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At least 253 records · Page 14Linked to original sources
PubMed2002

Hip-Op: an innovative software to plan total hip replacement surgery.

This paper describes an innovative surgical simulation software environment for the pre-operative planning of total hip replacement surgery. The software is a CT-based three-dimensional planning environment, with a user-friendly graphic user interface based on the multimodal display visualization paradigm. Although it relies on a fully three dimensional internal representation, this approach represents the relevant anatomical objects by means of multiple views, each simulating a different medical imaging modality familiar to the medical professional. In the Hip-Op program the multimodal display interface integrates four different display modalities: orthogonal radiographs, Blended slices, CT slices, and arbitrary slices. A conventional surface rendering view is also available. The user 'navigates' the prosthetic components, which are dynamically selected from a library of available parts, within the CT volume while the implant and the patient anatomy are simultaneously rendered in each specialized view. Beside a consideration of anatomical compatibility, the surgeon may evaluate the planned implant type, size and position, also on the basis of two analysis modules that compute the achieved level of implant fitting and filling. After being evaluated in an internal clinical trial, the software is currently made available as freeware at http:// www.ior.it/hipop/.

Algorithms↗
PubMed2026

Efforts towards a precision medicine approach in juvenile idiopathic arthritis.

Juvenile idiopathic arthritis (JIA) is the commonest group of childhood arthritides. Despite the availability of advanced therapeutics, many children and young people (CYP) with JIA experience disease flares, and in some, chronic joint damage. Tailoring treatment based on unique biological profiles would benefit CYP with JIA given their variable clinical presentation and disease course. To date, biomarkers to predict treatment response are lacking. With advances in single cell technologies, we are now able to profile the genes and proteins of target tissues at unprecedented resolution to define the biological basis of disease and guide novel treatment approaches. The complex analyses and combination of biological and clinical outcome data from large datasets across disease phenotypes have become possible with the development of computational and machine learning methods. Here, we summarize the strategies to integrate data through multimodal based approaches to maximize precision medicine and research priorities for CYP with JIA.

Humans↗
PubMed2006

Objectives and limitations of bloodless medical care.

PURPOSE OF REVIEW: To outline the rationale, limitations, and execution of bloodless medical and surgical programs, highlighting characteristics that contribute to successful outcomes. RECENT FINDINGS: Clinical experiences with patients who refuse blood transfusions for religious reasons have provided valuable lessons and raise intriguing questions about the necessity of routine blood transfusions. Healthcare centers with bloodless medicine and surgery programs feature a novel concept of patient care aimed at improving outcomes. A one-tiered approach to minimize blood usage for all patients, regardless of religious beliefs, is being successfully adopted at an increasing number of institutions. Since most single blood-conservation techniques reduce blood usage by just 1-2 units, a series of integrated preoperative, intraoperative, and postoperative conservation approaches is required. These include preoperative autologous donation, erythropoietic support, acute normovolemic hemodilution, individualized assessment of anemia tolerance, implementation of conservative transfusion thresholds, meticulous surgical techniques, and judicious use of phlebotomy and pharmacologic agents for limiting blood loss. SUMMARY: The objectives of bloodless medicine and surgery programs are straightforward but require staff with expertise in transfusion medicine, intensive teamwork, patient-specific customization, careful planning, and integrated use of multimodal strategies.

Blood Loss, Surgical↗
PubMed2001

State-dependent modulation of sensory feedback.

By tradition - and for historical reasons - reflex pathways and interneurones have been named by their dominating sensory input. Later studies have demonstrated that each individual interneurone, as a rule, receives a broad convergence from a large variety of sensory modalities, as well as inputs from one or more descending tracts. It is thus possible that the traditional nomenclature inadvertently has served as a 'straightjacket' for conceptual development in this field. Indeed, there is now much evidence in favour of the view that the many classes of spinal interneurones may be seen as 'functional units' representing different levels of muscle synergies, parts of movements, or even more integrated motor behaviour. Such 'functional units' may be used by (different) descending pathways to mediate the motor commands from the brain and integrate the appropriate (multimodal) sensory feedback into the central command. A given sensory stimulus would then be able to affect the motor output through a number of parallel, or alternative, segmental pathways belonging to different 'functional units'. If this were correct it would indeed be predicted, rather than coming as a surprise, that a given sensory stimulus can result in different outputs - even with a different sign - depending on the preceding selection of active 'functional units', i.e. the type of motor activity initiated by the brain.

Feedback↗
PubMed2026

Research agenda to advance anhedonia assessment, understanding and treatment: an ECNP-GALENOS expert meeting report.

Anhedonia, broadly defined as a reduced ability to experience interest or pleasure, represents an important transdiagnostic neuropsychiatric symptom dimension which may benefit from targeted diagnostics and treatments. Different lines of research have proposed that it comprises multiple facets, including deficits in anticipatory ('wanting') and consummatory ('liking') reward processing as well as reward learning and affects different aspects of life (eg, social, physical, cognitive). Certain facets-more specifically anticipation, motivation and reward learning-likely involve blunted phasic dopaminergic signalling. However, recent meta-analytical evidence of human depression studies indicates that prodopaminergic antidepressants produce relatively small improvements in anhedonia symptoms and suggest that mechanisms beyond dopamine likely contribute to anhedonia. This stimulated an expert meeting to review the literature and define priorities for future research in anhedonia. A central key priority is developing a translational biologically-informed nomenclature and consensus that solves the current mismatch between constructs, paradigms and measures, and mechanisms, which separates discrete reward-related processes such as effort allocation, reward learning and anticipatory interest versus consummatory pleasure. Clinical research priorities are improved multimodal measurement tools, integrating neurobiological frameworks (eg, neuroimaging, electrophysiology and liquid biomarkers capturing dopaminergic, glutamatergic, opioid and immunometabolic pathways) and transdiagnostic studies across neuropsychiatric disorders and developmental stages. Innovative trial designs that explicitly target anhedonic phenotypes as a primary outcome and test mechanism-based interventions are also needed. Translational research recommendations include back-translation strategies that begin with patient-relevant phenotypes followed by the development of comparable human and animal tasks that target reward-related processes, such as effort allocation, reward learning and anticipatory interest versus consummatory pleasure, improve cross-species behavioural paradigms and enhance methodological rigour and reproducibility. Collectively, these recommendations will help refine the conceptualisation of anhedonia and advance its role within precision psychiatry as a mechanistically grounded target across multiple disorders.

Humans↗
PubMed2026

Impact of PerioperAtive LidocAine Infusions on Enhanced Recovery After Noncardiac Surgery (IMPALA-ERAS) in an inpatient setting: rationale, design and protocol for a sequential, repeated crossover trial.

INTRODUCTION: Multimodal analgesic strategies designed to minimise perioperative opioid exposure are fundamental components of enhanced recovery after surgery (ERAS) pathways. Despite widespread implementation of ERAS protocols, the optimal analgesic regimen remains undefined, as the individual contributions of specific agents to overall analgesic efficacy and opioid-sparing effects are not fully elucidated. Intravenous lidocaine, a widely utilised local anaesthetic, possesses both analgesic and anti-inflammatory properties and has been associated with improved gastrointestinal recovery. This study seeks to pragmatically evaluate the impact of incorporating perioperative intravenous lidocaine infusion into established ERAS pathways on postoperative functional recovery. METHODS AND ANALYSIS: The Impact of PerioperAtive LidocAine Infusions (IMPALA) on ERAS trial is a single-centre, pragmatic, cluster-randomised, double-blinded, placebo-controlled study. A total of 2290 patients undergoing elective colorectal surgery, emergency general surgery, urology, ventral hernia repair, surgical oncology or spine surgery will be randomly assigned to receive either intraoperative and postoperative intravenous lidocaine infusions (administered for up to 48 hours) or placebo as part of a standardised multimodal analgesic regimen integrated into established ERAS pathways. The primary outcome is case mix index-adjusted resource length of stay, defined as the time interval from surgical initiation to hospital discharge adjusted for case mix index. The primary outcome is total inpatient opioid consumption within the first 72 hours, reported in oral morphine milligram equivalents. Secondary outcomes include various in-hospital clinical endpoints derived from the electronic health record. ETHICS AND DISSEMINATION: This protocol and accompanying statistical analysis plan outline the study design, primary and secondary endpoints and analytic methodology. The IMPALA-ERAS trial has received ethical approval from the Vanderbilt University Institutional Review Board (IRB: 250617). The findings will be disseminated via peer-reviewed publications and presentations at national conferences. Results from this trial are expected to inform evidence-based practices regarding perioperative lidocaine infusion and its potential contributions to enhanced postoperative recovery in surgical patients. TRIAL REGISTRATION NUMBER: NCT07224711.

Humans↗
PubMed1999

Does effective postoperative pain management influence surgical morbidity?

It has been assumed that adequate postoperative pain relief will improve outcome from surgery, but several controlled trials have demonstrated that pain treatment with nonsteroidal anti-inflammatory drugs, patient-controlled analgesia or epidural techniques will not significantly improve outcome after major procedures. In lower body procedures, however, intra- and early postoperative pain relief with epidural or spinal anaesthesia reduces blood loss and thromboembolic complications. It is hypothesized that effective postoperative pain relief may significantly improve outcome only if integrated into a multimodal rehabilitation program.

Analgesia, Epidural↗
PubMed1992

Further development and clinical application of the stereotactic operating microscope.

Implementation of a Vicom-VME image processing workstation for the frameless stereotactic operating microscope system has allowed an improved interpolation algorithm for more accurate reconstruction of three-dimensional data, the integration graphically of multimodality imaging information, an additional stereotactic graphics display outside of the microscope optics and optional three-dimensional displays through communication with a Convex mini-supercomputer. A precision-milled coupling for reproducible attachment of the spark gap bracket to the microscope has eliminated the need for that transformation calculation during each case. Clinical utility has been greatest in providing navigational guidance to small subcortical or deep lesions and in defining the extent of preoperatively planned resection of larger, infiltrating tumors. Mean accuracy in the past 17 cases has been 3.5-6.5 mm. The frameless methodology has also enabled extracranial stereotactic surgical procedures in 7 patients.

Brain Neoplasms↗
PubMed1994

Imaging techniques and computers.

Imaging technology has been the pacesetter of stereotactic technique since its introduction in clinical practice. Quite recently, the extraordinary quality of diagnostic neuroimages and the growing availability of computing power has widened the field of applications of stereotaxy suggesting, at the same time, substantial evolution of its instrumentation. Fusion of multimodal digital images, integration of morphological and functional data, and dimensional rendering techniques have become powerful 'navigational aids' for tissue sampling, functional procedures and image-guided endoscopic surgery. Radiosurgical dose planning systems integrated with image processing and computer graphics routines allow efficient interactive evaluation of tissue-dose volumes superimposition in brachytherapy and external beam focused irradiation. Volumetric guided open surgery, assisted by intraoperative acquisition of stereotactic echographic and microscopic images, allows satisfactory treatment of deep-seated cerebral lesions. Further improvement is to be expected with the implementation of the ongoing development of localizing solutions totally integrated with the microsurgical instrumentation.

Brain↗
PubMed2003

Photodynamic therapy in lung cancer. A review.

PDT utilizes photosensitizing agents that are selectively retained by tumors. These agents have high resulting tumor:tissue concentrations but are inactive by themselves. When activated by light, they generate free radicals, resulting in membrane injury, vascular injury, and immune-mediated injury with relatively selective cytotoxicity to tumor cells. Clinically, PDT can be used to treat CIS as well as more advanced lung cancers with endobronchial obstruction. PDT should be viewed as one tool of many that can be used to deal with airway problems in patients with lung cancer and it will often need to be used in conjunction with other techniques, such as airway stenting, Nd-YAG, or cryotherapy. For PDT to be effective, it must be integrated into a multimodality approach, including chemotherapy and radiation therapy.

Humans↗
PubMed2002

Role of neuroimaging in the management of seizure disorders.

Neuroimaging is one of the most important advances made in the past decade in the management of seizure disorders. Magnetic resonance imaging (MRI) has increased substantially the ability to detect causes of seizure disorders, to plan medical or surgical therapy, and to prognosticate the outcome of disorders and therapy. However, MRI must be performed with techniques that will maximize the detection of potentially epileptogenic lesions, especially in candidates for epilepsy surgery. Functional imaging has an established role in evaluating patients for epilepsy surgery. It is relied on when results from standard diagnostic methods, such as clinical information, electroencephalography, and MRI, are insufficient to localize the seizure focus. Also, functional imaging is a reportedly reliable alternative to invasive methods for identifying language, memory, and sensorimotor areas of the cerebral cortex. Despite the availability of multimodality imaging, the epileptogenic zone is not determined solely by a single imaging modality. Evidence and experience have shown that concordance of results from clinical, electrophysiologic, and neuroimaging studies is needed to identify the epileptogenic zone accurately. With modern techniques in image processing, multimodality imaging can integrate the location of abnormal electroencephalographic, structural, and functional imaging foci on a "map" of the patient's brain. Computer image-guided surgery allows surgically exact implantation of intracranial electrodes and resection of abnormal structural or functional imaging foci. These techniques decrease the risk of morbidity associated with epilepsy surgery and enhance the probability of postsurgical seizure control.

Adolescent↗
PubMed2000

Photodynamic therapy in lung cancer.

Photodynamic therapy (PDT) involves the use of photosensitizing agents that are selectively retained within tumor cells. The agents remain inactive until exposed to light of the proper wavelength. When activated by light, these compounds generate toxic oxygen radicals that result in tumor necrosis. In lung cancer, PDT can be used for both carcinoma in situ and for the treatment of unresectable disease with endobronchial obstruction. For patients with advanced disease, careful patient selection and integration of PDT with other interventional techniques are critical. Limited data suggest that PDT is comparable in efficacy to neodymium-yttrium-aluminum garnet (Nd-YAG) laser therapy, and some evidence indicates that it may be superior in terms of duration of response. For PDT to be used effectively, it should be integrated into a multimodality approach with chemotherapy and radiation. The optimal sequencing of these treatment modalities remains an area for further investigation.

Carcinoma in Situ↗
PubMed1991

Non-vestibular dizziness and static posturography.

In patients complaining of dizziness attributable neither to vestibular disorders nor to any neurological cause, static posturographic recordings can reveal signs consistent with the symptoms. These posturographic abnormalities are a sign, not of impairment of some other input of the fine-postural system, but of faulty integration of the multimodal sensory information that contributes to the control of orthostatic posture.

Dizziness↗
PubMed2026

Multimodal artificial intelligence and machine learning in oncology: from data integration to precision cancer care.

Cancer remains a major global health burden, with approximately 20 million new cases and 9.7 million cancer-related deaths reported globally in 2022. While advances in radiological imaging, molecular profiling, and clinical data have enhanced the interpretation of disease progression, the availability of multiple such modalities still does not meet the needs of a large patient population. This narrative review focuses on the role of multimodal artificial intelligence and machine learning in bridging the gap in interpreting heterogeneous modalities to improve risk prediction, prognostic assessment, and treatment decision-making in precision oncology. Multimodal frameworks such as Pathomic Fusion illustrate how complementary histopathological and genomic information can be integrated for cancer diagnosis and prognostic modeling. Multimodal models have demonstrated potential in virtual biopsy, cancer screening, prognostic prediction, radiotherapy planning, intraoperative guidance, and clinical-trial design using digital twins and synthetic control arms. The major limitations of incorporating multimodal artificial intelligence and machine learning in oncology include data heterogeneity, demographic or institutional biases, and reproducibility challenges that hinder translation. Accordingly, appropriate data-governance strategies, fairness audits, and privacy-preserving approaches such as federated learning should be considered where appropriate. Future progress will depend on the development of standardized benchmarking datasets, robust external validation, seamless integration with electronic health records and picture archiving and communication systems, and the implementation of explainable, secure, and clinically validated multimodal artificial intelligence frameworks that support precision oncology in routine clinical practice.

deep learning↗
PubMed2000

[Memory advantage of performed actions: comments on multimodal memory theory].

Based on the integration of the memory advantage for subject-performed actions into the multimodal theory of episodic memory by J. Engelkamp (1997), three issues referring to the so-called enactment effect are discussed and addressed by statistical r-analyses. Firstly, the empirical basis of the functional distinction between motor and non-motor memory resources by means of dual-task experiments is questioned. Secondly, a multinomial modeling analysis is presented which aims at the contributions of automatic and controlled memory processes to the enactment effect in the process-dissociation paradigm. Finally, the effect of enactment on memory for serial order information is discussed with respect to recent accounts of serial memory.

Attention↗
PubMed2026

Multimodal risk assessment for oral potentially malignant disorders: Integrating patient-centered and specimen-derived data.

BACKGROUND: Oral potentially malignant disorders exhibit heterogeneous malignant transformation risk that clinical approaches fail to adequately predict. Histopathologic dysplasia grading, the reference standard of risk assessment, is associated with poor interobserver reliability and limited prognostic discrimination. It is necessary to define other potential patient- and tissue-associated risk modifiers to improve patient-specific disease prediction. TYPES OF STUDIES REVIEWED: PubMed was queried for patient- and specimen-derived factors as they relate to oral cancer and oral potentially malignant disorders, with preference for systematic review and meta-analysis articles published within the past 5 years. When not available, guidelines from the American Cancer Society, National Cancer Institute, or other national organizations or the most recent best articles were referenced to support the data presented. RESULTS: Within patient-associated factors, validated measures of tobacco and alcohol exposure, clinical lesion characteristics, systemic health factors including metabolic syndrome components, comorbidity risk, and dental health indexes were found. Within specimen-derived data, tissue-based analyses encompassing histopathology and advanced molecular profiling (genomic, epigenomic, transcriptomic, spatial approaches), blood-based germline and somatic mutation analysis, and saliva-based microbiome characterization and inflammatory biomarker assessment were addressed. PRACTICAL IMPLICATIONS: Malignant transformation reflects intersecting patient and specimen risk pathways that affect each patient differently; no single modality captures this complexity. Realizing precision prognostication in oral precancer will require coordinated expansion and standardization of data collection across research groups. This review is intended to guide covariate selection for prospective study design, improve reproducibility, and ultimately enable the development of validated multimodal risk prediction tools for clinical deployment.

Humans↗
PubMed2006

Effects of fMRI-EEG mismatches in cortical current density estimation integrating fMRI and EEG: a simulation study.

OBJECTIVE: Multimodal functional neuroimaging by combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) has been studied to achieve high-resolution reconstruction of the spatiotemporal cortical current density (CCD) distribution. However, mismatches between these two imaging modalities may occur due to their different underlying mechanisms. The aim of the present study is to investigate the effects of different types of fMRI-EEG mismatches, including fMRI invisible sources, fMRI extra regions and fMRI displacement, on the fMRI-constrained cortical imaging in a computer simulation based on realistic-geometry boundary-element-method (BEM) model. METHODS: Two methods have been adopted to integrate the synthetic fMRI and EEG data for CCD imaging. In addition to the well-known 90% fMRI-constrained Wiener filter approach (Liu AK, Belliveau JW, Dale AM. PNAS 1998;95:8945-8950.), we propose a novel two-step algorithm (referred to as 'Twomey algorithm') for fMRI-EEG integration. In the first step, a 'hard' spatial prior derived from fMRI is imposed to solve the EEG inverse problem with a reduced source space; in the second step, the fMRI constraint is removed and the source estimate from the first step is re-entered as the initial guess of the desired solution into an EEG least squares fitting procedure with Twomey regularization. Twomey regularization is a modified Tikhonov technique that attempts to simultaneously minimize the distance between the desired solution and the initial estimate, and the residual errors of fitness to EEG data. The performance of the proposed Twomey algorithm has been evaluated both qualitatively and quantitatively along with the lead-field normalized minimum norm (WMN) and the 90% fMRI-weighted Wiener filter approach, under repeated and randomized source configurations. Point spread function (PSF) and localization error (LE) are used to measure the performance of different imaging approaches with or without a variety of fMRI-EEG mismatches. RESULTS: The results of the simulation show that the Twomey algorithm can successfully reduce the PSF of fMRI invisible sources compared to the Wiener estimation, without losing the merit of having much lower PSF of fMRI visible sources relative to the WMN solution. In addition, the existence of fMRI extra sources does not significantly affect the accuracy of the fMRI-EEG integrated CCD estimation for both the Wiener filter method and the proposed Twomey algorithm, while the Twomey algorithm may further reduce the chance of occurring spurious sources in the extra fMRI regions. The fMRI displacement away from the electrical source causes enlarged localization error in the imaging results of both the Twomey and Wiener approaches, while Twomey gives smaller LE than Wiener with the fMRI displacement ranging from 1-2 cm. With less than 2 cm fMRI displacement, the LEs for the Twomey and Wiener approaches are still smaller than in the WMN solution. CONCLUSIONS: The present study suggests that the presence of fMRI invisible sources is the most problematic factor responsible for the error of fMRI-EEG integrated imaging based on the Wiener filter approach, whereas this approach is relatively robust against the fMRI extra regions and small displacement between fMRI activation and electrical current sources. While maintaining the above advantages possessed by the Wiener filter approach, the Twomey algorithm can further effectively alleviate the underestimation of fMRI invisible sources, suppress fMRI spurious sources and improve the robustness against fMRI displacement. Therefore, the Twomey algorithm is expected to improve the reliability of multimodal cortical source imaging against fMRI-EEG mismatches. SIGNIFICANCE: The proposed method promises to provide a useful alternative for multimodal neuroimaging integrating fMRI and EEG.

Analysis of Variance↗