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The paraspinal muscles of the cervical, thoracic, and lumbar spine are important pain generators because muscle strains or myofascial pain syndrome caused by trigger points are common during clinical practice. Ultrasonography is the most convenient imaging tool for evaluating these muscles due to its advantages, such as providing good delineation of soft tissues, easy accessibility, and zero radiation. Additionally, ultrasound can serve as a useful guiding tool for paraspinal muscle intervention to prevent inadvertent injuries to vital axial neurovascular structures. This pictorial essay presents ultrasound scanning protocols for the paraspinal and other associated muscles as well as a discussion of their clinical relevance. Axial magnetic resonance imaging has also been used to elucidate reciprocal anatomy. In conclusion, ultrasound imaging proves to be a valuable tool that facilitates the differentiation of individual paraspinal muscles. This capability significantly enhances the precision of interventions designed to address myofascial pain syndrome.

ABSTRACT: Currently, the second most commonly diagnosed cancer in the world is lung cancer, and 85% of cases are non-small cell lung cancer (NSCLC). With growing knowledge of oncogene drivers and cancer immunology, several novel therapeutics have emerged to improve the prognostic outcomes of NSCLC. However, treatment outcomes remain diverse, and an accurate tool to achieve precision medicine is an unmet need. Radiomics, a method of extracting medical imaging features, is promising for precision medicine. Among all radiomic tools, 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET)-based radiomics provides distinct information on glycolytic activity and heterogeneity. In this review, we collected relevant literature from PubMed and summarized the various applications of 18F-FDG PET-derived radiomics in improving the detection of metastasis, subtyping histopathologies, characterizing driver mutations, assessing treatment response, and evaluating survival outcomes of NSCLC. Furthermore, we reviewed the values of 18F-FDG PET-based deep learning. Finally, several challenges and caveats exist in the implementation of 18F-FDG PET-based radiomics for NSCLC. Implementing 18F-FDG PET-based radiomics in clinical practice is necessary to ensure reproducibility. Moreover, basic studies elucidating the underlying biological significance of 18F-FDG PET-based radiomics are lacking. Current inadequacies hamper immediate clinical adoption; however, radiomic studies are progressively addressing these issues. 18F-FDG PET-based radiomics remains an invaluable and indispensable aspect of precision medicine for NSCLC. [ABSTRACT FROM AUTHOR]

This study investigates the pricing strategies of a mobile payment platform connecting merchants and customers who may bypass the platform and trade in cash. Our analytical model incorporates cross-side network externalities at both sides of the platform. We find that the optimal pricing strategy involves cross-subsidization, including subsidizing customers to register for the service while charging the merchants per transaction. Moreover, the technology option adopted by the platform influences this optimal pricing format. In particular, the platform should subsidize customers more if the payment technology imposes larger transaction costs on customers and charge merchants more if banks demand a higher payment processing fee. Our major findings remain qualitatively valid when per-transaction subsidy is available and the marginal benefit of cross-side network externalities diminishes. Finally, the presence of a platform improves social welfare if the per-transaction subsidy sufficiently stimulates consumption on the platform. [ABSTRACT FROM AUTHOR]

Objective: To investigate the prognostic value of 18F-FDG PET-based intensity, volumetric features, and deep learning (DL) across different generations of PET scanners in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma receiving tyrosine kinase inhibitor (TKI) treatment. Methods: We retrospectively analyzed the pre-treatment 18F-FDG PET of 217 patients with advanced-stage lung adenocarcinoma and actionable EGFR mutations who received TKI as first-line treatment. Patients were separated into analog (n = 166) and digital (n = 51) PET cohorts. 18F-FDG PET-derived intensity, volumetric features, ResNet-50 DL of the primary tumor, and clinical variables were used to predict progression-free survival (PFS). Independent prognosticators were used to develop prediction model. Model was developed and validated in the analog and digital PET cohorts, respectively. Results: In the analog PET cohort, female sex, stage IVB status, exon 19 deletion, SUVmax, metabolic tumor volume, and positive DL prediction independently predicted PFS. The model devised from these six prognosticators significantly predicted PFS in the analog (HR = 1.319, p < 0.001) and digital PET cohorts (HR = 1.284, p = 0.001). Our model provided incremental prognostic value to staging status (c-indices = 0.738 vs. 0.558 and 0.662 vs. 0.598 in the analog and digital PET cohorts, respectively). Our model also demonstrated a significant prognostic value for overall survival (HR = 1.198, p < 0.001, c-index = 0.708 and HR = 1.256, p = 0.021, c-index = 0.664 in the analog and digital PET cohorts, respectively). Conclusions: Combining 18F-FDG PET-based intensity, volumetric features, and DL with clinical variables may improve the survival stratification in patients with advanced EGFR-mutated lung adenocarcinoma receiving TKI treatment. Implementing the prediction model across different generations of PET scanners may be feasible and facilitate tailored therapeutic strategies for these patients. [ABSTRACT FROM AUTHOR]

Up to 50% of head and neck squamous cell carcinoma (HNSCC) patients have lymph node (LN) metastasis, resulting in poor survival rate. Numerous studies have supported the notion that the alterations of gene expression and mechanical properties of cancer cells play an important role in cancer metastasis. However, which genes and how they regulate the biomechanical properties of HNSCC cells to promote LN metastasis remains elusive. In this study, we used an LN-metastatic mouse model in vivo to generate an LN-metastatic head and neck squamous cell carcinoma cell line and compared the differences in the biomolecular and biomechanical properties of LN-metastatic and non-metastatic cells. Our results showed that LN-metastatic cells had a higher level of Snail expression compared to non-LN-metastatic cells. The higher Snail expression promoted the cellular invasion capability in confined environments, mainly by increasing the longitudinal strain of the cell nuclei, which could be attributed to the stronger cell traction force and softer nuclear stiffness. These two biomechanical changes were correlated, respectively, to a larger amount of focal adhesion and less amount of nuclear lamins. Taken together, our works revealed not only the biomechanical profiles of LN-metastatic cells but also the corresponding biomolecular expressions to pinpoint the key process in LN metastasis.

Ischiofemoral impingement syndrome is a neglected cause of posterior hip pain which is derived from narrowing of the space between the lateral aspect of the ischium and the medial aspect of the lesser trochanter. Its diagnosis is challenging and requires the combination of physical tests and imaging studies. In the present narrative review, we found that femoral anteversion predisposes patients to the narrowing of the ischiofemoral space and subsequent quadratus femoris muscle injury. Magnetic resonance imaging serves as the gold-standard diagnostic tool, which facilities the quantification of the ischiofemoral distance and the recognition of edema/fat infiltration/tearing of the quadratus femoris muscle. Ultrasound is useful for scrutinizing the integrity of deep gluteal muscles, and its capability to measure the ischiofemoral space is comparable to that of magnetic resonance. Various injection regimens can be applied to treat ischiofemoral impingement syndrome under ultrasound guidance and they appear to be safe and effective. Finally, more randomized controlled trials are needed to build solid bases of evidence on ultrasound-guided interventions in the management of ischiofemoral impingement syndrome.

A new method is developed to derive the hydrometer's bulk density and bulk water fraction from collocated measurements from Micro-Rain Radar (MRR) and Particle Size and Velocity disdrometer (Parsivel). Rigorous particle scattering simulation, namely the T-matrix method, is applied to particle size distribution data of Parsivel to calculate the reflectivity (ZHH). The possible combinations of the particle's ice, air, and water are derived to compare them with the MRR-measured ZHH. The combination of minimum water fraction subsequently determines the bulk density (ρbulk). The proposed method is applied to the data collected from the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018) Projects and its pre-campaign. The estimated ρbulk was examined by self-evaluation of reflectivity weighted fall velocity (Vz) of MRR and independent comparison of the liquid-equivalent snowfall rate (SR) of collocated Pluvio. The bias values are adequately low (Vz: -0.27~0.14 m s-1, SR: 0.52~0.74 mm hr-1). The correlation coefficient of calculated SR from estimated ρbulk and observed SR from Pluvio can be up to 0.74. The results indicate the capability to derive reliable ρbulk through the proposed method, leveraging the compact and easily deployable designs of MRR and Parsivel. The derived bulk density of the two warm-low cases (28 February and 07 March 2018) shares a similar transition as the systems were decaying. The particles with higher bulk density and bulk water fraction were found in the coastal sites (BKC and GWU: mean ρbulk values are 0.12 to 0.25 g cm-3), typically accompanied by higher liquid-water constituents (mean values of the top 5% bulk water fraction are 0.33 to 0.50) than the inland sites (YPO and MHS: mean ρbulk values are 0.09 to 0.08 and mean values of the top 5% bulk water fraction are 0.001 to 0.029) during such synoptic conditions. [ABSTRACT FROM AUTHOR]

Purpose: 18F‐FDG PET quantitative features are susceptible to respiratory motion. However, studies using clinical patient data to explore the impact of respiratory motion on 18F‐FDG PET radiomic features are limited. In this study, we investigated the impact of respiratory motion on radiomics stability with clinical 18F‐FDG PET images using a data‐driven gating (DDG) algorithm on the digital PET scanner. Materials and Methods: A total of 101 patients who underwent oncological 18F‐FDG PET scans were retrospectively included. A DDG algorithm combined with a motion compensation technique was used to extract the PET images with respiratory motion correction. 18F‐FDG‐avid lesions from the thorax to the upper abdomen were analyzed on the non‐DDG and DDG PET images. The lesions were segmented with a 40% threshold of the maximum standardized uptake. A total of 725 radiomic features were computed from the segmented lesions, including first‐order, shape, texture, and wavelet features. The intraclass correlation coefficient (ICC) and coefficient of variation (COV) were calculated to evaluate feature stability. An ICC above 0.9 and a COV below 5% were considered high stability. Results: In total, 168 lesions with and without respiratory motion correction were analyzed. Our results indicated that most 18F‐FDG PET radiomic features are sensitive to respiratory motion. Overall, only 27 out of 725 (3.72%) radiomic features were identified as highly stable, including one from the first‐order features (entropy), one from the shape features (sphericity), four from the gray‐level co‐occurrence matrix features (normalized and unnormalized inverse difference moment, joint entropy, and sum entropy), one from the gray‐level run‐length matrix features (run entropy), and 20 from the wavelet filter‐based features. Conclusion: Respiratory motion has a significant impact on 18F‐FDG PET radiomics stability. The highly stable features identified in our study may serve as potential candidates for further applications, such as machine learning modeling. [ABSTRACT FROM AUTHOR]