Supply-side reduction policy and drug-related harm

Large-scale seizures of cocaine, heroin and amphetamine-type substances (ATS) do not result in any reduction in overdoses on these drugs or on arrests for use and possession of these drugs, according to this report. Aim: The aim of this study was to examine the question of whether seizures of heroin, cocaine or amphetamine type substances (ATS) or supplier arrests for heroin, cocaine or ATS trafficking have any effect on the ED admissions related to or arrests for use and possession of these drugs. Method: Two strategies were employed to answer the question. The first involved a time series analysis of the relationship between seizures, supplier arrests, emergency department (ED) admissions and use/possession arrests. The second involved an analysis of three specific operations identified by the NSW Crime Commission as has having had the potential to have affected the market for cocaine. Results: Over the short term (i.e. up to four months), increases in the intensity of high-level drug law enforcement (as measured by seizures and supplier arrests) directed at ATS, cocaine and heroin did not appear to have any suppression effect on ED admissions relating to ATS, cocaine and heroin, or on arrests for use and/or possession of these drugs. The three major operations dealing with cocaine listed by the NSW Crime Commission as significant (Operation Balmoral Athens, Operation Tempest and Operation Collage) did exert a suppression effect on arrests for use and possession of cocaine. Conclusions: Increases in the quantities of ATS, cocaine and heroin drugs seized by law enforcement authorities are normally a signal of increased rather than reduced supply. Very large seizures, however, may temporarily suppress consumption of these drugs. Even if drug seizures and drug supplier arrests have no short term effects on ED admissions and arrests for drug use and/or possession, they may still suppress drug consumption through risk compensation

Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images

Segmentation masks of pathological areas are useful in many medical applications, such as brain tumour and stroke management. Moreover, healthy counterfactuals of diseased images can be used to enhance radiologists' training files and to improve the interpretability of segmentation models. In this work, we present a weakly supervised method to generate a healthy version of a diseased image and then use it to obtain a pixel-wise anomaly map. To do so, we start by considering a saliency map that approximately covers the pathological areas, obtained with ACAT. Then, we propose a technique that allows to perform targeted modifications to these regions, while preserving the rest of the image. In particular, we employ a diffusion model trained on healthy samples and combine Denoising Diffusion Probabilistic Model (DDPM) and Denoising Diffusion Implicit Model (DDIM) at each step of the sampling process. DDPM is used to modify the areas affected by a lesion within the saliency map, while DDIM guarantees reconstruction of the normal anatomy outside of it. The two parts are also fused at each timestep, to guarantee the generation of a sample with a coherent appearance and a seamless transition between edited and unedited parts. We verify that when our method is applied to healthy samples, the input images are reconstructed without significant modifications. We compare our approach with alternative weakly supervised methods on the task of brain lesion segmentation, achieving the highest mean Dice and IoU scores among the models considered.</p

ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging

In some medical imaging tasks and other settings where only small parts of the image are informative for the classification task, traditional CNNs can sometimes struggle to generalise. Manually annotated Regions of Interest (ROI) are sometimes used to isolate the most informative parts of the image. However, these are expensive to collect and may vary significantly across annotators. To overcome these issues, we propose a framework that employs saliency maps to obtain soft spatial attention masks that modulate the image features at different scales. We refer to our method as Adversarial Counterfactual Attention (ACAT). ACAT increases the baseline classification accuracy of lesions in brain CT scans from 71.39% to 72.55% and of COVID-19 related findings in lung CT scans from 67.71% to 70.84% and exceeds the performance of competing methods. We investigate the best way to generate the saliency maps employed in our architecture and propose a way to obtain them from adversarially generated counterfactual images. They are able to isolate the area of interest in brain and lung CT scans without using any manual annotations. In the task of localising the lesion location out of 6 possible regions, they obtain a score of 65.05% on brain CT scans, improving the score of 61.29% obtained with the best competing method.Comment: 17 pages, 7 figure

Challenges of building medical image datasets for development of deep learning software in stroke

Despite the large amount of brain CT data generated in clinical practice, the availability of CT datasets for deep learning (DL) research is currently limited. Furthermore, the data can be insufficiently or improperly prepared for machine learning and thus lead to spurious and irreproducible analyses. This lack of access to comprehensive and diverse datasets poses a significant challenge for the development of DL algorithms. In this work, we propose a complete semi-automatic pipeline to address the challenges of preparing a clinical brain CT dataset for DL analysis and describe the process of standardising this heterogeneous dataset. Challenges include handling image sets with different orientations (axial, sagittal, coronal), different image types (to view soft tissues or bones) and dimensions, and removing redundant background. The final pipeline was able to process 5,868/10,659 (45%) CT image datasets. Reasons for rejection include non-axial data (n=1,920), bone reformats (n=687), separated skull base/vault images (n=1,226), and registration failures (n=465). Further format adjustments, including image cropping, resizing and scaling are also needed for DL processing. Of the axial scans that were not localisers, bone reformats or split brains, 5,868/6,333 (93%) were accepted, while the remaining 465 failed the registration process. Appropriate preparation of medical imaging datasets for DL is a costly and time-intensive process.Comment: 9 pages, 5 figure

Effect of IV alteplase on the ischemic brain lesion at 24-48 hours after ischemic stroke

OBJECTIVE: To determine whether alteplase alters the development of ischemic lesions on brain imaging after stroke. METHODS: The Third International Stroke Trial (IST-3) was a randomized controlled trial of IV alteplase for ischemic stroke. We assessed CT or brain MRI at baseline (pretreatment) and 24 to 48 hours posttreatment for acute lesion visibility, extent, and swelling, masked to all other data. We analyzed associations between treatment allocation, change in brain tissue appearances between baseline and follow-up imaging, and 6-month functional outcome in IST-3. We performed a meta-analysis of randomized trials of alteplase vs control with pre- and postrandomization imaging. RESULTS: Of 3,035 patients recruited in IST-3, 2,916 had baseline and follow-up brain imaging. Progression in either lesion extent or swelling independently predicted poorer 6-month outcome (adjusted odds ratio [OR] = 0.92, 95% confidence interval [CI] 0.88-0.96, p < 0.001; OR = 0.73, 95% CI 0.66-0.79, p < 0.001, respectively). Patients allocated alteplase were less likely than controls to develop increased lesion visibility at follow-up (OR = 0.77, 95% CI 0.67-0.89, p < 0.001), but there was no evidence that alteplase reduced progression of lesion extent or swelling. In meta-analysis of 6 trials including IST-3 (n = 4,757), allocation to alteplase was associated with a reduction in ischemic lesion extent on follow-up imaging (OR = 0.85, 95% CI 0.76-0.95, p = 0.004). CONCLUSION: Alteplase was associated with reduced short-term progression in lesion visibility. In meta-analysis, alteplase reduced lesion extent. These findings may indicate that alteplase improves functional outcome by reducing tissue damage. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that IV alteplase impedes the progression of ischemic brain lesions on imaging after stroke

A core outcome set for localised prostate cancer effectiveness trials

Objective: To develop a core outcome set (COS) applicable for effectiveness trials of all interventions for localised prostate cancer. Background: Many treatments exist for localised prostate cancer, although it is unclear which offers the optimal therapeutic ratio. This is confounded by inconsistencies in the selection, definition, measurement and reporting of outcomes in clinical trials. Subjects and methods: A list of 79 outcomes was derived from a systematic review of published localised prostate cancer effectiveness studies and semi-structured interviews with 15 prostate cancer patients. A two-stage consensus process involving 118 patients and 56 international healthcare professionals (HCPs) (cancer specialist nurses, urological surgeons and oncologists) was undertaken, consisting of a three-round Delphi survey followed by a face-to-face consensus panel meeting of 13 HCPs and 8 patients. Results: The final COS included 19 outcomes. Twelve apply to all interventions: death from prostate cancer, death from any cause, local disease recurrence, distant disease recurrence/metastases, disease progression, need for salvage therapy, overall quality of life, stress urinary incontinence, urinary function, bowel function, faecal incontinence, sexual function. Seven were intervention-specific: perioperative deaths (surgery), positive surgical margin (surgery), thromboembolic disease (surgery), bothersome or symptomatic urethral or anastomotic stricture (surgery), need for curative treatment (active surveillance), treatment failure (ablative therapy), and side effects of hormonal therapy (hormone therapy). The UK-centric participants may limit the generalisability to other countries, but trialists should reason why the COS would not be applicable. The default position should not be that a COS developed in one country will automatically not be applicable elsewhere. Conclusion: We have established a COS for trials of effectiveness in localised prostate cancer, applicable across all interventions which should be measured in all localised prostate cancer effectiveness trials