Advanced Imaging Modalities Research Articles

Small size, big problems: insights and difficulties in prenatal diagnosis of fetal microcephaly.

Microcephaly is a sign, not a diagnosis. Its incidence varies widely due to the differences in the definition and the population being studied. It is strongly related to neurodevelopmental disorders. Differences in definitions and measurement techniques between fetuses and newborns pose a great challenge for the diagnosis and prognostication of fetal microcephaly. A false positive diagnosis can result (in countries where it is legal) in erroneous termination of pregnancy, where a false negative diagnosis might lead to the birth of a microcephalic newborn. Microcephaly in growth restricted fetuses deserves special attention and separate evaluation as it is an important prognostic factor, and not necessarily part of the general growth retardation. Several genetic syndromes incorporating microcephaly and intrauterine growth retardation (IUGR) are discussed. Deceleration of the head circumference (HC) growth rate even when the HC is still within normal limits might be the only clue for developing microcephaly and should be considered during fetal head growth follow up. Combining additional parameters such as a positive family history, associated anomalies, and new measurement parameters can improve prediction in about 50% of cases, and thus should be part of the prenatal workup. Advances in imaging modalities and in prenatal genetic investigation along with the emergence of new growth charts can also improve diagnostic accuracy. In this article, we review the different definitions and etiologies of fetal microcephaly, discuss difficulties in diagnosis, investigate the reasons for the low yield of prenatal diagnosis, and provide improvement suggestions. Finally, we suggest an updated algorithm that will aid in the diagnosis and management of fetal microcephaly.

Misidentification of the True Aortic Annulus With 2-dimensional Echocardiography: A Critical Appraisal Using 3-Dimensional Imaging

ObjectivesThis study aimed to evaluate the accuracy of identifying the 'true aortic valve (AV) annulus' using 2-dimensional (2D) echocardiography with the aim of highlighting potential misidentification issues in clinical practice. DesignAn observational study employing 3-dimensional (3D) datasets to generate 2D images of the AV annulus for analysis. SettingThe study was conducted in an academic medical center. ParticipantsThree-dimensional transesophageal echocardiography (3D TEE) datasets were obtained from 11 patients with normal AV and aortic root anatomies, undergoing coronary artery bypass surgery. Attending anaesthesiologists certified by the national board of echocardiography (NBE) were subsequently approached to participate in this study. InterventionsTwo images per patient were generated from 3D datasets, reflecting the mid-esophageal long-axis view of the AV: a 'True AV Annulus Image' and an 'Off-Axis Image'. A survey was distributed to NBE certified perioperative echocardiographers across 12 academic institutions to identify the 'true AV annulus' from these images. Measurements and Main ResultsThe survey, completed by 45 qualified respondents, revealed a significant misidentification rate of the 'true AV annulus', with only 36.8% of responses correctly identifying it. The rate of correct identification varied across image sets, with 44.4% of participants unable to correctly identify any 'true AV annulus' image. ConclusionsThe study highlights the limitations of 2D echocardiography in accurately identifying the 'true AV annulus' in complex 3D structures like the aortic root. The findings suggest a need for greater reliance on advanced imaging modalities, such as 3D echocardiography, to improve accuracy in clinical practice.

SPINAL ANATOMY AND BEYOND: INVESTIGATING DEGENERATIVE DISC DISEASE

Degenerative disc disease is a common manifestation in routine spine imaging; this finding is partly attributable to physiological aging and partly to a pathological condition, and sometimes, this distinction is simply not clear. The study's main objective is to find the spinal anatomy and investigate degenerative disc disease in spinal patients. This mixed-methods study was conducted in a public hospital in Karachi, Pakistan from March 2023 to September 2023. Fifty patients diagnosed with DDD are enrolled, with comprehensive clinical assessments conducted to evaluate symptomatology, functional impairment, and radiological findings. Additionally, advanced imaging modalities, including MRI and CT scans, elucidate structural changes within the spinal column. Preliminary analysis reveals a mean disc height loss of 3.2 mm (±0.8) across the study cohort, with significant variability observed among individual patients. Annular tears are prevalent in 70% of cases, predominantly localized to the lumbar spine. Furthermore, facet joint degeneration is evident in 85% of patients, with a mean grade of 2.4 (±0.6) on the Pfirrmann scale. Correlation analysis demonstrates a moderate positive correlation (r = 0.56, p < 0.001) between disc height loss and severity of clinical symptoms. It is concluded that this study provides the complex pathology of degenerative disc disease (DDD) and its impact on spinal anatomy. Through a comprehensive investigation involving clinical assessments and advanced imaging techniques, we have elucidated the spectrum of degenerative changes within the intervertebral discs and facet joints.

Directional TV algorithm for fast EPR imaging

Precise radiation guided by oxygen images has demonstrated superiority over the traditional radiation methods. Electron paramagnetic resonance (EPR) imaging has proven to be the most advanced oxygen imaging modality. However, the main drawback of EPR imaging is the long scan time. For each projection, we usually need to collect the projection many times and then average them to achieve high signal-to-noise ratio (SNR). One approach to fast scan is to reduce the repeating time for each projection. While the projections would be noisy and thus the traditional commonly-use filtered backprojection (FBP) algorithm would not be capable of accurately reconstructing images. Optimization-based iterative algorithms may accurately reconstruct images from noisy projections for they may incorporate prior information into optimization models. Based on the total variation (TV) algorithms for EPR imaging, in this work, we propose a directional TV (DTV) algorithm to further improve the reconstruction accuracy. We construct the DTV constrained, data divergence minimization (DTVcDM) model, derive its Chambolle–Pock (CP) solving algorithm, validate the correctness of the whole algorithm, and perform evaluations via simulated and real data. The experimental results show that the DTV algorithm outperforms the existing TV and FBP algorithms in fast EPR imaging. Compared to the standard FBP algorithm, the proposed algorithm may achieve 10 times of acceleration.

Advancements in keratoplasty: Exploring newer techniques and imaging modalities for enhanced surgical outcomes

Abstract: Keratoplasty, the transplantation of corneal tissue, is a well-established surgical procedure for the treatment of various corneal diseases. Over the years, advancements in keratoplasty techniques have significantly improved surgical outcomes and patient satisfaction. This review article provides an overview of newer techniques and imaging modalities in keratoplasty that have emerged as promising options for corneal transplantation. The article begins with a brief overview of traditional keratoplasty techniques, including penetrating keratoplasty, deep anterior lamellar keratoplasty, Descemet’s stripping automated endothelial keratoplasty (EK), and Descemet’s membrane EK. It then delves into the discussion of newer techniques, including femtosecond laser-assisted keratoplasty, Bowman layer transplantation, and the role of anterior segment optical coherence tomography in keratoplasty. This review article aims to provide ophthalmologists with a comprehensive understanding of the newer techniques in keratoplasty, their advantages, limitations, and clinical outcomes. It emphasizes the importance of individualized treatment planning, considering patient-specific factors, and utilizing advanced imaging modalities to optimize surgical outcomes. The incorporation of newer techniques and imaging modalities in keratoplasty has the potential to revolutionize the field, offering improved visual outcomes, reduced complications, and enhanced patient satisfaction. Continued research and technological advancements will further refine these techniques, paving the way for the future of keratoplasty and improving the quality of life for patients with corneal diseases. We evaluate the currently available literature in this article to provide a comprehensive overview of contemporary surgical and imaging methods in ophthalmology to facilitate additional developments in the field of corneal transplantation.

New perspectives on advances in diagnosis through imaging in chronic respiratory diseases: a systematic literature review

Background: Chronic respiratory diseases, such as asthma, chronic obstructive pulmonary disease (COPD), interstitial lung disease, and cystic fibrosis, present substantial global health challenges. This systematic review explores recent advances in imaging-based diagnostic methods for these conditions, emphasizing high-resolution computed tomography (HRCT), magnetic resonance imaging (MRI), positron emission tomography (PET), and artificial intelligence (AI). Methodology: A systematic search of databases identified studies published in the last five years, focusing on innovative imaging techniques for chronic respiratory diseases. Inclusion criteria emphasized diagnostic accuracy and advancements in imaging modalities. Results: Seven studies were included, covering interventions in intensive care, mesenchymal stem cell therapy for COVID-19-induced acute respiratory distress syndrome (ARDS), endovascular treatment for aortic arch aneurysms, and lung cancer screening. MSC therapy demonstrated positive outcomes in ARDS patients, while endovascular repair showed technical success. LungSEARCH highlighted the effectiveness of lung cancer screening in high-risk populations. Discussion: Recent imaging technologies, including HRCT, MRI, PET, and AI, have revolutionized chronic respiratory disease diagnosis. The review emphasizes their clinical applications, impact on patient outcomes, and potential for personalized medicine. AI enhances image analysis accuracy, yet challenges like cost and interpretation discrepancies persist. Conclusion: Imaging technologies, particularly HRCT, MRI, PET, and AI, show promise in improving diagnostic accuracy and personalized treatment for chronic respiratory diseases. Collaboration among healthcare professionals, researchers, and industry stakeholders is crucial for addressing challenges and ensuring widespread access to advanced diagnostic tools. Future directions involve refining imaging methods for routine clinical integration, advancing patient care, and reducing the burden of respiratory diseases.

European Association of Cardiovascular Imaging survey on the evaluation of mitral regurgitation.

To evaluate the diagnosis and imaging of patients with mitral regurgitation (MR) and the management in routine clinical practice across Europe, the European Association of Cardiovascular Imaging Scientific Initiatives Committee performed a survey across European centres. In particular, the routine use of echocardiography, advanced imaging modalities, heart valve clinics, and heart valve teams was explored. A total of 61 responders, mainly from tertiary centres or university hospitals, from 26 different countries responded to the survey, which consisted of 22 questions. For most questions related to echocardiography and advanced imaging, the answers were relatively homogeneous and demonstrated good adherence to current recommendations. In particular, the centres used a multi-parametric echocardiographic approach and selected the effective regurgitant orifice and vena contracta width as their preferred assessments. 2D measurements are still the most widely used parameters to assess left ventricular structure; however, the majority use 3D trans-oesophageal echocardiography (TOE) to evaluate valve morphology in severe MR. The majority of centres reported the onsite availability and clinical use of ergometric stress echocardiography, cardiac computed tomography (CCT), and cardiac magnetic resonance (CMR) imaging. Heart valve clinics and heart valve teams were also widely prevalent. Consistent with current guidelines, echocardiography (transthoracic echocardiography and TOE) remains the first-line and central imaging modality for the assessment of MR although the complementary use of 3D TOE, CCT, and CMR appears to be growing. Heart valve clinics and heart valve teams are now widely prevalent.

Cistoadenoma mucinoso gigante de ovario

Although ovarian mucinous cystadenoma has a benign growth, it can grow to be very large. We present the case of a 70-year-old patient who came to the clinic for recurrent and diffuse abdominal pain. On physical examination, a large mass was palpated that occupied the entire abdominal cavity, up to the xiphoid appendix, rounded, retentive, with defined edges, non- painful, non-movable. Presence of edema in lower limbs. During the surgical act, a myomatous uterus and a giant left ovarian cyst measuring approximately 40 x3 0 cm and weighing 13.6 kg were identified. Total abdominal hysterectomy and bilateral salpingo-oophorectomy were performed. The biopsy confirmed the diagnosis of benign ovarian mucinous cystadenoma and uterine leiomyomatosis. The postoperative period progressed favorably. The incidence of giant ovarian cystadenoma is relatively unknown due to the lack of a standardized concept and currently available advanced imaging modalities. Keywords: Ovary, Ovarian cysts, Mucinous cystadenoma, Ovarian neoplasms.

Counting cells in motion by quantitative real-time magnetic particle imaging

Magnetic Particle Imaging (MPI) is an advanced and powerful imaging modality for visualization and quantitative real-time detection of magnetic nanoparticles (MNPs). This opens the possibility of tracking cells in vivo once they have been loaded by MNPs. Imaging modalities such as optical imaging, X-ray computed tomography (CT), positron emission tomography (PET), single photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI) face limitations, from depth of penetration and radiation exposure to resolution and quantification accuracy. MPI addresses these challenges, enabling radiation-free tracking of MNP-loaded cells with precise quantification. However, the real-time tracking of MNP-loaded cells with MPI has not been demonstrated yet. This study establishes real-time quantitative tracking of MNP-loaded cells. Therefore, THP-1 monocytes were loaded with three different MNP systems, including the MPI gold standard Resovist and Synomag. The real-time MPI experiments reveal different MPI resolution behaviors of the three MNP systems after cellular uptake. Real-time quantitative imaging was achieved by time-resolved cell number determination and comparison with the number of inserted cells. About 95% of the inserted cells were successfully tracked in a controlled phantom environment. These results underline the potential of MPI for real-time investigation of cell migration and interaction with tissue in vivo.

Hydroxychloroquine Induced Cardiotoxicity: A Case Series.

Hydroxychloroquine (HCQ) induced cardiotoxicity is a rare diagnosis and is often associated with chronic use of the medication. It has been shown that chronic HCQ use is associated with a drug-induced cardiomyopathy mainly driven by acquired lysosomal storage defects leading to hypertrophy and conduction abnormalities. As the only proven treatment is the discontinuation of the offending agent, prompt recognition is required to avoid further exposure to the drug and potential progression of disease. History, physical examination and advanced imaging modalities are useful diagnostic tools, but more invasive testing with an endomyocardial biopsy is required for definitive diagnosis. We present a descriptive case series of ten patients that were diagnosed with biopsy proven HCQ cardiotoxicity.

Review of machine learning for optical imaging of burn wound severity assessment.

Over the past decade, machine learning (ML) algorithms have rapidly become much more widespread for numerous biomedical applications, including the diagnosis and categorization of disease and injury. Here, we seek to characterize the recent growth of ML techniques that use imaging data to classify burn wound severity and report on the accuracies of different approaches. To this end, we present a comprehensive literature review of preclinical and clinical studies using ML techniques to classify the severity of burn wounds. The majority of these reports used digital color photographs as input data to the classification algorithms, but recently there has been an increasing prevalence of the use of ML approaches using input data from more advanced optical imaging modalities (e.g., multispectral and hyperspectral imaging, optical coherence tomography), in addition to multimodal techniques. The classification accuracy of the different methods is reported; it typically ranges from to 90% relative to the current gold standard of clinical judgment. The field would benefit from systematic analysis of the effects of different input data modalities, training/testing sets, and ML classifiers on the reported accuracy. Despite this current limitation, ML-based algorithms show significant promise for assisting in objectively classifying burn wound severity.

A deep learning approach for mental health quality prediction using functional network connectivity and assessment data.

While one can characterize mental health using questionnaires, such tools do not provide direct insight into the underlying biology. By linking approaches that visualize brain activity to questionnaires in the context of individualized prediction, we can gain new insights into the biology and behavioral aspects of brain health. Resting-state fMRI (rs-fMRI) can be used to identify biomarkers of these conditions and study patterns of abnormal connectivity. In this work, we estimate mental health quality for individual participants using static functional network connectivity (sFNC) data from rs-fMRI. The deep learning model uses the sFNC data as input to predict four categories of mental health quality and visualize the neural patterns indicative of each group. We used guided gradient class activation maps (guided Grad-CAM) to identify the most discriminative sFNC patterns. The effectiveness of this model was validated using the UK Biobank dataset, in which we showed that our approach outperformed four alternative models by 4-18% accuracy. The proposed model's performance evaluation yielded a classification accuracy of 76%, 78%, 88%, and 98% for the excellent, good, fair, and poor mental health categories, with poor mental health accuracy being the highest. The findings show distinct sFNC patterns across each group. The patterns associated with excellent mental health consist of the cerebellar-subcortical regions, whereas the most prominent areas in the poor mental health category are in the sensorimotor and visual domains. Thus the combination of rs-fMRI and deep learning opens a promising path for developing a comprehensive framework to evaluate and measure mental health. Moreover, this approach had the potential to guide the development of personalized interventions and enable the monitoring of treatment response. Overall this highlights the crucial role of advanced imaging modalities and deep learning algorithms in advancing our understanding and management of mental health.

Abstract TMP56: Accuracy of Dual-Energy Computed Tomography for Differentiation Between Cerebral Hemorrhage and Contrast Extravasation Following Mechanical Revascularization in Acute Ischemic Stroke: A Diagnostic Accuracy Meta-Analysis

Background: Mechanical revascularization has become an essential treatment for acute ischemic stroke patients. Post-treatment imaging frequently displays hyperdense regions, prompting concerns regarding possible cerebral hemorrhage. Dual-energy computed tomography (DECT), as an advanced imaging modality, offers the potential to discern between hemorrhage and harmless contrast leakage. Aim: This study aims to assess the diagnostic precision of DECT in distinguishing cerebral hemorrhage from contrast extravasation post-mechanical revascularization in acute ischemic stroke cases. Methods: A comprehensive search was performed for PubMed, EMBASE, and the Cochrane Library until January 2023. We focused on studies that focused on the diagnostic efficacy of DECT for this specific application. R software (version 4.0.3) coupled with mada package facilitated the analyses pooling metrics such as sensitivity, specificity, false-positive rate estimates, diagnostic odds ratio, and positive and negative Likelihood Ratios. These metrics were reported with a 95% Confidence Interval (CI). Results: Our analysis included 5 studies involving 241 patients. DECT demonstrated a pooled sensitivity of 94.5% (95% CI: 25.9% to 99.9%, I 2 =0%) and a specificity of 99% (95% CI: 77.3% to 100%, I 2 =0%). The false-positive rate was minimal at 1% (95% CI: 0% to 22.7%). The positive likelihood ratio was calculated as 98.94 (95% CI: 3.34 to 2929.22), while the negative likelihood ratio was 0.05 (95% CI: 0.001 to 2.21). The diagnostic odds ratio was substantial at 1795.17 (95% CI: 10.04 to 321055.24), signifying a robust performance of DECT in making the differentiation. Conclusion: While DECT manifests impressive accuracy in differentiating cerebral hemorrhage from contrast extravasation after mechanical revascularization in acute ischemic stroke cases, the wide confidence intervals signify a degree of uncertainty in these estimates. Nevertheless, given its high diagnostic metrics, DECT can substantially influence post-intervention evaluations, paving the way for more informed clinical decisions and potentially reducing patient adverse outcomes. However, further studies with larger sample sizes might help refine these diagnostic estimates.

How Imaging Advances Are Defining the Future of Precision Radiation Therapy.

Radiation therapy is fundamental in the treatment of cancer. Imaging has always played a central role in radiation oncology. Integrating imaging technology into irradiation devices has increased the precision and accuracy of dose delivery and decreased the toxic effects of the treatment. Although CT has become the standard imaging modality in radiation therapy, the development of recently introduced next-generation imaging techniques has improved diagnostic and therapeutic decision making in radiation oncology. Functional and molecular imaging techniques, as well as other advanced imaging modalities such as SPECT, yield information about the anatomic and biologic characteristics of tumors for the radiation therapy workflow. In clinical practice, they can be useful for characterizing tumor phenotypes, delineating volumes, planning treatment, determining patients' prognoses, predicting toxic effects, assessing responses to therapy, and detecting tumor relapse. Next-generation imaging can enable personalization of radiation therapy based on a greater understanding of tumor biologic factors. It can be used to map tumor characteristics, such as metabolic pathways, vascularity, cellular proliferation, and hypoxia, that are known to define tumor phenotype. It can also be used to consider tumor heterogeneity by highlighting areas at risk for radiation resistance for focused biologic dose escalation, which can impact the radiation planning process and patient outcomes. The authors review the possible contributions of next-generation imaging to the treatment of patients undergoing radiation therapy. In addition, the possible roles of radio(geno)mics in radiation therapy, the limitations of these techniques, and hurdles in introducing them into clinical practice are discussed. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Navigating the Frontier: Emerging Techniques for Detecting Microvascular Complications in Type 2 Diabetes Mellitus: A Comprehensive Review.

This review comprehensively explores emerging techniques for detecting microvascular complications in Type 2 Diabetes Mellitus (T2DM), addressing the critical need for advancements in early detection and management. As T2DM continues to rise globally, microvascular complications, including retinopathy, nephropathy, and neuropathy, contribute significantly to the morbidity and mortality associated with the condition. The review synthesizes key findings, revealing various emerging technologies, from advanced imaging modalities to genomic and proteomic approaches. It underscores the potential for personalized medicine, emphasizing the importance of tailoring diagnostic strategies to individual patient profiles. Challenges, including the lack of standardized criteria and issues related to patient adherence, highlight the necessity for collaborative efforts. The conclusion issues a call to action, advocating for enhanced collaboration, increased research investment, patient empowerment through education, and seamless integration of emerging diagnostic techniques into routine clinical care. The review envisions a transformative shift in detecting and managing microvascular complications in T2DM, ultimately improving patient outcomes and contributing to a healthier future for individuals affected by this prevalent metabolic disorder.

Validating the safety of low-dose CTPA in pregnancy: results from the OPTICA (Optimised CT Pulmonary Angiography in Pregnancy) Study.

Pulmonary embolism (PE) is a leading cause of pregnancy-related mortality. CT pulmonary angiogram (CTPA) is the first-line advanced imaging modality for suspected PE in pregnancy at institutes offering low-dose techniques; however, a protocol balancing safety with low dose remains undefined. The wide range of CTPA doses reported in pregnancy suggests a lack of confidence in implementing low-dose techniques in this group. To define and validate the safety, radiation dose and image quality of a low-dose CTPA protocol optimised for pregnancy. The OPTICA study is a prospective observational study. Pregnant study participants with suspected PE underwent the same CTPA protocol between May 2018 and February 2022. The primary outcome, CTPA safety, was judged by the reference standard; the 3-month incidence of venous thromboembolism (VTE) in study participants with a negative index CTPA. Secondary outcomes defined radiation dose and image quality. Absorbed breast, maternal effective and fetal doses were estimated by Monte-Carlo simulation on gestation-matched phantoms. Image quality was assessed by signal-to-noise and contrast-to-noise ratios and a Likert score for pulmonary arterial enhancement. A total of 116 CTPAs were performed in 113 pregnant women of which 16 CTPAs were excluded. PE was diagnosed on 1 CTPA and out-ruled in 99. The incidence of recurrent symptomatic VTE was 0.0% (one-sided 95% CI, 2.66%) at follow-up. The mean absorbed breast dose was 2.9 ± 2.1mGy, uterine/fetal dose was 0.1 ± 0.2mGy and maternal effective dose was 1.4 ± 0.9mSv. Signal-to-noise ratio (SNR) was 11.9 ± 3.7. Contrast-to-noise ratio (CNR) was 10.4 ± 3.5. The OPTICA CTPA protocol safely excluded PE in pregnant women across all trimesters, with low fetal and maternal radiation. OPTICA (Optimised CT Pulmonary Angiography in Pregnancy) is the first prospective study to define the achievable radiation dose, image-quality and safety of a low-dose CT pulmonary angiogram protocol optimised for pregnancy (NCT04179487). It provides the current benchmark for safe and achievable CT pulmonary angiogram doses in the pregnant population. • Despite the increased use of CT pulmonary angiogram in pregnancy, an optimised low-dose protocol has not been defined and reported doses in pregnancy continue to vary widely. • The OPTICA (Optimised CT Pulmonary Angiography in Pregnancy) study prospectively defines the achievable dose, image quality and safety of a low-dose CT pulmonary angiogram protocol using widely available technology. • OPTICA provides a benchmark for safe and achievable CT pulmonary angiogram doses in the pregnant population.

Subtle Syndesmotic Instability.

Latent or subtle syndesmotic instability is defined as an injury to the syndesmosis which is not apparent on static radiographs of the ankle. Syndesmotic injuries have also been referred to as high ankle sprains. Injury to the syndesmosis typically occurs with collision sports and often involves an external rotation force to the ankle. Diagnosis can be delayed because of negative initial imaging studies. Physical examination tests including the external rotation test, proximal squeeze test, and fibular shuck test can assist in the diagnosis. Advanced imaging modalities such as MRI and weight-bearing CT have been studied and can provide prognostic indications for management, although arthroscopic stress evaluation remains the benchmark for diagnosis. Both surgical and nonsurgical management techniques have been described, which can assist patients in returning to their preinjury level of function.

Progress in Oligometastatic Prostate Cancer: Emerging Imaging Innovations and Therapeutic Approaches

Prostate cancer (PCa) exhibits a spectrum of heterogeneity, from indolent to highly aggressive forms, with approximately 10–20% of patients experiencing metastatic PCa. Oligometastatic PCa, characterized by a limited number of metastatic lesions in specific anatomical locations, has gained attention due to advanced imaging modalities. Although patients with metastatic PCa typically receive systemic therapy, personalized treatment approaches for oligometastatic PCa are emerging, including surgical and radiotherapeutic interventions. This comprehensive review explores the latest developments in the field of oligometastatic PCa, including its biological mechanisms, advanced imaging techniques, and relevant clinical studies. Oligometastatic PCa is distinct from widespread metastases and presents challenges in patient classification. Imaging plays a crucial role in identifying and characterizing oligometastatic lesions, with new techniques such as prostate-specific membrane antigen positron emission tomography demonstrating a remarkable efficacy. The management strategies encompass cytoreductive surgery, radiotherapy targeting the primary tumor, and metastasis-directed therapy for recurrent lesions. Ongoing clinical trials are evaluating the effectiveness of these approaches. Oligometastatic PCa occupies a unique position between locally advanced and high-volume metastatic diseases. While a universally accepted definition and standardized diagnostic criteria are still evolving, emerging imaging technologies and therapeutic strategies hold promise for improving the patient outcomes in this intermediate stage of PCa.

Silent Myocardial Ischemia: From Pathophysiology to Diagnosis and Treatment.

Silent myocardial ischemia (SMI), characterized by a lack of overt symptoms despite an inadequate blood supply to the myocardium, remains a challenging entity in cardiovascular medicine. The pathogenesis involves intricate interactions of vascular, neurohormonal, and metabolic factors, contributing to perfusion deficits without the characteristic chest pain. Understanding these mechanisms is pivotal for recognizing diverse clinical presentations and designing targeted interventions. Diagnostic strategies for SMI have evolved from traditional electrocardiography to advanced imaging modalities, including stress echocardiography, single-photon emission computed tomography (SPECT), positron emission tomography (PET), and cardiac magnetic resonance imaging (MRI). Treating SMI is a matter of ongoing debate, as the available evidence on the role of invasive versus medical management is controversial. This comprehensive review synthesizes current knowledge of silent myocardial ischemia, addressing its pathophysiology, diagnostic modalities, and therapeutic interventions.

Imaging Findings and Management of Kidney Cysts – A Pictorial Essay

Renal cysts have become more commonly recognized in asymptomatic patients due to the improvement and frequency of the use of advanced imaging modalities, such as CT and MRI. The purpose of the following review is to illustrate the main and most important aspects of renal cysts, including a checklist of top differential diagnoses and also, their further management and treatment options. Some renal cysts can have significant clinical implications; this is why increased awareness of these renal lesions is of the utmost importance to avoid diagnostic pitfalls or further complications.