Search Results (51)

Advanced Gastric Signet Ring Cell Carcinoma (SRCC) is characterized by aggressive behavior, high metastatic potential, and extremely poor prognosis. There is an urgent need for effective imaging modalities to evaluate systemic metastatic lesions and to dynamically monitor disease progression during treatment. We report a rare case of a 26-year-old female with advanced SRCC presenting with extensive systemic metastases, clinically staged as IV (cT4N3M1). High-frequency and conventional ultrasound imaging revealed metastatic lesions involving the scalp soft tissues, cervical lymph nodes, intercostal soft tissues, pancreatic-splenic hilum region, pelvic cavity, peritoneum and omentum. The ultrasonographic findings were highly consistent with contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI) results. The patient received seven cycles of a modified BEMA regimen (oxaliplatin, leucovorin and 5-fluorouracil) combined with nivolumab. Serial ultrasound monitoring indicated continuous disease progression. Due to poor therapeutic response, the patient succumbed to acute obstructive renal failure caused by tumor progression seven months after diagnosis. This report provided a comprehensive ultrasonographic assessment of widespread and rare metastatic sites in advanced SRCC, a scenario seldom documented. The combination of high-frequency ultrasound and Super Microvascular Imaging (SMI) offered precise, radiation-free, and repeatable evaluation of both superficial and deep lesions, proving particularly valuable for real-time monitoring of treatment response in critically ill patients. These findings underscore the unique role of systemic ultrasound in enhancing metastatic detection and therapeutic evaluation for advanced SRCC. Full article

Amyotrophic lateral sclerosis (ALS) is still a heterogeneous neurodegenerative disorder that can be identified clinically and biologically, without a strong set of biomarkers that can adequately measure its fast rate of progression and molecular heterogeneity. In this review, we intend to consolidate the most relevant and timely advances in ALS biomarker discovery, in order to begin to bring molecular, imaging, genetic, and digital areas together for potential integration into a precision medicine approach to ALS. Our goal is to begin to display how several biomarkers in development (e.g., neurofilament light chain (NfL), phosphorylated neurofilament heavy chain (pNfH), TDP-43 aggregates, mitochondrial stress markers, inflammatory markers, etc.) are changing our understanding of ALS and ALS dynamics. We will attempt to provide a framework for thinking about biomarkers in a systematic way where our candidates are not signals alone but part of a tethered pathophysiological cascade. We are particularly interested in the fast progressor phenotype, a devastating and under-characterized subset of ALS due to a rapid axonal degeneration, early respiratory failure, and very short life span. We will try to highlight the salient molecular features of this ALS subtype, including SOD1 A5V toxicity, C9orf72 repeats, FUS variants, mitochondrial collapse, and impaired autophagy mechanisms, and relate these features to measurable blood and CSF (biomarkers) and imaging platforms. We will elaborate on several interesting tools, for example, single-cell transcriptomics, CSF exosomal cargo analysis, MRI techniques, and wearable sensor outputs that are developing into high-resolution windows of disease progression and onset. Instead of providing a static catalog, we plan on providing a conceptual roadmap to integrate biomarker panels that will allow for earlier diagnosis, real-time disease monitoring, and adaptive therapeutic trial design. We hope this synthesis will make a meaningful contribution to the shift from observational neurology to proactive biologically informed clinical care in ALS. Although there are still considerable obstacles to overcome, the intersection of a precise molecular or genetic association approach, digital phenotyping, and systems-level understandings may ultimately redefine how we monitor, care for, and treat this challenging neurodegenerative disease. Full article

Background: Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumour, associated with poor survival outcomes and significant clinical challenges. Conventional diagnostic methods, including MRI, CT, and histopathological analysis of tissue biopsies, are limited by their inability to reliably distinguish treatment effects from true tumour progression, often resulting in misdiagnosis and delayed intervention. Repeated tissue biopsies are also invasive and unsuitable for longitudinal monitoring. Liquid biopsy, a minimally invasive approach analysing tumour-derived material in biofluids such as blood and cerebrospinal fluid (CSF), offers a promising alternative. This review aims to evaluate current evidence on circulating biomarkers including circulating tumour cells (CTCs), circulating tumour DNA (ctDNA), microRNAs (miRNAs), extracellular vesicles (EVs), and proteins in GBM diagnosis and monitoring, and to assess the potential role of artificial intelligence (AI) in enhancing their clinical application. Methods: A narrative synthesis of the literature was undertaken, focusing on studies that have investigated blood- and CSF-derived biomarkers in GBM patients. Key aspects evaluated included biomarker biology, detection techniques, diagnostic and prognostic value, current technical challenges, and progress towards clinical translation. Studies exploring AI and machine learning (ML) approaches for biomarker integration and analysis were also reviewed. Results: Liquid biopsy enables repeated and minimally invasive sampling of tumour-derived material, reflecting the genetic, epigenetic, proteomic, and metabolomic landscape of GBM. Although promising, its translation into routine clinical practice is hindered by the low abundance of circulating biomarkers and lack of standardised collection and analysis protocols. Evidence suggests that combining multiple biomarkers improves sensitivity and specificity compared with single-marker approaches. Emerging AI and ML tools show significant potential for improving biomarker discovery, integrating multi-omic datasets, and enhancing diagnostic and prognostic accuracy. Conclusions: Liquid biopsy represents a transformative tool for GBM management, with the capacity to overcome limitations of conventional diagnostics and provide real-time insights into tumour biology. By integrating multiple circulating biomarkers and leveraging AI-driven approaches, liquid biopsy could enhance diagnostic precision, enable dynamic disease monitoring, and improve clinical decision-making. However, large-scale validation and standardisation are required before routine clinical adoption can be achieved. Full article

Stroke is a significant global health concern characterized by the abrupt disruption of cerebral blood flow, leading to neurological impairment. Accurate and timely diagnosis—enabled by imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI)—is essential for differentiating stroke types and initiating interventions like thrombolysis, thrombectomy, or surgical management. In parallel, recent advancements in wearable technology, particularly smart clothing, offer new opportunities for stroke prevention, real-time monitoring, and rehabilitation. These garments integrate various sensors, including electrocardiogram (ECG) electrodes, electroencephalography (EEG) caps, electromyography (EMG) sensors, and motion or pressure sensors, to continuously track physiological and functional parameters. For example, ECG shirts monitor cardiac rhythm to detect atrial fibrillation, smart socks assess gait asymmetry for early mobility decline, and EEG caps provide data on neurocognitive recovery during rehabilitation. These technologies support personalized care across the stroke continuum, from early risk detection and acute event monitoring to long-term recovery. Integration with AI-driven analytics further enhances diagnostic accuracy and therapy optimization. This narrative review explores the application of smart clothing in conjunction with traditional imaging to improve stroke management and patient outcomes through a more proactive, connected, and patient-centered approach. Full article

Tissue-engineered scaffolds, particularly composite scaffolds composed of polymers combined with ceramics, bioactive glasses, or nanomaterials, play a vital role in regenerative medicine by providing structural and biological support for tissue repair. As scaffold designs grow increasingly complex, the need for non-invasive imaging modalities capable of monitoring scaffold integration, degradation, and tissue regeneration in real-time has become critical. This review summarizes current non-invasive imaging techniques used to evaluate tissue-engineered constructs, including optical methods such as near-infrared fluorescence imaging (NIR), optical coherence tomography (OCT), and photoacoustic imaging (PAI); magnetic resonance imaging (MRI); X-ray-based approaches like computed tomography (CT); and ultrasound-based modalities. It discusses the unique advantages and limitations of each modality. Finally, the review identifies major challenges—including limited imaging depth, resolution trade-offs, and regulatory hurdles—and proposes future directions to enhance translational readiness and clinical adoption of imaging-guided tissue engineering (TE). Emerging prospects such as multimodal platforms and artificial intelligence (AI) assisted image analysis hold promise for improving precision, scalability, and clinical relevance in scaffold monitoring. Full article

Although intracranial hypertension (ICH) has traditionally been framed as simply a numerical escalation of intracranial pressure (ICP) and usually dealt with in its clinical form and not in terms of its complex underlying pathophysiology, an emerging body of evidence indicates that ICH is not simply an elevated ICP process but a complex process of molecular dysregulation, glymphatic dysfunction, and neurovascular insufficiency. Our aim in this paper is to provide a complete synthesis of all the new thinking that is occurring in this space, primarily on the intersection of glymphatic dysfunction and cerebral vein physiology. The aspiration is to review how glymphatic dysfunction, largely secondary to aquaporin-4 (AQP4) dysfunction, can lead to delayed cerebrospinal fluid (CSF) clearance and thus the accumulation of extravascular fluid resulting in elevated ICP. A range of other factors such as oxidative stress, endothelin-1, and neuroinflammation seem to significantly impair cerebral autoregulation, making ICH challenging to manage. Combining recent studies, we intend to provide a revised conceptualization of ICH that recognizes the nuance and complexity of ICH that is understated by previous models. We wish to also address novel diagnostics aimed at better capturing the dynamic nature of ICH. Recent advances in non-invasive imaging (i.e., 4D flow MRI and dynamic contrast-enhanced MRI; DCE-MRI) allow for better visualization of dynamic changes to the glymphatic and cerebral blood flow (CBF) system. Finally, wearable ICP monitors and AI-assisted diagnostics will create opportunities for these continuous and real-time assessments, especially in limited resource settings. Our goal is to provide examples of opportunities that exist that might augment early recognition and improve personalized care while ensuring we realize practical challenges and limitations. We also consider what may be therapeutically possible now and in the future. Therapeutic opportunities discussed include CRISPR-based gene editing aimed at restoring AQP4 function, nano-robotics aimed at drug targeting, and bioelectronic devices purposed for ICP modulation. Certainly, these proposals are innovative in nature but will require ethically responsible confirmation of long-term safety and availability, particularly to low- and middle-income countries (LMICs), where the burdens of secondary ICH remain preeminent. Throughout the review, we will be restrained to a balanced pursuit of innovative ideas and ethical considerations to attain global health equity. It is not our intent to provide unequivocal answers, but instead to encourage informed discussions at the intersections of research, clinical practice, and the public health field. We hope this review may stimulate further discussion about ICH and highlight research opportunities to conduct translational research in modern neuroscience with real, approachable, and patient-centered care. Full article

Primary hyperparathyroidism is commonly caused by parathyroid adenomas, hyperplasia, or, rarely, carcinoma. In up to 20% of cases, parathyroid tissue may be ectopic, often located in the mediastinum due to aberrant embryologic migration. Ectopic parathyroid glands pose a diagnostic and therapeutic challenge, and an accurate preoperative localization is essential for an effective and safe resection. Imaging modalities such as CT scan, TC-sestamibi scintigraphy, PET/CT, ultrasonography and MRI are routinely employed, whereas combined techniques offer improved diagnostic accuracy. Emerging approaches, however, including PET/CT with choline tracers, have shown promise in enhancing sensitivity in complex or recurrent cases. When ectopic glands are in the mediastinum, thoracic surgical intervention is required. Traditional open approaches, such as sternotomy or thoracotomy, are associated with significant morbidity. The development and evolution of minimally invasive surgery (MIS) has become the preferred approach in selected cases. When MIS is performed, intraoperative assessment and parathyroid identification are crucial to ensure complete gland removal. Intraoperative parathyroid hormone (ioPTH) monitoring provides real-time confirmation of surgical success. The integration of advanced imaging, intraoperative monitoring, and minimally invasive techniques significantly improves surgical outcomes while minimizing complications and accelerating patient recovery. Ultimately, the effective treatment of ectopic parathyroid glands relies on a personalized approach, adapting both diagnostic and surgical strategies to the unique anatomical and clinical context of each patient. Integration of advanced imaging, intraoperative monitoring, and minimally invasive techniques, combined with a multidisciplinary team involving endocrinologists, radiologists, and thoracic surgeons, is key to optimizing outcomes and reducing patient morbidity. Full article

Musculoskeletal (MSK) disorders remain a major global cause of disability, with diagnostic complexity arising from their heterogeneous presentation and multifactorial pathophysiology. Recent advances across imaging modalities, molecular biomarkers, artificial intelligence applications, and point-of-care technologies are fundamentally reshaping musculoskeletal diagnostics. This review offers a novel synthesis by unifying recent innovations across multiple diagnostic imaging modalities, such as CT, MRI, and ultrasound, with emerging biochemical, genetic, and digital technologies. While existing reviews typically focus on advances within a single modality or for specific MSK conditions, this paper integrates a broad spectrum of developments to highlight how use of multimodal diagnostic strategies in combination can improve disease detection, stratification, and clinical decision-making in real-world settings. Technological developments in imaging, including photon-counting detector computed tomography, quantitative magnetic resonance imaging, and four-dimensional computed tomography, have enhanced the ability to visualize structural and dynamic musculoskeletal abnormalities with greater precision. Molecular imaging and biochemical markers such as CTX-II (C-terminal cross-linked telopeptides of type II collagen) and PINP (procollagen type I N-propeptide) provide early, objective indicators of tissue degeneration and bone turnover, while genetic and epigenetic profiling can elucidate individual patterns of susceptibility. Point-of-care ultrasound and portable diagnostic devices have expanded real-time imaging and functional assessment capabilities across diverse clinical settings. Artificial intelligence and machine learning algorithms now automate image interpretation, predict clinical outcomes, and enhance clinical decision support, complementing conventional clinical evaluations. Wearable sensors and mobile health technologies extend continuous monitoring beyond traditional healthcare environments, generating real-world data critical for dynamic disease management. However, standardization of diagnostic protocols, rigorous validation of novel methodologies, and thoughtful integration of multimodal data remain essential for translating technological advances into improved patient outcomes. Despite these advances, several key limitations constrain widespread clinical adoption. Imaging modalities lack standardized acquisition protocols and reference values, making cross-site comparison and clinical interpretation difficult. AI-driven diagnostic tools often suffer from limited external validation and transparency (“black-box” models), impacting clinicians’ trust and hindering regulatory approval. Molecular markers like CTX-II and PINP, though promising, show variability due to diurnal fluctuations and comorbid conditions, complicating their use in routine monitoring. Integration of multimodal data, especially across imaging, omics, and wearable devices, remains technically and logistically complex, requiring robust data infrastructure and informatics expertise not yet widely available in MSK clinical practice. Furthermore, reimbursement models have not caught up with many of these innovations, limiting access in resource-constrained healthcare settings. As these fields converge, musculoskeletal diagnostics methods are poised to evolve into a more precise, personalized, and patient-centered discipline, driving meaningful improvements in musculoskeletal health worldwide. Full article

Optical Coherence Tomography (OCT) is a relatively new medical imaging device that provides high-resolution and real-time visualization of biological tissues. Initially designed for ophthalmology, OCT is now being applied in other types of pathologies, like cancer diagnosis. This review highlights its impact on disease diagnosis, biopsy guidance, and treatment monitoring. Despite its advantages, OCT has limitations, particularly in tissue penetration and differentiating between malignant and benign lesions. To overcome these challenges, the integration of nanoparticles has emerged as a transformative approach, which significantly enhances contrast and tumor vascularization at the molecular level. Gold and superparamagnetic iron oxide nanoparticles, for instance, have demonstrated great potential in increasing OCT’s diagnostic accuracy through enhanced optical scattering and targeted biomarker detection. Beyond these innovations, integrating OCT with multimodal imaging methods, including magnetic resonance imaging (MRI), positron emission tomography (PET), and ultrasound, offers a more comprehensive approach to disease assessment, particularly in oncology. Additionally, advances in artificial intelligence (AI) and biosensors have further expanded OCT’s capabilities, enabling real-time tumor characterization and optimizing surgical precision. However, despite these advancements, clinical adoption still faces several hurdles. Issues related to nanoparticle biocompatibility, regulatory approvals, and standardization need to be addressed. Moving forward, research should focus on refining nanoparticle technology, improving AI-driven image analysis, and ensuring broader accessibility to OCT-guided diagnostics. By tackling these challenges, OCT could become an essential tool in precision medicine, facilitating early disease detection, real-time monitoring, and personalized treatment for improved patient outcomes. Full article

Gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) represent a rare and varied class of neoplasms, characterized by diverse clinical presentations and prognostic trajectories. Accurate and prompt diagnosis is vital to inform and optimize therapeutic decisions. Ultrasound, including standard B-mode imaging and advanced methods such as contrast-enhanced ultrasound (CEUS) and endoscopic ultrasound (EUS), serves as a key component in the diagnostic evaluation of these tumors. B-mode US and CEUS provide non-invasive, accessible methods for early detection and characterization. On B-mode imaging, GEP-NETs typically present as well-defined, hyperechoic, or iso-echoic lesions, while CEUS highlights their characteristic vascularity, marked by arterial-phase hyperenhancement and venous-phase washout. Compared to CT and MRI, ultrasound offers real-time, dynamic imaging without ionizing radiation or nephrotoxic contrast agents, making it particularly advantageous for patients requiring frequent monitoring or with contraindications to other imaging modalities. CT and MRI are widely regarded as the preferred methods for staging and surgical planning due to their detailed anatomical visualization. However, ultrasound, especially CEUS, provides a significant adjunctive role in both early detection and the follow-up on GEP-NETs. This analysis delves into the strengths, challenges, and innovations in ultrasound technology for diagnosing pancreatic NETs, focusing on its contribution to comprehensive imaging strategies and its impact on patient care decisions. Full article

Background/Objectives: Accurate assessment of tumor response to neoadjuvant chemotherapy (NAC) in breast cancer is critical for optimizing treatment strategies. While magnetic resonance imaging (MRI) and mammography are commonly used for response evaluation, they have inherent limitations. Ultrasound (US) has emerged as a promising, cost-effective, and real-time alternative. This study aimed to evaluate the effectiveness of US in tracking tumor regression during NAC and its correlation with pathologic tumor regression grade (TRG). Methods: This study included 282 breast cancer patients undergoing NAC. Tumor size was measured using ultrasound at three key time points: pre-chemotherapy, after four cycles, and post-chemotherapy. Spearman’s correlation was used to assess the relationship between US-measured tumor changes and TRG. Multinomial logistic regression and receiver operating characteristic (ROC) curve analyses were performed to determine the predictive accuracy of the measurements from our US in identifying pathologic complete response (pCR). Conclusions: Ultrasound is a reliable, real-time imaging tool for monitoring NAC response in breast cancer patients. Its ability to predict pCR and track tumor shrinkage highlights its potential for treatment adaptation. Standardization of US protocols and integration with AI-based analysis may further improve its clinical utility, making it a valuable adjunct in breast cancer treatment monitoring. Full article

Background: Bone marrow (BM) adipocytes play a critical role in the progression of both solid tumor metastases and expansion of hematological malignancies across a spectrum of ages, from pediatric to aging populations. Single-point biopsies remain the gold standard for monitoring BM diseases, including hematologic malignancies, but these are limited in capturing the full complexity of loco-regional and global BM microenvironments. Non-invasive imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and Positron Emission Tomography (PET) could provide valuable alternatives for real-time evaluation in both preclinical translational and clinical studies. Methods: We developed a preclinical proton density fat fraction (PDFF) MRI technique for the quantitative assessment of BM composition, focusing on the fat fraction (FF) within mouse femurs. We validated this method using aging mice and young mice subjected to 10 Gy X-ray irradiation, compared to young control mice. Water–fat phantoms with varying fat percentages (0% to 100%) were used to optimize the imaging sequence, and immunohistochemical (IHC) staining with H&E validated equivalent adipose content in the femur BM region. Results: Significant differences in FF were observed across age groups (p = 0.001 for histology and p < 0.001 for PDFF) and between irradiated and control mice (p = 0.005 for histology and p = 0.002 for PDFF). A strong correlation (R²~0.84) between FF values from PDFF-MRI and histology validated the accuracy of the technique. Conclusions: These findings highlight PDFF-MRI’s potential as a non-invasive, real-time, in vivo biomarker for quantitatively assessing the BM fat fraction in preclinical studies, particularly in studies evaluating the effects of aging, disease progression, and cytotoxic cancer therapies, including chemotherapy and radiation. Full article

Bladder cancer, a highly heterogeneous disease, necessitates precise diagnostic and therapeutic strategies to enhance patient outcomes. Metabolomics, through comprehensive small-molecule analysis, provides valuable insights into cancer-associated metabolic alterations at the cellular, tissue, and systemic levels. Concurrently, molecular imaging modalities like PET, MRI, and CT enable the non-invasive, real-time visualization of tumor biology, facilitating the spatial and functional assessment of biomarkers. Key findings highlight the identification of metabolomic profiles correlated with cancer progression, recurrence, and treatment responses across serum, urine, and tissue samples. Advanced analytical platforms, such as LC-MS and NMR, uncover distinct metabolic signatures and pathway alterations in glycolysis, amino acid metabolism, and lipid biosynthesis. Molecular imaging further enhances staging accuracy and treatment monitoring by visualizing metabolic activity and receptor expression. The integration of these technologies addresses the limitations of invasive diagnostic methods and paves the way for precision oncology. Future advancements should focus on multi-omics integration, AI-driven analysis, and large-scale clinical validation to ensure broad accessibility and transformative impacts on bladder cancer management. Full article

The reliability of the “last mile” of cold-chain logistics is crucial for food safety. This study investigated the effect of different packaging treatments on the quality of anhydrously preserved live Ruditapes philippinarum (R. philippinarum) in “last mile” cold chain disruption. The temperature profiles of three packaging treatments at ambient temperature (25 °C) were monitored. Quality assessment was conducted based on sensory scoring, survival rate, total viable count (TVC), water-holding capacity (WHC), pH, total volatile basic nitrogen (TVB-N), thiobarbituric acid-reactive substances (TBA), color, and texture. Low-frequency nuclear magnetic resonance (LF-NMR) and magnetic resonance imaging (MRI) were utilized to characterize the water state profile. The findings demonstrated a progressive increase in internal package temperature throughout the “last mile”, with packages containing additional ice packs more effectively maintaining lower temperature and restricting the migration of “hot spots” towards the center. Specifically, the package with three ice packs maintained a markedly lower temperature, which effectively inhibited microbial activity, lipid oxidation, and the production of alkaline substances, resulting in higher survival rates, water-holding capacity, texture, sensory acceptability, and immobilized water fraction. Furthermore, LF-NMR relaxation parameters showed strong correlations with various physicochemical indices, suggesting a potential approach for real-time quality monitoring. This study provides insights for maintaining live R. philippinarum quality during the “last mile”. Full article

This narrative review provides an overview of the various diagnostic tools used to assess cartilage health, with a focus on early detection, nutrition intervention, and management of osteoarthritis. Early detection of cartilage damage is crucial for effective patient management. Traditional diagnostic tools like radiography and conventional magnetic resonance imaging (MRI) sequences are more suited to detecting late-stage structural changes. This paper highlights advanced imaging techniques, including sodium MRI, T2 mapping, T1ρ imaging, and delayed gadolinium-enhanced MRI of cartilage, which provide valuable biochemical information about cartilage composition, particularly the glycosaminoglycan content and its potential links to nutrition-related factors influencing cartilage health. Cartilage degradation is often linked with inflammation and measurable via markers like CRP and IL-6 which, although not specific to cartilage breakdown, offer insights into the inflammation affecting cartilage. In addition to imaging techniques, biochemical markers, such as collagen breakdown products and aggrecan fragments, which reflect metabolic changes in cartilage, are discussed. Emerging tools like optical coherence tomography and hybrid positron emission tomography–magnetic resonance imaging (PET-MRI) are also explored, offering high-resolution imaging and combined metabolic and structural insights, respectively. Finally, wearable technology and biosensors for real-time monitoring of osteoarthritis progression, as well as the role of artificial intelligence in enhancing diagnostic accuracy through pattern recognition in imaging data are addressed. While these advanced diagnostic tools hold great potential for early detection and monitoring of osteoarthritis, challenges remain in clinical translation, including validation in larger populations and integration into existing clinical workflows and personalized treatment strategies for cartilage-related diseases. Full article