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1. Sharrief A. Diagnosis and Management of Cerebral Small Vessel Disease. Continuum (Minneap Minn). 2023;29(2):501-518. doi:10.1212/CON.0000000000001232

Cerebral small vessel disease (CSVD) is one of the most common clinical conditions that a neuroimager will encounter. CSVD is associated with an increased risk of clinical ischemic and hemorrhagic stroke, silent infarcts, and cognitive decline and dementia. It has well-defined radiographic features and various clinical presentations. Despite its increasing prevalence with the aging population, few specific therapies exist to decrease its progression.

CSVD contributes to significant morbidity and mortality through its impact on stroke risk, cognitive decline, and dementia. Small vessel disease accounts for approximately 22% of ischemic stroke, and small vessel disease burden increases the risk of recurrent stroke following ischemic or hemorrhagic stroke. CSVD manifests as “silent” brain infarcts as well as clinically recognized small vessel ischemic strokes. Silent brain infarcts, which are also included in the classification of “covert cerebral small vessel disease,” are more common than acute ischemic stroke, with an estimated prevalence of 10% to 20% in adults. These lesions are often found incidentally but are associated with an increased risk of stroke and death, as well as other neurologic, neuropsychiatric, and cognitive symptoms, which are poorly recognized in clinical practice. CSVD accounts for most of the intracerebral hemorrhage (ICH) through arteriosclerosis (sometimes referred to as hypertensive arteriosclerosis) and cerebral amyloid angiopathy (CAA).

Age is the most common nonmodifiable risk factor for CSVD, and the aging of the population has led to the increased global prevalence of CSVD. Almost 100% of adults aged 90 and older have evidence of CSVD, with 36% of adults aged 80 to 90 demonstrating evidence of cerebral microbleeds.

Several modifiable clinical risk factors are associated with the development of CSVD. These include hypertension, obstructive sleep apnea, diabetes mellitus, hyperlipidemia, and tobacco use. Chronic kidney disease is associated with increased presence of cerebral microbleeds, white matter hyperintensities, and silent brain infarctions.

In 2013, a multidisciplinary group from the Centers for Standards in Neurodegeneration published a position paper describing the need for consistent terminology and setting the standard for describing CSVD. They described six radiographic phenotypes of CSVD: (1) recent small subcortical infarct, (2) white matter hyperintensity, (3) lacune of presumed vascular origin, (4) widened perivascular spaces, (5) cerebral microbleed, and (6) brain atrophy.

4 tables and 5 figures with this, including MR

2. Perneczky R, Jessen F, Grimmer T, et al. Anti-amyloid antibody therapies in Alzheimer’s disease. Brain. 2023;146(3):842-849. doi:10.1093/brain/awad005

New disease-modifying therapies (DMT) promise a step change in dementia care and prevention. At present, monoclonal antibodies (mAbs) targeting amyloid-β (Aβ) are the most prevalent drugs in phase III trials, with robust evidence on their engagement of the biological target in humans. However, clinical efficacy is less consistent across different agents, and the overall trial evidence so far indicated that successful Aβ clearance in early Alzheimer’s disease has at best very small effects on cognitive decline. The authors present this update which aims to elucidate the key reasons for those inconsistencies. To showcase the challenges with developing DMTs for Alzheimer’s disease, they start with an analysis of the three most recent anti-Aβ mAbs with completed phase III trials. They provide reasons why results of meta-analyses of the previous trials are less relevant in the appreciation of the new lecanemab data, including differences in drug dose, cohort characteristics, mAb specificity and adverse events.

Aducanumab, a human IgG1 mAb targeting amino acids of the Aβ peptide, is specific for Aβ plaques and on 7 June 2021, the US Food and Drug Administration (FDA) approved aducanumab for the treatment of Alzheimer’s disease.  Significant side effects also occurred during treatment with aducanumab in the phase III trials. Of particular importance were amyloid-related imaging abnormalities with edema (ARIA-E) and/or microhemorrhages (ARIA-H) on brain MRI scans, with an incidence of 35% and 36% in the two phase III studies, and 25% of affected participants experiencing symptoms, particularly in carriers of the APOE ϵ4 allele.

While the primary aim of the phase III studies was to provide evidence for the clinical efficacy of aducanumab, the approval now granted is based on proof of meeting the surrogate biomarker end point of reducing Aβ plaques on PET. This accelerated approval route chosen by the FDA for aducanumab is intended for drugs targeting serious diseases, expected to have a significant added value over the available therapy, even if there is residual uncertainty about the ultimate clinical benefit. There must be substantial evidence for efficacy on a surrogate end point reflecting the underlying disease pathology, with no requirement for demonstration of any clinical benefit. While biomarker evidence was sufficient for approval by FDA, the European Medicines Agency was unlikely to follow the US decision, and the developer therefore withdrew the marketing authorization application; approval for the marketing of aducanumab will not be granted in the EU.

On September 27 2022, results were announced from CLARITY AD, a large worldwide clinical trial with 1795 participants with early Alzheimer’s disease, showing that lecanemab had achieved its primary end point, a statistically significant slowdown of clinical disease progression on the CDR-SB. In this phase III trial the treatment group received 10 mg/kg lecanemab intravenously every 2 weeks, with participants receiving either placebo or lecanemab in a 1:1 ratio.

Over the 18-month study period, both groups deteriorated on the Clinical Dementia Rating Scale-sum of the boxes (CDR-SB) and on other secondary clinical end points, as expected in Alzheimer’s disease. However, clinical deterioration in the lecanemab group was 27% slower compared to placebo after 18 months, resulting in a statistically highly significant difference.

1 table, 3 figures, no imaging

3. Haug CJ, Drazen JM. Artificial Intelligence and Machine Learning in Clinical Medicine, 2023. Drazen JM, Kohane IS, Leong TY, eds. New England Journal of Medicine. 2023;388(13):1201-1208. doi:10.1056/NEJMra2302038

What are the standards to which AI and machine learning–based interventional research should be held, if an app is going to be accepted as the standard that will shape, reform, and improve clinical practice? That research has three components. First, the research must be structured to answer a clinically meaningful question in a way that can influence the behavior of the health professional and lead to an improvement in outcomes for a patient. Second, the intervention must be definable, scalable, and applicable to the problem at hand. It must not be influenced by factors outside the domain of the problem and must yield outcomes that can be applied to similar clinical problems across a wide range of populations and disease prevalence. Can AI and machine learning–driven care meet these standards — ones that we demand from a novel therapeutic intervention or laboratory-based diagnostic test — or do we need to have a unique set of standards for this type of intervention? Third, when the results of the research are applied in such a way as to influence practice, the outcome must be beneficial for all patients under consideration, not just those who are like the ones with characteristics and findings on which the algorithm was trained. This raises the question of whether such algorithms should include consideration of public health (i.e., the use of scarce resources) when diagnostic or treatment recommendations are being made and the extent to which such considerations are part of the decision-making process of the algorithm. Such ethical considerations have engaged health professionals and the public for centuries.

3 figures

4. Sarraj A, Hassan AE, Abraham MG, et al. Trial of Endovascular Thrombectomy for Large Ischemic Strokes. New England Journal of Medicine. 2023;388(14):1259-1271. doi:10.1056/NEJMoa2214403

The authors performed a prospective, randomized, open-label, adaptive, international trial involving patients with stroke due to occlusion of the internal carotid artery or the first segment of the middle cerebral artery to assess endovascular thrombectomy within 24 hours after onset. Patients had a large ischemic-core volume, defined as an ASPECT score of 3 to 5 (range, 0 to 10, with lower scores indicating larger infarction) or a core volume of at least 50 ml on computed tomography perfusion or diffusion-weighted magnetic resonance imaging. Patients were assigned in a 1:1 ratio to endovascular thrombectomy plus medical care or to medical care alone. The primary outcome was the modified Rankin scale score at 90 days (range, 0 to 6, with higher scores indicating greater disability). Functional independence was a secondary outcome.

The trial was stopped early for efficacy; 178 patients had been assigned to the thrombectomy group and 174 to the medical-care group. The generalized odds ratio for a shift in the distribution of modified Rankin scale scores toward better outcomes in favor of thrombectomy was 1.51.  A total