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Early clinical diagnosis, effective intraoperative guidance, and an accurate prognosis can lead to timely and effective medical treatment. The current conventional clinical methods have several limitations. Therefore, there is a need to develop faster and more reliable clinical detection, treatment, and monitoring methods to enhance their clinical applications. Raman spectroscopy is noninvasive and provides highly specific information about the molecular structure and biochemical composition of analytes in a rapid and accurate manner. It has a wide range of applications in biomedicine, materials, and clinical settings. This review primarily focuses on the application of Raman spectroscopy in clinical medicine. The advantages and limitations of Raman spectroscopy over traditional clinical methods are discussed. In addition, the advantages of combining Raman spectroscopy with machine learning, nanoparticles, and probes are demonstrated, thereby extending its applicability to different clinical phases. Examples of the clinical applications of Raman spectroscopy over the last 3 years are also integrated. Finally, various prospective approaches based on Raman spectroscopy in clinical studies are surveyed, and current challenges are discussed. [ABSTRACT FROM AUTHOR]

Fluorescent analysis of bone provides valuable insights into bone structures. However, conventional dyes suffer from low specificity on bone tissue, small stokes shift, short fluorescent lifetime, and aggregation‐caused quenching effect, which result in low efficacy and artifacts. In this work, we design an aggregation‐induced emission (AIE)‐active iridium(III) complex (Ir‐BP2) as a highly selective, convenient, nondestructiveness, and dual‐mode staining agent for bone analysis. Ir‐BP2 containing phosphonate groups selectively binds to hydroxyapatites, the main component of bone matrix, and exhibits turn‐on AIE phosphorescence with prolonged lifetime. Ir‐BP2 exhibits promising biosafety and offers higher accuracy in staining calcium deposits than conventional Alizarin Red S staining assay when it is employed in real‐time monitoring of osteogenesis differentiation process. A ready‐to‐use staining spray of Ir‐BP2 is fabricated. By using fluorescent imaging and lifetime imaging, Ir‐BP2 staining provides valuable insights into bone microstructure analysis, microdamage diagnosis, and bone growth state identification. Further, Ir‐BP2 is successfully applied on a human spine vertebra for diagnosing bone invasiveness of eosinophilic granuloma, validating its clinical practice. This work presents a powerful tool in bone analysis and will lead to new approaches for the diagnosis and treatment of bone‐related diseases. [ABSTRACT FROM AUTHOR]

Diagnostic medical imaging plays an imperative role in clinical assessment and treatment of medical abnormalities. The fusion of multimodal medical images merges complementary information present in the multi-source images and provides a better interpretation with improved diagnostic accuracy. This paper presents a CT–MR neurological image fusion method using an optimised biologically inspired neural network in nonsubsampled shearlet (NSST) domain. NSST decomposed coefficients are utilised to activate the optimised neural model using particle swarm optimisation method and to generate the firing maps. Low and high-frequency NSST subbands get fused using max-rule based on firing maps. In the optimisation process, a fitness function is evaluated based on spatial frequency and edge index of the resultant fused image. To analyse the fusion performance, extensive experiments are conducted on the different CT–MR neurological image dataset. Objective performance is evaluated based on different metrics to highlight the clarity, contrast, correlation, visual quality, complementary information, salient information, and edge information present in the fused images. Experimental results show that the proposed method is able to provide better-fused images and outperforms other existing methods in both visual and quantitative assessments. [ABSTRACT FROM AUTHOR]

Background: Appropriate depression care is a cancer‐care priority. However, many cancer survivors live with undiagnosed and untreated depression. Prostate cancer survivors may be particularly vulnerable, but little is known about their access to depression care. The goal of this study was to describe patterns and predictors of clinical diagnosis and treatment of depression in prostate cancer survivors. Methods: Generalized estimating equations were used to evaluate indicators of self‐reported clinical diagnosis and treatment depression as a function of individual‐level characteristics within a longitudinal dataset. The data were from a population‐based cohort of North Carolinian prostate cancer survivors who were enrolled from 2004 to 2007 on the North Carolina‐Louisiana Prostate Cancer Project (N = 1,031), and prospectively followed annually from 2008 to 2011 on the Health Care Access and Prostate Cancer Treatment in North Carolina (N = 805). Results: The average rate of self‐reported clinical diagnosis of depression was 44% (95% CI: 39%‐49%), which declined from 60% to 40% between prostate cancer diagnosis and 5‐7 years later. Factors associated with lower odds of self‐reported clinical diagnosis of depression include African‐American race, employment, age at enrollment, low education, infrequent primary care visits, and living with a prostate cancer diagnosis for more than 2 years. The average rate of self‐reported depression treatment was 62% (95% CI: 55%‐69%). Factors associated with lower odds of self‐reported depression treatment included employment and living with a prostate cancer diagnosis for 2 or more years. Conclusion: Prostate cancer survivors experience barriers when in need of depression care. [ABSTRACT FROM AUTHOR]