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BACKGROUND AND PURPOSE: The 3-dimensional cranial nerve imaging (CRANI) sequence may assist visualization of anatomical details of extraforaminal cranial nerves and aid in clinical diagnosis and preoperative planning. In this study, we investigated the feasibility of using a combined CRANI and magnetization-prepared rapid-acquisition gradient-echo (MPRAGE) imaging protocol to comprehensively identify trigeminal nerve projections. METHOD: We evaluated the detection of distal regions of three branches of the ophthalmic nerve (V1), three branches of the maxillary nerve (V2), and five branches of the mandibular nerve (V3) in seven healthy adult subjects, with and without contrast injection. Nerve branches were rated on a 5-point scale by three observers. Interobserver reliability was studied using weighted kappa statistics and percentage agreement. RESULTS: Among V1 and V2 branches, the frontal nerve and infraorbital nerve were most successfully identified (average rating of 3.9, agreement >80%) in precontrast MPRAGE images. In V3 branches, lingual and inferior alveolar nerves were most successfully identified (average rating of 3.9, agreement >80%) in precontrast CRANI images, with an excellent average rating. In all cases except one, interobserver reliability was rated good to excellent. The buccal nerve was the only branch with a low average interobserver rating. Gadolinium contrast did not improve nerve segment visualization in our study. This may relate to the specific anatomic regions assessed, gadolinium dose, postcontrast image timing, and lack of pathology. CONCLUSION: A combined CRANI and MPRAGE protocol can be combined to visualize distal branches of V1, V2, and V3 and has potential for clinical use.

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In recent years, deep learning (DL) has emerged as a powerful tool in clinical imaging, offering unprecedented opportunities for the diagnosis and treatment of neurological disorders (NDs). This comprehensive review explores the multifaceted role of DL techniques in leveraging vast datasets to advance our understanding of NDs and improve clinical outcomes. Beginning with a systematic literature review, we delve into the utilization of DL, particularly focusing on multimodal neuroimaging data analysis-a domain that has witnessed rapid progress and garnered significant scientific interest. Our study categorizes and critically analyses numerous DL models, including Convolutional Neural Networks (CNNs), LSTM-CNN, GAN, and VGG, to understand their performance across different types of Neurology Diseases. Through particular analysis, we identify key benchmarks and datasets utilized in training and testing DL models, shedding light on the challenges and opportunities in clinical neuroimaging research. Moreover, we discuss the effectiveness of DL in real-world clinical scenarios, emphasizing its potential to revolutionize ND diagnosis and therapy. By synthesizing existing literature and describing future directions, this review not only provides insights into the current state of DL applications in ND analysis but also covers the way for the development of more efficient and accessible DL techniques. Finally, our findings underscore the transformative impact of DL in reshaping the landscape of clinical neuroimaging, offering hope for enhanced patient care and groundbreaking discoveries in the field of neurology. This review paper is beneficial for neuropathologists and new researchers in this field.

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PURPOSE: Standardized reporting of treatment response in oncology patients has traditionally relied on methods like RECIST, PERCIST and Deauville score. These endpoints assess only a few lesions, potentially overlooking the response heterogeneity of all disease. This study hypothesizes that comprehensive spatial-temporal evaluation of all individual lesions is necessary for superior prognostication of clinical outcome. METHODS: [18F]FDG PET/CT scans from 241 patients (127 diffuse large B-cell lymphoma (DLBCL) and 114 non-small cell lung cancer (NSCLC)) were retrospectively obtained at baseline and either during chemotherapy or post-chemoradiotherapy. An automated TRAQinform IQ software (AIQ Solutions) analyzed the images, performing quantification of change in regions of interest suspicious of cancer (lesion-ROI). Multivariable Cox proportional hazards (CoxPH) models were trained to predict overall survival (OS) with varied sets of quantitative features and lesion-ROI, compared by bootstrapping with C-index and t-tests. The best-fit model was compared to automated versions of previously established methods like RECIST, PERCIST and Deauville score. RESULTS: Multivariable CoxPH models demonstrated superior prognostic power when trained with features quantifying response heterogeneity in all individual lesion-ROI in DLBCL (C-index = 0.84, p < 0.001) and NSCLC (C-index = 0.71, p < 0.001). Prognostic power significantly deteriorated (p < 0.001) when using subsets of lesion-ROI (C-index = 0.78 and 0.67 for DLBCL and NSCLC, respectively) or excluding response heterogeneity (C-index = 0.67 and 0.70). RECIST, PERCIST, and Deauville score could not significantly associate with OS (C-index < 0.65 and p > 0.1), performing significantly worse than the multivariable models (p < 0.001). CONCLUSIONS: Quantitative evaluation of response heterogeneity of all individual lesions is necessary for the superior prognostication of clinical outcome.

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Ischemic stroke poses a significant global health challenge, necessitating ongoing exploration of its pathophysiology and treatment strategies. This comprehensive review integrates various aspects of ischemic stroke research, emphasizing crucial mechanisms, therapeutic approaches, and the role of clinical imaging in disease management. It discusses the multifaceted role of Netrin-1, highlighting its potential in promoting neurovascular repair and mitigating post-stroke neurological decline. It also examines the impact of blood-brain barrier permeability on stroke outcomes and explores alternative therapeutic targets such as statins and sphingosine-1-phosphate signaling. Neurocardiology investigations underscore the contribution of cardiac factors to post-stroke mortality, emphasizing the importance of understanding the brain-heart axis for targeted interventions. Additionally, the review advocates for early reperfusion and neuroprotective agents to counter-time-dependent excitotoxicity and inflammation, aiming to preserve tissue viability. Advanced imaging techniques, including DWI, PI, and MR angiography, are discussed for their role in evaluating ischemic penumbra evolution and guiding therapeutic decisions. By integrating molecular insights with imaging modalities, this interdisciplinary approach enhances our understanding of ischemic stroke and offers promising avenues for future research and clinical interventions to improve patient outcomes.

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Heart failure with preserved ejection fraction (HFpEF) is an important, emerging risk factor for dementia, but it is not clear whether HFpEF contributes to a specific pattern of neuroanatomical changes in dementia. A major challenge to studying this is the relative paucity of datasets of patients with dementia, with/without HFpEF, and relevant neuroimaging. We sought to demonstrate the feasibility of using modern data mining tools to create and analyze clinical imaging datasets and identify the neuroanatomical signature of HFpEF-associated dementia. We leveraged the bioinformatics tools at Vanderbilt University Medical Center to identify patients with a diagnosis of dementia with and without comorbid HFpEF using the electronic health record. We identified high resolution, clinically-acquired neuroimaging data on 30 dementia patients with HFpEF (age 76.9 ± 8.12 years, 61% female) as well as 301 age- and sex-matched patients with dementia but without HFpEF to serve as comparators (age 76.2 ± 8.52 years, 60% female). We used automated image processing pipelines to parcellate the brain into 132 structures and quantify their volume. We found six regions with significant atrophy associated with HFpEF: accumbens area, amygdala, posterior insula, anterior orbital gyrus, angular gyrus, and cerebellar white matter. There were no regions with atrophy inversely associated with HFpEF. Patients with dementia and HFpEF have a distinct neuroimaging signature compared to patients with dementia only. Five of the six regions identified in are in the temporo-parietal region of the brain. Future studies should investigate mechanisms of injury associated with cerebrovascular disease leading to subsequent brain atrophy.

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INTRODUCTION: Understanding the complex nature of low back pain (LBP) is crucial for effective management. The PainDETECT questionnaire is a tool that distinguishes between neuropathic (NeP), nociceptive (NoP), and ambiguous pain. This study aimed to investigate the relationship between pain classification and lumbar intervertebral degenerative parameters obtained from imaging. METHODS: A cohort study was conducted involving 279 patients, aged 18 years and above, who completed PainDETECT questionnaires and underwent lumbar MRI and/or X-ray scans. RESULTS: The study included 102 patients with NoP, 78 with ambiguous pain, and 99 with NeP. The NeP group had lower mean age (58.21 vs. 53.63, p < 0.05) and higher mean numerical rating scale score (7.9 vs. 5.9, p < 0.001) compared to the NoP group. A negative correlation was found between PainDETECT scores and pelvic incidence (τ = - 0.177, p = 0.043). The NeP group exhibited significantly higher severity of foraminal stenosis (U = 18.962, p = 0.002), spinal stenosis (U = 14.481, p = 0.005), and Pfirrmann grade (U = 14.221, p = 0.028) compared to the NoP group. A higher proportion of NeP patients had intervertebral disk bulge (96% vs. 78% vs. 78%, p = 0.002) and high-intensity zones (51% vs. 41% vs. 19%, p < 0.001) compared to those with NoP and ambiguous pain. CONCLUSION: NeP, as determined by the PainDETECT questionnaire, is associated with more severe neural compression, increased presence of discogenic disease and inflammatory disk severity, and decreased pelvic incidence. This pioneering study establishes a connection between pathological findings and pain categorization, providing clinicians with valuable guidance for formulating tailored management plans and reducing the need for unnecessary pharmacotherapy, imaging, and non-targeted surgical interventions.

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OBJECTIVE: Rapid On-Site Evaluation (ROSE) of fine needle aspirations (FNA) is widely accepted as best practice, resulting in better outcomes and delivery of care for patients. However, it is not always practical for cytology laboratories to release staff. To increase the availability of ROSE, this study aimed to robustly test the effectiveness of Telecytology ROSE (TCROSE) utilising a clinical imaging assistant (CIA) to prepare the samples and operate the microscope. METHODS: The study was divided into 3 phases. Phase 1, equipment testing, validation and in-house training for the CIA and the Consultant Biomedical Scientist (CBMS) performing TCROSE. Phase 2, Verifying TCROSE on the same site as the cytology laboratory and phase 3, TCROSE utilising a clinic at a peripheral site away from the cytology laboratory. RESULTS: 78/80 (97% sensitivity, 95% accuracy) of TCROSE cases matched the final report for assessment of adequacy and sufficient sampling, demonstrating 94% reliability with a 95% confidence value. An appropriately trained CIA effectively prepared the samples and operated the microscope for remote interpretation. The samples were triaged effectively, and biopsy requests were appropriate to reduce the need for repeat procedures and delays in treatment. This approach received positive feedback from patients. CONCLUSION: TCROSE utilising a CIA provides a highly effective alternative to conventional ROSE, minimising the resources required from cytopathology services and improving patient care and access to best practice. This study supports the validity of trained CIAs for a more involved role in the ultrasound-guided FNA service.

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Focal cortical dysplasia (FCD) is a cortical malformation in brain development and is considered as one of the major causes of drug-resistant epilepsiesin children and adults. The pathogenesis of FCD is yet to be fully understood. Imaging markers such as MRI are currently the surgeons major obstacle due to the difficulty in delimiting the precise dysplasic area and a mosaic brain where there is epileptogenic tissue invisible to MRI. Also increased gene expression and activity may be responsible for the alterations in cell proliferation, migration, growth, and survival. Altered expressions were found, particularly in the PI3K/AKT/mTOR pathway. Surgery is still considered the most effective treatment option, due to drug-resistance, and up to 60 % of patients experience complete seizure control, varying according to the type and location of FCD. Both genetic and epigenetic factors may be involved in the pathogenesis of FCD, and there is no conclusive evidence whether these alterations are inherited or have an environmental origin.

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Introducción: Durante el proceso docente educativo en la asignatura de Cirugía, los estudiantes necesitan apoyarse en estudios imagenológicos y correlacionarlos con su planteamiento clínico para arribar a un diagnóstico certero. Sobre esta base proponen un tratamiento óptimo a pacientes con afecciones quirúrgicas, por lo cual requieren un adecuado desarrollo de esta habilidad. El avance de las tecnologías de la información y las comunicaciones, y las condiciones en las universidades de ciencias médicas, permiten su utilización como recurso del aprendizaje, en especial una de sus herramientas: la multimedia educativa. Objetivo: Diseñar una multimedia que permita el desarrollo de la correlación clínico-imagenológica en los estudiantes de la asignatura Cirugía. Métodos: Se realizó una investigación educativa de desarrollo tecnológico. En su diseño se utilizaron métodos teóricos: el histórico-lógico, el análisis documental, el enfoque sistémico estructural y el inductivo-deductivo; y empíricos: encuestas, entrevistas, observación, consulta a expertos y triangulación metodológica. Resultados: Se obtuvo una lista de dificultades y de potencialidades, que permitieron construir el contenido de una multimedia, cuyo diseño de carácter marxista-leninista contiene un enfoque pedagógico constructivista, flexible y abierto, con el fin de propiciar la autonomía, la colaboración, el estudio independiente y la innovación virtual. Conclusiones: Se identificaron necesidades de aprendizaje para una adecuada correlación clínico-imagenológica. Las habilidades fundamentales a desarrollar fueron la descripción del estudio imagenológico y la correlación clínica. Se encontró como necesario y pertinente el diseño de una multimedia para contribuir al desarrollo de dicha habilidad. Se diseñó la multimedia y se validó por expertos.

Introduction: During the teaching-educational process in the subject Surgery, students need to rely on imaging studies and correlate them with their clinical approach to arrive at an accurate diagnosis. On this basis, they propose an optimal treatment to patients with surgical conditions, a reason why they require an adequate development of this skill. The advance of information and communication technologies, as well as the conditions in the universities of medical sciences, allow their usage as learning resources; especially one of their tools: educational multimedia. Objective: To design a multimedia that allows the development of the clinical-imaging correlation in students of the subject Surgery. Methods: An educational research of technological development was carried out. Theoretical methods were used in its design (the historical-logical method, documentary analysis, the structural-systemic approach, and the inductive-deductive method), as well as empirical methods (surveys, interviews, observation, expert consultation, and methodological triangulation). Results: A list of difficulties and potentialities was obtained, which allowed building the content for a multimedia, whose Marxist-Leninist character design contains a constructivist, flexible and open pedagogical approach, in order to promote autonomy, collaboration, independent study and virtual innovation. Conclusions: Learning needs were identified for an adequate clinical-imaging correlation. The fundamental skills to be developed were description of the imaging study and clinical correlation. The design of a multimedia to contribute to the development of these skills was found to be necessary and pertinent. The multimedia was designed and validated by experts.

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The amygdala was highlighted as an early site for neurofibrillary tau tangle pathology in Alzheimer's disease in the seminal 1991 article by Braak and Braak. This knowledge has, however, only received traction recently with advances in imaging and image analysis techniques. Here, we provide a cross-disciplinary overview of pathology and neuroimaging studies on the amygdala. These studies provide strong support for an early role of the amygdala in Alzheimer's disease and the utility of imaging biomarkers of the amygdala in detecting early changes and predicting decline in cognitive functions and neuropsychiatric symptoms in early stages. We summarize the animal literature on connectivity of the amygdala, demonstrating that amygdala nuclei that show the earliest and strongest accumulation of neurofibrillary tangle pathology are those that are connected to brain regions that also show early neurofibrillary tangle accumulation. Additionally, we propose an alternative pathway of neurofibrillary tangle spreading within the medial temporal lobe between the amygdala and the anterior hippocampus. The proposed existence of this pathway is strengthened by novel experimental data on human functional connectivity. Finally, we summarize the functional roles of the amygdala, highlighting the correspondence between neurofibrillary tangle accumulation and symptomatic profiles in Alzheimer's disease. In summary, these findings provide a new impetus for studying the amygdala in Alzheimer's disease and a unique perspective to guide further study on neurofibrillary tangle spreading and the occurrence of neuropsychiatric symptoms in Alzheimer's disease.

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Myxoid soft tissue tumors are an unusually diverse group of neoplasms, most commonly involving the extremities. They are mesenchymal neoplasms characterized by the abundant production of myxoid matrix with a gelatinous appearance. They have varying characteristics in medical imaging and histopathology. The prognosis is variable for recurrence. Less regularly, they are found in bone, skin, the genitourinary tract, aponeurotic tissue, and subcutaneous tissue. We present a case of myxomatous tumor at the scapulothoracic region mimicking bursitis.

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Cadaveric anatomy is frequently described as the gold standard for anatomy education. Increasingly and especially following the COVID-19 pandemic, there is acceptance that a blended approach for anatomy curriculum delivery is optimal for learners.Setting up a new UK Medical School in 2019 necessitated building a new cadaveric anatomy facility. To enable anatomy curriculum delivery during the construction period (2019-2021), a technology-enhanced learning (TEL) anatomy curriculum was developed, as well as an anatomy laboratory suitable for TEL. Development of a TEL anatomy curriculum with the later inclusion of cadaveric anatomy is unusual since the typical model is to supplement cadaveric anatomy with TEL approaches.TEL solutions that provide digital visualisation of anatomy may support learners by reducing cognitive load. Examples include using colour and/or translucency features to highlight and signpost pertinent anatomy and constructing virtual anatomical models in real time, rather than dissection. Radiology and portable ultrasound provide clinically contextualised visualisations of anatomy; the latter offers a haptic learning experience too. A TEL anatomy laboratory can provide interactive learning experiences for engagement and outreach activities for young school children, where cadaveric anatomy is not suitable.

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RESUMEN Los estudios radiológicos son fundamentales en el diagnóstico y tratamiento de diversas patologías. Su calidad depende de múltiples variables, entre las que destacan, los parámetros de adquisición, interpretación, entre otros. Se propone una metodología estandarizada, sencilla, de fácil interpretación, permitiendo la evaluación regular de la calidad de las imágenes, dando indicios de la propiedad del trabajo en el centro de salud y poder realizar comparaciones entre centros y autores, a partir de los criterios anatómicos establecidos por la Unión Europea, definiendo el parámetro de calidad de la imagen (CI), representadas en una escala de Likert para el análisis de frecuencia, demostrando que puede ser una herramienta de utilidad para la evaluación reiterada de los centros de radiología. Evaluando 140 proyecciones postero anterior y 85 laterales de tórax, con una muestra de 225 estudios, realizados en un centro de salud, ubicado en la ciudad de Mérida, República Bolivariana de Venezuela, escogiendo estas proyecciones, ya que, representan el 32% de los estudios de radiología convencional. Permitiendo la comparación entre proyecciones y autores, obteniéndose para la proyección postero anterior un CI de 5,07 ± 1,53 criterios de los ocho establecidos, normalizado un CI de 0,62 ± 0,19; las imágenes excelentes solo representan el 22,78%. Comparado con un CI de 4,91 ± 1,17 criterios de los seis establecidos, normalizado un CI de 0,82 ± 0,19, e imágenes excelentes en un 64,71% para la proyección lateral. Se observa las notorias diferencias entre la calidad de las imágenes clínicas en hombres y mujeres para ambas proyecciones

ABSTRACT Radiological studies are essential in the diagnosis and treatment of various pathologies. Their quality depends on multiple variables, among which the acquisition and interpretation parameters, among others, stand out. A standardized methodology is proposed, simple, of easy interpretation, allowing the regular evaluation of the quality of the images, giving indications of the property of the work in the health center and being able to make comparisons between centers and authors, from the anatomical criteria established by the European Union, defining the parameter of image quality (IQ), represented on a Likert scale for frequency analysis, demonstrating that it can be a useful tool for the repeated evaluation of radiology centers. Evaluating 140 postero anterior and 85 lateral projections of the thorax, with a sample of 225 studies, performed in a health center, located in the city of Merida, Bolivarian Republic of Venezuela, taking these projections, since they represent 32% of the conventional radiology studies. Allowing the comparison between projections and authors, obtaining for the postero anterior projection an IQ of 5.07 ± 1.53 criteria of the eight established, normalized an IQ of 0.62 ± 0.19; the excellent images only represent 22.78%. Compared with an IQ of 4.91 ± 1.17 criteria of the six established, normalized IQ of 0.82 ± 0.19, and excellent images in 64.71% for the lateral projection. It is observed the notorious differences between the quality of clinical images in men and women for both projections

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Anterior inferior cerebellar artery (AICA) occlusion is a subtype of posterior circulation stroke. Confirmation of its angiomorphology and etiology is challenging because of the complex mechanisms underlying small-artery thrombogenesis. In addition to conventional factors, physicians frequently overlook hemorheological changes. In this case report, we describe right AICA occlusion in a 50-year-old man. He presented with an unsteady walk, tinnitus, dizziness, and left-sided peripheral facial palsy observed over 36 hours, accompanied by increased blood viscosity on hemorheological evaluation. Magnetic resonance imaging revealed acute infarction in the left cerebellar hemisphere and middle cerebellar peduncles. Magnetic resonance angiography (MRA) and computed tomographic angiography (CTA) failed to detect AICA occlusion, which was later confirmed using digital subtraction angiography. Repeat routine blood examinations showed elevated erythrocyte and leukocyte counts and serum hemoglobin concentrations that persisted over many days. Hemorheological evaluation revealed increased whole blood viscosity at a low shear rate. AICA occlusion should thus be diagnosed based on its initial characteristic manifestations; notably, MRA and CTA may fail to detect arterial occlusion. The importance of hemorheological change as a factor of stroke is frequently neglected. We therefore report this case hoping to emphasize its relevance, especially in small-artery occlusion.

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Background: Getting the most value from expert clinicians' limited labelling time is a major challenge for artificial intelligence (AI) development in clinical imaging. We present a novel method for ground-truth labelling of cardiac magnetic resonance imaging (CMR) image data by leveraging multiple clinician experts ranking multiple images on a single ordinal axis, rather than manual labelling of one image at a time. We apply this strategy to train a deep learning (DL) model to classify the anatomical position of CMR images. This allows the automated removal of slices that do not contain the left ventricular (LV) myocardium. Methods: Anonymised LV short-axis slices from 300 random scans (3,552 individual images) were extracted. Each image's anatomical position relative to the LV was labelled using two different strategies performed for 5 hours each: (I) 'one-image-at-a-time': each image labelled according to its position: 'too basal', 'LV', or 'too apical' individually by one of three experts; and (II) 'multiple-image-ranking': three independent experts ordered slices according to their relative position from 'most-basal' to 'most apical' in batches of eight until each image had been viewed at least 3 times. Two convolutional neural networks were trained for a three-way classification task (each model using data from one labelling strategy). The models' performance was evaluated by accuracy, F1-score, and area under the receiver operating characteristics curve (ROC AUC). Results: After excluding images with artefact, 3,323 images were labelled by both strategies. The model trained using labels from the 'multiple-image-ranking strategy' performed better than the model using the 'one-image-at-a-time' labelling strategy (accuracy 86% vs. 72%, P=0.02; F1-score 0.86 vs. 0.75; ROC AUC 0.95 vs. 0.86). For expert clinicians performing this task manually the intra-observer variability was low (Cohen's κ=0.90), but the inter-observer variability was higher (Cohen's κ=0.77). Conclusions: We present proof of concept that, given the same clinician labelling effort, comparing multiple images side-by-side using a 'multiple-image-ranking' strategy achieves ground truth labels for DL more accurately than by classifying images individually. We demonstrate a potential clinical application: the automatic removal of unrequired CMR images. This leads to increased efficiency by focussing human and machine attention on images which are needed to answer clinical questions.

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Photodynamic therapy (PDT) and sonodynamic therapy (SDT) are non-invasive treatment methods with obvious inhibitory effect on tumors and have few side effects, which have been widely concerned and explored by researchers. Sensitizer is the main factor in determining the therapeutic effect of PDT and SDT. Porphyrins, a group of organic compounds widespread in nature, can be activated by light or ultrasound and produce reactive oxygen species. Therefore, porphyrins as sensitizers in PDT have been widely explored and investigated for many years. Herein, we summarize the classical porphyrin compounds and their applications and mechanisms in PDT and SDT. The application of porphyrin in clinical diagnosis and imaging is also discussed. In conclusion, porphyrins have good application prospects in disease treatment as an important part of PDT or SDT, and in clinical diagnosis and imaging.

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Genetically engineered mouse models (GEMMs) and patient-derived xenograft mouse models (PDXs) can recapitulate important biological features of cancer. They are often part of precision medicine studies in a co-clinical setting, in which therapeutic investigations are conducted in patients and in parallel (or sequentially) in cohorts of GEMMs or PDXs. Employing radiology-based quantitative imaging in these studies allows in vivo assessment of disease response in real time, providing an important opportunity to bridge precision medicine from the bench to the bedside. The Co-Clinical Imaging Research Resource Program (CIRP) of the National Cancer Institute focuses on the optimization of quantitative imaging methods to improve co-clinical trials. The CIRP supports 10 different co-clinical trial projects, spanning diverse tumor types, therapeutic interventions, and imaging modalities. Each CIRP project is tasked to deliver a unique web resource to support the cancer community with the necessary methods and tools to conduct co-clinical quantitative imaging studies. This review provides an update of the CIRP web resources, network consensus, technology advances, and a perspective on the future of the CIRP. The presentations in this special issue of Tomography were contributed by the CIRP working groups, teams, and associate members.

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Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute's (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard.

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