Stereotactic body radiation therapy for the treatment of early-stage minimally invasive adenocarcinoma or adenocarcnioma in situ (formerly bronchioloalveolar carcinoma): A patterns of failure analysis

INTRODUCTION: Ongoing prospective trials exploring stereotactic body radiation therapy (SBRT) for early stage non-small cell lung cancer (NSCLC) often exclude minimally invasive adenocarcinoma or adenocarcnioma in situ, formerly bronchioloalveolar carcinoma (BAC), due to concerns for accurate target delineation on CT. We performed a patterns of failure analysis to compare outcomes between BAC and other NSCLC subtypes. METHODS: One hundred twenty patients with early stage NSCLC were treated with SBRT from 2004–2009. Pathologic confirmation of NSCLC was obtained in 97 patients. Radiotherapy was delivered according to RTOG guidelines. The log-rank test was used to compare outcomes between BAC and other NSCLC. RESULTS: Median follow-up was 29 months. The median SBRT dose was 5400 cGy. Thirteen patients had radiographically diagnosed BAC and five patients had biopsy confirmed BAC, of which two had both. The three-year local control was 100% for biopsy-proven or radiographically diagnosed BAC (n = 18) and 86% for all other NSCLC subtypes (n = 102) (p = 0.13). Likewise, no significant difference was detected between BAC and other NSCLC for 3-year regional failure (12% vs. 20%, p = 0.45), progression-free survival (57.6% vs. 53.5%, p = 0.84) or overall survival (35% vs. 47%, p = 0.66). There was a trend towards lower three-year rates of freedom from distant failure in patients with any diagnosis of BAC compared to those without (26% vs. 38%, p = 0.053). CONCLUSIONS: Compared to other NSCLC subtypes, BAC appears to have similar patterns of failure and survival after treatment with SBRT, however there may be an increased risk of distant metastases with BAC. RTOG guideline-based target delineation provides encouraging local control rates for patients with BAC

The Impact of Railway Stations on Residential and Commercial Property Value: A Meta-analysis

Railway stations function as nodes in transport networks and places in an urban environment. They have accessibility and environmental impacts, which contribute to property value. The literature on the effects of railway stations on property value is mixed in its finding in respect to the impact magnitude and direction, ranging from a negative to an insignificant or a positive impact. This paper attempts to explain the variation in the findings by meta-analytical procedures. Generally the variations are attributed to the nature of data, particular spatial characteristics, temporal effects and methodology. Railway station proximity is addressed from two spatial considerations: a local station effect measuring the effect for properties with in 1/4 mile range and a global station effect measuring the effect of coming 250 m closer to the station. We find that the effect of railway stations on commercial property value mainly takes place at short distances. Commercial properties within 1/4 mile rang are 12.2% more expensive than residential properties. Where the price gap between the railway station zone and the rest is about 4.2% for the average residence, it is about 16.4% for the average commercial property. At longer distances the effect on residential property values dominate. We find that for every 250 m a residence is located closer to a station its price is 2.3% higher than commercial properties. Commuter railway stations have a consistently higher positive impact on the property value compared to light and heavy railway/Metro stations. The inclusion of other accessibility variables (such as highways) in the models reduces the level of reported railway station impact. © 2007 Springer Science+Business Media, LLC

Law in social work education: reviewing the evidence on teaching, learning and assessment

This paper presents the findings from a systemic review of knowledge relating to current practice in the teaching, learning and assessment of law in social work education. The research comprised an internationally conducted systematic review of the literature, together with a survey of current education practice in the four countries of the UK. Two consultation events sought the views of a range of stakeholders, including the perspectives of service users and carers. Set in the context of debates about the relationship between law and social work practice, this paper identifies the common themes emerging from the review and offers an analysis of key findings, together with priorities for future directions in education practice

Validation of clinical acceptability of deep-learning-based automated segmentation of organs-at-risk for head-and-neck radiotherapy treatment planning

IntroductionOrgan-at-risk segmentation for head and neck cancer radiation therapy is a complex and time-consuming process (requiring up to 42 individual structure, and may delay start of treatment or even limit access to function-preserving care. Feasibility of using a deep learning (DL) based autosegmentation model to reduce contouring time without compromising contour accuracy is assessed through a blinded randomized trial of radiation oncologists (ROs) using retrospective, de-identified patient data.MethodsTwo head and neck expert ROs used dedicated time to create gold standard (GS) contours on computed tomography (CT) images. 445 CTs were used to train a custom 3D U-Net DL model covering 42 organs-at-risk, with an additional 20 CTs were held out for the randomized trial. For each held-out patient dataset, one of the eight participant ROs was randomly allocated to review and revise the contours produced by the DL model, while another reviewed contours produced by a medical dosimetry assistant (MDA), both blinded to their origin. Time required for MDAs and ROs to contour was recorded, and the unrevised DL contours, as well as the RO-revised contours by the MDAs and DL model were compared to the GS for that patient.ResultsMean time for initial MDA contouring was 2.3 hours (range 1.6-3.8 hours) and RO-revision took 1.1 hours (range, 0.4-4.4 hours), compared to 0.7 hours (range 0.1-2.0 hours) for the RO-revisions to DL contours. Total time reduced by 76% (95%-Confidence Interval: 65%-88%) and RO-revision time reduced by 35% (95%-CI,-39%-91%). All geometric and dosimetric metrics computed, agreement with GS was equivalent or significantly greater (p<0.05) for RO-revised DL contours compared to the RO-revised MDA contours, including volumetric Dice similarity coefficient (VDSC), surface DSC, added path length, and the 95%-Hausdorff distance. 32 OARs (76%) had mean VDSC greater than 0.8 for the RO-revised DL contours, compared to 20 (48%) for RO-revised MDA contours, and 34 (81%) for the unrevised DL OARs.ConclusionDL autosegmentation demonstrated significant time-savings for organ-at-risk contouring while improving agreement with the institutional GS, indicating comparable accuracy of DL model. Integration into the clinical practice with a prospective evaluation is currently underway

Interactions between canopy structure and herbaceous biomass along environmental gradients in moist forest and dry miombo woodland of Tanzania

We have limited understanding of how tropical canopy foliage varies along environmental gradients, and how this may in turn affect forest processes and functions. Here, we analyse the relationships between canopy leaf area index (LAI) and above ground herbaceous biomass (AGBH) along environmental gradients in a moist forest and miombo woodland in Tanzania. We recorded canopy structure and herbaceous biomass in 100 permanent vegetation plots (20 m × 40 m), stratified by elevation. We quantified tree species richness, evenness, Shannon diversity and predominant height as measures of structural variability, and disturbance (tree stumps), soil nutrients and elevation as indicators of environmental variability. Moist forest and miombo woodland differed substantially with respect to nearly all variables tested. Both structural and environmental variables were found to affect LAI and AGBH, the latter being additionally dependent on LAI in moist forest but not in miombo, where other factors are limiting. Combining structural and environmental predictors yielded the most powerful models. In moist forest, they explained 76% and 25% of deviance in LAI and AGBH, respectively. In miombo woodland, they explained 82% and 45% of deviance in LAI and AGBH. In moist forest, LAI increased non-linearly with predominant height and linearly with tree richness, and decreased with soil nitrogen except under high disturbance. Miombo woodland LAI increased linearly with stem density, soil phosphorous and nitrogen, and decreased linearly with tree species evenness. AGBH in moist forest decreased with LAI at lower elevations whilst increasing slightly at higher elevations. AGBH in miombo woodland increased linearly with soil nitrogen and soil pH. Overall, moist forest plots had denser canopies and lower AGBH compared with miombo plots. Further field studies are encouraged, to disentangle the direct influence of LAI on AGBH from complex interrelationships between stand structure, environmental gradients and disturbance in African forests and woodlands

Long-Term Vegetation Change in Central Africa: The Need for an Integrated Management Framework for Forests and Savannas

peer reviewedTropical forests and savannas are the main biomes in sub-Saharan Africa, covering most of the continent. Collectively they offer important habitat for biodiversity and provide multiple ecosystem services. Considering their global importance and the multiple sustainability challenges they face in the era of the Anthropocene, this chapter undertakes a comprehensive analysis of the past, present, and future vegetation patterns in central African forests and savannas. Past changes in climate, vegetation, land use, and human activity have affected the distribution of forests and savannas across central Africa. Currently, forests form a continuous block across the wet and moist areas of central Africa, and are characterized by high tree cover (>90% tree cover). Savannas and woodlands have lower tree cover (<40% tree cover), are found in drier sites in the north and south of the region, and are maintained by frequent fires. Recent tree cover loss (2000–2015) has been more important for forests than for savannas, which, however, reportedly experienced woody encroachment. Future cropland expansion is expected to have a strong impact on savannas, while the extent of climatic impacts depends on the actual scenario. We finally identify some of the policy implications for restoring ecosystems, expanding protected areas, and designing sustainable ecosystem management approaches in the region