Citations

Abstract Background and study aims Endoscopic ultrasound (EUS)-guided fine-needle aspiration (EUS-FNA) has limitations of inadequate sampling and false-negative results for malignancy. It has been performed using conventional smear (CS) cytology with rapid on-site evaluation (ROSE) with reasonable diagnostic accuracy. An alternative to ROSE is liquid-based cytology (LBC). Commonly used LBC techniques include precipitation-based (SurePath™) and filtration-based (ThinPrep®, CellPrep®). Data regarding the diagnostic efficacy of LBC compared with CS are limited. Methods Multiple databases were searched through March 2020 to identify studies reporting diagnostic yield of EUS-guided CS and LBC in pancreatic lesions. Pooled diagnostic odds and rates of performance for the cytologic diagnoses of benign, suspicious, and malignant lesions were calculated. Diagnostic efficacy was evaluated by pooled rates of accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Results Nine studies with a total of 1308 patients were included in our final analysis. Pooled diagnostic odds of CS cytology were 1.69 (CI 1.02–2.79) and 0.39 (CI 0.19–0.8) for malignant lesions when compared to filtration-based and precipitation-based LBC techniques, respectively. For CS, precipitation-based and filtration-based LBC, pooled diagnostic accuracy was 79.7 %, 85.2 %, 77.3 %, sensitivity was 79.2 %, 83.6 %, 68.3 %, and specificity was 99.4 %, 99.5 %, 99.5 %, respectively. Conclusions The precipitation-based LBC technique (SurePath™) had superior diagnostic odds for malignant pancreatic lesions compared with CS cytology in the absence of ROSE. It showed superior accuracy and sensitivity, but comparable specificity and PPV. Diagnostic odds of CS cytology in the absence of ROSE were superior to the filtration-based LBC technique (ThinPrep®, Cellprep®) for diagnosing malignant pancreatic lesions.

Objective: To evaluate adverse events and feasibility of performing 1.5-T MRI in patients with cochlear implants (CI) and auditory brainstem implants (ABI). Setting: Single tertiary academic referral center. Patients: CI and ABI recipients undergoing 1.5-T MRI without internal magnet removal. Intervention(s): MRI after tight headwrap application. Main Outcome Measures: Adverse events, patient tolerance. Results: A total of 131 MR studies in 79 patients were performed, with a total of 157 study ears. Sixty-one patients (77%) had unilateral devices. Four patients (5%) underwent MRI with ABI magnets in place. Sixteen patients (20%) had MRI-compatible devices that did not require a head wrap. There were no instances of device stimulation, device malfunction, or excessive heating of the receiver-stimulator package. Magnet tilt requiring manual repositioning occurred during seven studies (4.5%) and magnet displacement requiring operative intervention occurred during seven studies (4.5%). Significant pain where imaging had to be discontinued occurred during three episodes (2%). No adverse events were noted among patients who underwent MRI with an MRI-compatible magnet. Conclusions: MRI with CI or ABI magnets in place is associated with a low prevalence of adverse events when performed in a controlled setting. Many partial magnet displacements can be corrected with firm manual pressure. Devices with magnets that align with the field within their housing were not associated with any adverse events and do not require immobilization of the magnet during the scan. These may be valuable in patients with known or anticipated need for MRI.

Objective The diagnosis of autoimmune pancreatitis (AIP) is challenging. Sonographic and cross-sectional imaging findings of AIP closely mimic pancreatic ductal adenocarcinoma (PDAC) and techniques for tissue sampling of AIP are suboptimal. These limitations often result in delayed or failed diagnosis, which negatively impact patient management and outcomes. This study aimed to create an endoscopic ultrasound (EUS)-based convolutional neural network (CNN) model trained to differentiate AIP from PDAC, chronic pancreatitis (CP) and normal pancreas (NP), with sufficient performance to analyse EUS video in real time. Design A database of still image and video data obtained from EUS examinations of cases of AIP, PDAC, CP and NP was used to develop a CNN. Occlusion heatmap analysis was used to identify sonographic features the CNN valued when differentiating AIP from PDAC. Results From 583 patients (146 AIP, 292 PDAC, 72 CP and 73 NP), a total of 1 174 461 unique EUS images were extracted. For video data, the CNN processed 955 EUS frames per second and was: 99% sensitive, 98% specific for distinguishing AIP from NP; 94% sensitive, 71% specific for distinguishing AIP from CP; 90% sensitive, 93% specific for distinguishing AIP from PDAC; and 90% sensitive, 85% specific for distinguishing AIP from all studied conditions (ie, PDAC, CP and NP). Conclusion The developed EUS-CNN model accurately differentiated AIP from PDAC and benign pancreatic conditions, thereby offering the capability of earlier and more accurate diagnosis. Use of this model offers the potential for more timely and appropriate patient care and improved outcome.

AbstractCancer treatment has been transformed by checkpoint blockade therapies, with the highest anti-tumor activity of anti-programmed death 1 (PD-1) antibody therapy seen in Hodgkin lymphoma. Disappointingly, response rates have been low in the non-Hodgkin lymphomas, with no activity seen in relapsed/refractory chronic lymphocytic leukemia (CLL) with PD-1 blockade. Thus, identifying more powerful combination therapy is required for these patients. Here, we preclinically demonstrate enhanced anti-CLL activity following combinational therapy with anti-PD-1 or anti-PD-1 ligand (PD-L1) and avadomide, a cereblon E3 ligase modulator (CELMoD). Avadomide induced type I and II interferon (IFN) signaling in patient T cells, triggering a feedforward cascade of reinvigorated T-cell responses. Immune modeling assays demonstrated that avadomide stimulated T-cell activation, chemokine expression, motility and lytic synapses with CLL cells, as well as IFN-inducible feedback inhibition through upregulation of PD-L1. Patient-derived xenograft tumors treated with avadomide were converted to CD8+ T cell-inflamed tumor microenvironments that responded to anti-PD-L1/PD-1-based combination therapy. Notably, clinical analyses showed increased PD-L1 expression on T cells, as well as intratumoral expression of chemokine signaling genes in B-cell malignancy patients receiving avadomide-based therapy. These data illustrate the importance of overcoming a low inflammatory T-cell state to successfully sensitize CLL to checkpoint blockade-based combination therapy.

The field of cardiac electrophysiology has been on the cutting edge of advanced digital technologies for many years. More recently, medical device development through traditional clinical trials has been supplemented by direct to consumer products with advancement of wearables and health care apps. The rapid growth of innovation along with the mega-data generated has created challenges and opportunities. This review summarizes the regulatory landscape, applications to clinical practice, opportunities for virtual clinical trials, the use of artificial intelligence to streamline and interpret data, and integration into the electronic medical records and medical practice. Preparation of the new generation of physicians, guidance and promotion by professional societies, and advancement of research in the interpretation and application of big data and the impact of digital technologies on health outcomes will help to advance the adoption and the future of digital health care.

Chronic myeloid leukemia (CML) is defined by the presence of Philadelphia chromosome (Ph) which results from a reciprocal translocation between chromosomes 9 and 22 [t(9;22] that gives rise to a BCR-ABL1 fusion gene. CML occurs in 3 different phases (chronic, accelerated, and blast phase) and is usually diagnosed in the chronic phase. Tyrosine kinase inhibitor therapy is a highly effective first-line treatment option for all patients with newly diagnosed chronic phase CML. This manuscript discusses the recommendations outlined in the NCCN Guidelines for the diagnosis and management of patients with chronic phase CML.