified one randomized phase III trial addressing the potential benefits of dose-intensified salvage RT (SAKK 09/10). Recently, acute gastrointestinal and genitourinary toxicities and early quality of life data of this trial were reported, and no significant difference in acute toxicities between both treatment arms were found; however, a significant worsening of genitourinary quality of life was noted in the dose-intensified treatment arm. Whereas dose-intensified salvage RT appears to be feasible and well tolerated, the improved biochemical control rates using dose intensified RT as suggested by retrospective analyses have yet to be validated by prospective trials.