Humans and machines: Moving towards a more symbiotic approach to learning clinical reasoning

Abstract

Artificial intelligence is a growing phenomenon that is driving major changes to how we deliver healthcare. One of its most significant and challenging contributions is likely to be in diagnosis. Artificial intelligence is challenging the physician’s exclusive role in diagnosis and in some areas, its diagnostic accuracy exceeds that of humans. We argue that we urgently need to consider how we will incorporate AI into our teaching of clinical reasoning in the undergraduate curriculum; students need to successfully navigate the benefits and potential issues of new and developing approaches to AI in clinical diagnosis. We offer a pedagogical framework for this challenging change to our curriculum.     

Detecting white matter alterations in multiple sclerosis using advanced diffusion magnetic resonance imaging

Multiple sclerosis is a neurodegenerative and inflammatory disease, a hallmark of which is demyelinating lesions in the white matter. We hypothesized that alterations in white matter microstructures can be non-invasively characterized by advanced diffusion magnetic resonance imaging. Seven diffusion metrics were extracted from hybrid diffusion imaging acquisitions via classic diffusion tensor imaging, neurite orientation dispersion and density imaging, and q-space imaging. We investigated the sensitivity of the diffusion metrics in 36 sets of regions of interest in the brain white matter of six female patients(age 52.8 ± 4.3 years) with multiple sclerosis. Each region of interest set included a conventional T2-defined lesion, a matched perilesion area, and normal-appearing white matter. Six patients with multiple sclerosis(n = 5) or clinically isolated syndrome(n = 1) at a mild to moderate disability level were recruited. The patients exhibited microstructural alterations from normal-appearing white matter transitioning to perilesion areas and lesions, consistent with decreased tissue restriction, decreased axonal density, and increased classic diffusion tensor imaging diffusivity. The findings suggest that diffusion compartment modeling and q-spa ce analysis appeared to be sensitive for detecting subtle microstructural alterations between perilesion areas and normal-appearing white matter.     

Immunotherapy for urothelial carcinoma: Metastatic disease and beyond

For advanced and metastatic urothelial carcinomas (UCs), platinum (preferably cisplatin)‐based chemotherapy has been the standard treatment for many years. However, many patients are ineligible for cisplatin‐based chemotherapy because of poor performance status and/or other age‐related conditions. At the other end of the spectrum, patients with localized non‐muscle–invasive bladder cancer who are unresponsive to intravesical Bacillus Calmette‐Guérin (BCG) treatment often face radical cystectomy as the only option. In recent years, the application of immunotherapy in the form of immune‐checkpoint inhibitors has provided viable alternatives in the second‐line postplatinum and first‐line cisplatin‐ineligible settings. Recent and ongoing clinical trials are also assessing the safety and efficacy of immunotherapy for neoadjuvant and adjuvant uses before/after cystectomy, for BCG‐unresponsive cases, and for combination treatments that include the newer indoleamine 2,3‐dioxygenase‐1 inhibitors and/or BCG. This review summarizes recent developments in immunotherapy for UCs.