A case of purulent pneumococcal pericarditis

Background

Purulent bacterial pericarditis is a rare and potentially fatal disease. The course may be fulminant, and the presentation may pose a diagnostic challenge.

Optimal combination of antiangiogenic therapy for hepatocellular carcinoma

The success of sorafenib in prolonging survival of patients with hepatocellular carcinoma (HCC) makes therapeutic inhibition of angiogenesis a component of treatment for HCC. To enhance therapeutic efficacy, overcome drug resistance and reduce toxicity, combination of antiangiogenic agents with chemotherapy, radiotherapy or other targeted agents were evaluated. Nevertheless, the use of antiangiogenic therapy remains suboptimal regarding dosage, schedule and duration of therapy. The issue is further complicated by combination antiangiogenesis to other cytotoxic or biologic agents. There is no way to determine which patients are most likely respond to a given form of antiangiogenic therapy. Activation of alternative pathways associated with disease progression in patients undergoing antiangiogenic therapy has also been recognized. There is increasing importance in identifying, validating and standardizing potential response biomarkers for antiangiogenesis therapy for HCC patients. In this review, biomarkers for antiangiogenesis therapy including systemic, circulating, tissue and imaging ones are summarized. The strength and deficit of circulating and imaging biomarkers were further demonstrated by a series of studies in HCC patients receiving radiotherapy with or without thalidomide.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

In Vivo Kinematics of Functional Ankle Instability Patients and Lateral Ankle Sprain Copers During Stair Descent

Patients with mechanic ankle instability experience increased tibiotalar and subtalar joint laxity. However, in vivo joint kinematics in functional ankle instability (FAI) patients and lateral ankle sprain (LAS) copers, especially during dynamic activities, are poorly understood. Ten FAI patients, 10 LAS copers, and 10 healthy controls were included in this study. A dual fluoroscopic imaging system was used to analyze the tibiotalar and subtalar joint kinematics during stair descent. Five key poses of stair descent were analyzed. Kinematic data from six degrees of freedom were calculated utilizing a solid modeling software. The range of motion and joint positions in each degree of freedom were compared among the three groups. The tibiotalar joints of FAI patients and LAS copers were significantly more inverted than those of healthy controls during the foot strike (p = 0.016, = 0.264). The subtalar joints of FAI patients were significantly more anteriorly translated (pose 2, p = 0.003, = 0.352; pose 3, p < 0.001, = 0.454; pose 4, p = 0.004, = 0.334), inverted (pose 4, p = 0.027, = 0.234; pose 5,p = 0.034, = 0.221), and externally rotated (pose 4, p = 0.037, = 0.217; pose 5; p = 0.004, = 0.331) than those of healthy controls during the mid‐stance and the heel off. The FAI patients showed excessive tibiotalar inversion and subtalar joint hypermobility during stair descent. Meanwhile, the LAS copers maintained subtalar joint stability, and only showed excessive tibiotalar inversion in foot strike. These data provide insight into the mechanisms behind the development of FAI after initial LAS. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:1860–1867, 2019     

The use of cadaver models to diagnose rib fractures: A pilot study

Background

In the emergency department, rib fractures are a common finding in patients who sustain chest trauma. Rib fractures may be a sign of significant, underlying pathology, especially in the elderly patients where rib fractures are associated with significant morbidity and mortality. To date, no studies have evaluated the ability of ultrasound to detect rib fractures using cadaver models and subsequently use this model as a teaching tool.

Temperature-controlled power modulation compensates for heterogeneous nanoparticle distributions: a computational optimization analysis for magnetic hyperthermia

Purpose: To study, with computational models, the utility of power modulation to reduce tissue temperature heterogeneity for variable nanoparticle distributions in magnetic nanoparticle hyperthermia.

Methods: Tumour and surrounding tissue were modeled by elliptical two- and three-dimensional computational phantoms having six different nanoparticle distributions. Nanoparticles were modeled as point heat sources having amplitude-dependent loss power. The total number of nanoparticles was fixed, and their spatial distribution and heat output were varied. Heat transfer was computed by solving the Pennes’ bioheat equation using finite element methods (FEM) with temperature-dependent blood perfusion. Local temperature was regulated using a proportional-integral-derivative (PID) controller. Tissue temperature, thermal dose and tissue damage were calculated. The required minimum thermal dose delivered to the tumor was kept constant, and heating power was adjusted for comparison of both the heating methods.

Results: Modulated power heating produced lower and more homogeneous temperature distributions than did constant power heating for all studied nanoparticle distributions. For a concentrated nanoparticle distribution, located off-center within the tumor, the maximum temperatures inside the tumor were 16% lower for modulated power heating when compared to constant power heating. This resulted in less damage to surrounding normal tissue. Modulated power heating reached target thermal doses up to nine-fold more rapidly when compared to constant power heating.

Conclusions: Controlling the temperature at the tumor-healthy tissue boundary by modulating the heating power of magnetic nanoparticles demonstrably compensates for a variable nanoparticle distribution to deliver effective treatment.