Noninvasive Assessment Research Articles

Wearable laser Doppler flowmetry for non-invasive assessment of diabetic foot microcirculation: methodological considerations and clinical implications.

Type 2 diabetes mellitus (T2DM) is a global health concern with significant implications for vascular health. The current evaluation methods cannot achieve effective, portable, and quantitative evaluation of foot microcirculation. We aim to use a wearable device laser Doppler flowmetry (LDF) to evaluate the foot microcirculation of T2DM patients at rest. Eleven T2DM patients and twelve healthy subjects participated in this study. The wearable LDF was used to measure the blood flows (BFs) for regions of the first metatarsal head (M1), fifth metatarsal head (M5), heel, and dorsal foot. Typical wavelet analysis was used to decompose the five individual control mechanisms: endothelial, neurogenic, myogenic, respiratory, and heart components. The mean BF and sample entropy (SE) were calculated, and the differences between diabetic patients and healthy adults and among the four regions were compared. Diabetic patients showed significantly reduced mean BF in the neurogenic () and heart () components at the M1 and M5 regions () compared with healthy adults. Diabetic patients had significantly lower SE in the neurogenic () and myogenic () components at the M1 region, as well as in the endothelial () component at the M5 region and in the myogenic component at the dorsal foot (), compared with healthy adults. The SE in the myogenic component at the dorsal foot was lower than at the M5 region () and heel area (). Similarly, the SE in the heart component at the dorsal foot was lower than at the M5 region () and heel area () in diabetic patients. This study indicated the potential of using the novel wearable LDF device for tracking vascular complications and implementing targeted interventions in T2DM patients.

Autonomous Tumor Signature Extraction Applied to Spatially Registered Bi-Parametric MRI to Predict Prostate Tumor Aggressiveness: A Pilot Study

Background: Accurate, reliable, non-invasive assessment of patients diagnosed with prostate cancer is essential for proper disease management. Quantitative assessment of multi-parametric MRI, such as through artificial intelligence or spectral/statistical approaches, can provide a non-invasive objective determination of the prostate tumor aggressiveness without side effects or potential poor sampling from needle biopsy or overdiagnosis from prostate serum antigen measurements. To simplify and expedite prostate tumor evaluation, this study examined the efficacy of autonomously extracting tumor spectral signatures for spectral/statistical algorithms for spatially registered bi-parametric MRI. Methods: Spatially registered hypercubes were digitally constructed by resizing, translating, and cropping from the image sequences (Apparent Diffusion Coefficient (ADC), High B-value, T2) from 42 consecutive patients in the bi-parametric MRI PI-CAI dataset. Prostate cancer blobs exceeded a threshold applied to the registered set from normalizing the registered set into an image that maximizes High B-value, but minimizes the ADC and T2 images, appearing “green” in the color composite. Clinically significant blobs were selected based on size, average normalized green value, sliding window statistics within a blob, and position within the hypercube. The center of mass and maximized sliding window statistics within the blobs identified voxels associated with tumor signatures. We used correlation coefficients (R) and p-values, to evaluate the linear regression fits of the z-score and SCR (with processed covariance matrix) to tumor aggressiveness, as well as Area Under the Curves (AUC) for Receiver Operator Curves (ROC) from logistic probability fits to clinically significant prostate cancer. Results: The highest R (R > 0.45), AUC (>0.90), and lowest p-values (<0.01) were achieved using z-score and modified registration applied to the covariance matrix and tumor signatures selected from the “greenest” parts from the selected blob. Conclusions: The first autonomous tumor signature applied to spatially registered bi-parametric MRI shows promise for determining prostate tumor aggressiveness.

Invasive and non-invasive assessment of non-culprit coronary lesions in patients with ST-segment elevation myocardial infarction

Invasive and non-invasive assessment of non-culprit coronary lesions in patients with ST-segment elevation myocardial infarction

Diagnosis and Management of MASLD: An Metabolic Perspective of a Multisystem Disease

Metabolic dysfunction–associated steatotic liver disease (MASLD) has attained epidemic proportions in recent years, affecting nearly one-third of the general population and two-thirds of patients with type 2 diabetes (T2DM). It encompasses a wide spectrum of pathophysiological entities, ranging from simple steatosis to steatohepatitis to fibrosis and cirrhosis, with both hepatic and extrahepatic implications, including cardiovascular disease. The possibility of MASLD should be considered in high-risk groups such as T2DM, obesity, metabolic syndrome, polycystic ovarian syndrome (PCOS), etc., with/ without evidence of hepatic steatosis on imaging or persistently raised liver enzymes. Initial assessment should include a comprehensive evaluation of comorbidities, exclusion of secondary causes of steatosis, and fibrosis risk stratification. The presence of NASH and fibrosis is the most important predictor of adverse clinical outcomes, and non-invasive risk assessment has been an area of intense research in recent decades. FIB-4 can be used as a primary tool to effectively rule out significant fibrosis, followed by vibration-controlled transient elastography (VCTE) or enhanced liver fibrosis (ELF) tests as secondary tools if the FIB-4 score is indeterminate or high. The management of MASLD patients has shifted from a hepatocentric to a multicentric approach, with a focus on lifestyle interventions, disease-modifying pharmacotherapy in selected patients, and optimized management of comorbidities and complications.

Interpretable machine learning based on CT-derived extracellular volume fraction to predict pathological grading of hepatocellular carcinoma.

To develop a non-invasive auxiliary assessment method based on CT-derived extracellular volume (ECV) to predict the pathological grading (PG) of hepatocellular carcinoma (HCC). The study retrospectively analyzed 238 patients who underwent HCC resection surgery between January 2013 and April 2023. Six machine learning algorithms were employed to construct predictive models for HCC PG: logistic regression, extreme gradient boosting, Light Gradient Boosting Machine (LightGBM), random forest, adaptive boosting, and Gaussian naive Bayes. Model performance was evaluated using receiver operating characteristic curve analysis, including area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and F1 score. Calibration plots were used for visual evaluation of model calibration. Clinical decision curve analysis was performed to assess potential clinical utility by calculating net benefit. 166 patients from Hospital A were allocated to the training set, while 72 patients from Hospital B (constituting 30.25% of the total sample) were assigned to the test set. The model achieved an AUC of 1.000 (95%CI: 1.000-1.000) in the training set and 0.927 (95%CI: 0.837-0.999) in the validation set, respectively. Ultimately, the model achieved an AUC of 0.909 (95%CI: 0.837-0.980) in the test set, with an accuracy of 0.778, sensitivity of 0.906, specificity of 0.789, negative predictive value of 0.556, and F1 score of 0.908. This study successfully developed and validated a non-invasive auxiliary assessment method based on CT-derived ECV to predict the HCC PG, providing important supplementary information for clinical decision-making.

Radioligand therapies in meningioma - evidence and future directions.

Meningiomas are the most common intracranial neoplasms in adults. While most meningiomas are cured by resection, further treatment by radiotherapy may be needed, particularly in WHO grade 2 and 3 tumors which have an increased risk of recurrence, even after conventional therapies. Still, there is an urgent need for novel therapeutic strategies after exhaustion of local treatment approaches. Radionuclide therapies combine the specificity of tumor-specific antibodies or ligands with the cytotoxic activity of radioactive emitters. Alongside, integrated molecular imaging allows for a non-invasive assessment of predictive biomarkers as treatment targets. Whereas the concept of "theranostics" has initially evolved in extracranial tumors such as thyroid diseases, neuroendocrine tumors, and prostate cancer, data from retrospective case series and early phase trials underscore the potential of this strategy in meningioma. This review aims to explore the available evidence of radionuclide treatments and ongoing clinical trial initiatives in meningioma. Moreover, we discuss optimal clinical trial design and future perspectives in the field, including compound- and host-specific determinants of the efficacy of "theranostic" treatment approaches.

The discerning influence of dynamic contrast-enhanced MRI in anticipating molecular subtypes of breast cancer through the artistry of artificial intelligence - a narrative review.

Radio genomics is an exciting new area that uses diagnostic imaging to discover genetic features of diseases. In this review, we carefully examined existing literature to evaluate the role of artificial intelligence (AI) and machine learning (ML) on dynamic contrastenhanced MRI (DCE-MRI) data to distinguish molecular subtypes of breast cancer (BC). Implications to noninvasive assessment of molecular subtype include reduction in procedure risks, tailored treatment approaches, ability to examine entire lesion, follow-up of tumour biology in response to treatment and evaluation of treatment resistance and failure secondary to tumour heterogeneity. Recent studies leverage radiomics and AI on DCE-MRI data for reliable, non-invasive breast cancer subtype classification. This review recognizes the potential of AI to predict the molecular subtypes of breast cancer non-invasively.

Nitric oxide donor increases umbilical vein blood flow and fetal oxygenation in fetal growth restriction. A pilot study

IntroductionTo evaluate the maternal and fetal hemodynamic effects of treatment with a nitric oxide donor and oral fluid in pregnancies complicated by fetal growth restriction. Methods30 normotensive participants with early fetal growth restriction were enrolled. 15 participants were treated until delivery with transdermal glyceryl trinitrate and oral fluid intake (Treated group), and 15 comprised the untreated group. All women underwent non-invasive assessment of fetal and maternal hemodynamics and repeat evaluation 2 weeks later. ResultsIn the treated group, maternal hemodynamics improved significantly after two weeks of therapy compared to untreated participants. Fetal hemodynamics in the treated group showed an increase in umbilical vein diameter by 18.87 % (p < 0.01), in umbilical vein blood flow by 48.16 % (p < 0.01) and in umbilical vein blood flow corrected for estimated fetal weight by 30.03 % (p < 0.01). In the untreated group, the characteristics of the umbilical vein were unchanged compared to baseline. At the same time, the cerebro-placental ratio increased in the treated group, while it was reduced in the untreated group, compared to baseline values. The treated group showed a higher birthweight centile (p = 0.03) and a lower preeclampsia rate (p = 0.04) compared to the untreated group. DiscussionThe combined therapeutic approach with nitric oxide donor and oral fluid intake in fetal growth restriction improves maternal hemodynamics, which becomes more hyperdynamic (volume-dominant). At the same time, in the fetal circuit, umbilical vein flow increased and fetal brain sparing improved. Although a modest sample size, there was less preeclampsia and a higher birthweight suggesting beneficial maternal and fetal characteristics of treatment.

Prospective Deep Learning-based Quantitative Assessment of Coronary Plaque by CT Angiography Compared with Intravascular Ultrasound.

Coronary computed tomography angiography provides noninvasive assessment of coronary stenosis severity and flow impairment. Automated artificial intelligence analysis may assist in precise quantification and characterization of coronary atherosclerosis, enabling patient-specific risk determination and management strategies. This multicenter international study compared an automated deep-learning-based method for segmenting coronary atherosclerosis in coronary computed tomography angiography (CCTA) against the reference standard of intravascular ultrasound (IVUS). The study included clinically stable patients with known coronary artery disease from 15 centers in the U.S. and Japan. An artificial intelligence (AI)-enabled plaque analysis service was utilized to quantify and characterize total plaque (TPV), vessel, lumen, calcified plaque (CP), non-calcified plaque (NCP), and low attenuation plaque (LAP) volumes derived from CCTA and compared with IVUS measurements in a blinded, core laboratory-adjudicated fashion. In 237 patients, 432 lesions were assessed; mean lesion length was 24.5 mm. Mean IVUS-TPV was 186.0 mm3. AI-enabled plaque analysis on CCTA showed strong correlation and high accuracy when compared with IVUS; correlation coefficient, slope, and Y intercept for TPV were 0.91, 0.99, and 1.87, respectively; for CP volume 0.91, 1.05, and 5.32, respectively; and for NCP volume 0.87, 0.98, and 15.24, respectively. Bland-Altman analysis demonstrated strong agreement with little bias for these measurements. Artificial intelligence enabled CCTA quantification and characterization of atherosclerosis demonstrated strong agreement with IVUS reference standard measurements. This tool may prove effective for accurate evaluation of coronary atherosclerotic burden and cardiovascular risk assessment.[ClinicalTrails.gov identifier: NCT05138289].

Assessment of testicular stiffness in fertile dogs with shear wave elastography techniques: a pilot study

Ultrasound of the testes is important in the evaluation of breeding dogs, and recently advanced techniques such as Shear Wave Elastography (SWE) have been developed. This study focused on evaluation of normal testicular stiffness in healthy and fertile male dogs, employing both qualitative (2D-SWE) and quantitative (pSWE, 2D-SWE) techniques. Nineteen dogs of various medium-large breeds aged 3.39 ± 2.15 years, and with a history of successful reproduction were included after clinical, B-mode and Doppler ultrasound of testes and prostate, and semen macro and microscopic evaluations. pSWE involved square regions of interest (ROIs) placed at six different points in the testicular parenchyma, while 2D-SWE depicted stiffness with a color scale ranging from blue (soft) to red (stiff), allowing a subsequent quantification of stiffness by the application of 4 round ROIs. The results showed a mean Shear Wave Speed (SWS) of 2.15 ± 0.39 m/s using pSWE, with lower values above the mediastinum compared to below, and in the center of the testis compared to the cranial and caudal poles. 2D-SWE demonstrated a uniform blue pattern in the parenchyma, and a mean SWS of 1.65 ± 0.15 m/s. No significant differences were found between left and right testes, above and below the mediastinum, or among breeds. No correlations were observed between mean SWS and body condition score, age, testicular and prostatic volume. Weight was positively correlated with mean SWS only by 2D-SWE. By performing semen analysis and enrolling only healthy and fertile adult dogs, we ensured both structural and functional integrity of the testes. This pilot study represents a valuable baseline data for testicular stiffness by both pSWE and 2D-SWE with a Mindray US machine in medium-large sized healthy and fertile dogs, pointing out the potential role of SWE in the non-invasive fertility assessment and management of breeding dogs.

3D-Volumetric Shunt Measurement for Detection of High-Risk Esophageal Varices in Liver Cirrhosis.

Background and Objectives: Esophageal varices (EV) and variceal hemorrhages are major causes of mortality in liver cirrhosis patients. Detecting EVs early is crucial for effective management. Computed tomography (CT) scans, commonly performed for various liver-related indications, provide an opportunity for non-invasive EV assessment. However, previous CT studies focused on variceal diameter, neglecting the three-dimensional (3D) nature of varices and shunt vessels. This study aims to evaluate the potential of 3D volumetric shunt-vessel measurements from routine CT scans for detecting high-risk esophageal varices in portal hypertension. Methods: 3D volumetric measurements of esophageal varices were conducted using routine CT scans and compared to endoscopic variceal grading. Receiver operating characteristic (ROC) analyses were performed to determine the optimal cutoff value for identifying high-risk varices based on shunt volume. The study included 142 patients who underwent both esophagogastroduodenoscopy (EGD) and contrast-enhanced CT within six months. Results: The study established a cutoff value for identifying high-risk varices. The CT measurements exhibited a significant correlation with endoscopic EV grading (correlation coefficient r = 0.417, p < 0.001). A CT cutoff value of 2060 mm3 for variceal volume showed a sensitivity of 72.1% and a specificity of 65.5% for detecting high-risk varices during endoscopy. Conclusions: This study demonstrates the feasibility of opportunistically measuring variceal volumes from routine CT scans. CT volumetry for assessing EVs may have prognostic value, especially in cirrhosis patients who are not suitable candidates for endoscopy.

A brain metastasis liquid biopsy – Where are we now?

Abstract Brain metastases remain a challenging and feared complication for patients with cancer and research in this area has lagged behind research into metastases to other organs. Due to their location and the risks associated with neurosurgical biopsies, the biology underpinning brain metastases response to treatment and evolution over time remains poorly understood. Liquid biopsies are proposed to overcome many of the limitations present with tissue biopsies, providing a better representation of tumour heterogeneity, facilitating repeated sampling, and providing a non-invasive assessment of tumour biology. Several different liquid biopsy approaches have been investigated including circulating tumour cells, circulating tumour DNA, extracellular vesicles, and tumour educated platelets; however, these have generally been less effective in assessing brain metastases compared to metastases to other organs requiring improved techniques to investigate these approaches, studies combining different liquid biopsy approaches and/or novel liquid biopsy approaches. Through this review we highlight the current state of the art and define key unanswered questions related to brain metastases liquid biopsies.

Deep learning in magnetic resonance enterography for Crohn's disease assessment: a systematic review.

Crohn's disease (CD) poses significant morbidity, underscoring the need for effective, non-invasive inflammatory assessment using magnetic resonance enterography (MRE). This literature review evaluates recent publications on the role of deep learning in improving MRE for CD assessment. We searched MEDLINE/PUBMED for studies that reported the use of deep learning algorithms for assessment of CD activity. The study was conducted according to the PRISMA guidelines. The risk of bias was evaluated using the QUADAS-2 tool. Five eligible studies, encompassing 468 subjects, were identified. Our study suggests that diverse deep learning applications, including image quality enhancement, bowel segmentation for disease burden quantification, and 3D reconstruction for surgical planning are useful and promising for CD assessment. However, most of the studies are preliminary, retrospective studies, and have a high risk of bias in at least one category. Future research is needed to assess how deep learning can impact CD patient diagnostics, particularly when considering the increasing integration of such models into hospital systems.

Smartphone-Based Interferometry for Non-Invasive Assessment of Tear Film Lipid Layer Kinetics

Smartphone-Based Interferometry for Non-Invasive Assessment of Tear Film Lipid Layer Kinetics

Impact of obstruction size on ureter dynamics: A computational investigation

Kidney stones, known medically as nephrolithiasis, present a significant health concern globally, particularly in regions such as India and the Middle East. Despite extensive research, the complexity of ureteral obstruction due to kidney stones remains a challenge in urology. This study addresses this gap by analysing the effects of obstruction in a three-dimensional model of the ureter with a constant diameter, simulating various percentages of blockage. Through computational analysis, the pressure and velocity effects on the ureter wall are explored, providing insights into the dynamics of obstructed ureters. Building upon previous research, this study contributes to a deeper understanding of the factors influencing flow patterns and pressure variations within the urinary tract. Additionally, findings from this study may lead to advancements in non-invasive assessment methods for diagnosing and treating ureteral obstruction caused by kidney stones. Furthermore, insights gained from this research could potentially inform clinical decision-making, leading to improved management strategies and better outcomes for patients affected by this debilitating condition. The novelty of this work lies in its comprehensive analysis of the effects of obstruction on the ureteral wall, offering valuable implications for urological practice and patient care.

Unraveling molecular advancements in chordoma tumorigenesis and treatment response: a review of scientific discoveries and clinical implications.

Chordomas are tumors thought to originate from notochordal remnants that occur in midline structures from the cloves of the skull base to the sacrum. In adults, the most common location is the sacrum, followed by the clivus and then mobile spine, while in children a clival origin is most common. Most chordomas are slow growing. Clinical presentation of chordomas tend to occur late, with local invasion and large size often complicating surgical intervention. Radiation therapy with protons has been proven to be an effective adjuvant therapy. Unfortunately, few adjuvant systemic treatments have demonstrated significant effectiveness, and chordomas tend to recur despite intensive multimodal care. However, insight into the molecular underpinnings of chordomas may guide novel therapeutic approaches including selection for immune and molecular therapies, individualized prognostication of outcomes, and real-time noninvasive assessment of disease burden and evolution. At the genomic level, elevated levels of brachyury stemming from duplications and mutations resulting in altered transcriptional regulation may introduce druggable targets for new surgical adjuncts. Transcriptome and epigenome profiling have revealed promoter- and enhancer-dependent mechanisms of protein regulation, which may influence therapeutic response and long-term disease history. Continued scientific and clinical advancements may offer further opportunities for treatment of chordomas. Single-cell transcriptome profiling has further provided insight into the heterogeneous molecular pathways contributing to chordoma propagation. New technologies such as spatial transcriptomics and emerging biochemical analytes such as cell-free DNA have further augmented the surgeon-clinician's armamentarium by facilitating detailed characterization of intra- and intertumoral biology while also demonstrating promise for point-of-care tumor quantitation and assessment. Recent and ongoing clinical trials highlight accelerating interest to translate laboratory breakthroughs in chordoma biology and immunology into clinical care. In this review, the authors dissect the landmark studies exploring the molecular pathogenesis of chordoma. Incorporating this into an outline of ongoing clinical trials and discussion of emerging technologies, the authors aimed to summarize recent advancements in understanding chordoma pathogenesis and how neurosurgical care of chordomas may be augmented by improvements in adjunctive treatments.

Non-invasive pulse arrival time as a surrogate for oscillometric systolic blood pressure changes during non-pharmacological intervention.

Non-invasive continuous blood pressure monitoring is of longstanding interest in various cardiovascular scenarios. In this context, pulse arrival time (PAT), i.e., a surrogate parameter for systolic blood pressure (change), became very popular recently, especially in the context of cuffless blood pressure measurement and dedicated lifestyle interventions. Nevertheless, there is also understandable doubt on its reliability in uncontrolled and mobile settings.&#xD;Objective: The aim of this work is therefore the investigation whether PAT follows oscillometric systolic blood pressure readings during moderate interventions by physical or mental activity using a medical grade handheld device for non-invasive PAT assessment.&#xD;Methods: A study was conducted featuring an experimental group performing a physical and a mental task, and a control group. Oscillometric blood pressure and PAT were assessed at baseline and after each intervention. Interventions were selected randomly but then performed sequentially in a counterbalanced order. Multivariate analyses of variance were used to test within-subject and between-subject effects for the dependent variables, followed by univariate analyses for post-hoc testing. Furthermore, correlation analysis was performed to assess the association of intervention effects between blood pressure and PAT. &#xD;Results: The study included 51 subjects (31 females). Multivariate analysis of variances showed that effects in blood pressure, heart rate, PAT and pulse wave parameters were consistent and significantly different between experimental and control groups. After physical activity, heart rate and systolic blood pressure increased significantly whereas PAT decreased significantly. Mental activity leads to a decrease in systolic blood pressure at stable heart rate. Pulse wave parameters follow accordingly by an increase of PAT and mainly unchanged pulse wave analysis features due to constant heart rate. Finally, also the control group behaviour was accurately registered by the PAT method compared to oscillometric cuff. Correlation analyses revealed significant negative associations between changes of systolic blood pressure and changes of PAT from baseline to the physical task (-0.33 [-0.63, 0.01], p<0.048), and from physical to mental task (-0.51 [-0.77, -0.14], p=0.001), but not for baseline to mental task (-0.12 [-0,43,0,20], p=0.50) in the experimental group.&#xD;Conclusion: PAT and the used digital, handheld device proved to register changes in blood pressure and heart rate reliably compared to oscillometric measurements during intervention. Therefore, it might add benefit to future mobile health solutions to support blood pressure management by tracking relative, not absolute, blood pressure changes during non-pharmacological interventions.

Development and Clinical Application of Left Ventricular–Arterial Coupling Non-Invasive Assessment Methods

The constant and dynamic interaction between ventricular function and arterial afterload, known as ventricular-arterial coupling, is key to understanding cardiovascular pathophysiology. Ventricular–arterial coupling has traditionally been assessed invasively as the ratio of effective arterial elastance over end-systolic elastance (Ea/Ees), calculated from information derived from pressure–volume loops. Over the past few decades, numerous invasive and non-invasive simplified methods to estimate the elastance ratio have been developed and applied in clinical investigation and practice. The echocardiographic assessment of left ventricular Ea/Ees, as proposed by Chen and colleagues, is the most widely used method, but novel echocardiographic approaches for ventricular–arterial evaluation such as left ventricle outflow acceleration, pulse-wave velocity, and the global longitudinal strain or global work index have arisen since the former was first published. Moreover, multimodal imaging or artificial intelligence also seems to be useful in this matter. This review depicts the progressive development of these methods along with their academic and clinical application. The left ventricular–arterial coupling assessment may help both identify patients at risk and tailor specific pharmacological or interventional treatments.

Contrast-enhanced Ultrasound Using Intradermal Microbubble Sulfur Hexafluoride in Non-invasive Axillary Staging in Breast Cancer: Are we Missing a Chance?

In the context of surgical de-escalation in early breast cancer (EBC), this study aimed to evaluate the contrast enhancement ultrasound (CEUS) sentinel lymph node (SLN) procedure as a non-invasive axillary staging procedure in EBC in comparison with standard SLN biopsy (SLNB). A subanalysis of the AX-CES study, a prospective single-arm, monocentric phase 3 study was performed (EudraCT: 2020-000393-20). The study included patients with EBC undergoing upfront surgery and SLN resection, with no prior history of locoregional treatment, and weighing between 40-85 kg. All patients underwent the CEUS SLN procedure as a non-invasive axillary staging procedure, with CEUS SLN accumulation marked using blue dye. After the CEUS SLN procedure, all patients underwent the standard mapping procedure. Data on success rate, systemic reactions, mean procedure time, mean surgical procedure, mean procedure without axillary staging, CEUS SLN appearance (normal/pathological), SLN number, and concordance with standard mapping procedure were collected. After the CEUS SLN procedure, 29 LNs among 16 patients were identified and marked. In all cases, CEUS SLN revealed at least one LN enhancement. Six (37.50%) LNs were defined as pathological after the CEUS SLN procedure. Definitive staining of CEUS SLN pathology revealed metastatic involvement in four (66.67%) of the cases. Two SLNs were identified during the CEUS SLN procedure; however, owing to the low disease burden, no change in the surgical plan was reported. The CEUS SLN procedure shows promise as a technique for non-invasive assessment of the axilla, potentially enabling safe axillary de-escalation in EBC by estimating the axillary disease burden.

Subclinical Atherosclerosis to Guide Treatment in Dyslipidemia and Diabetes Mellitus.

Dyslipidemia and type 2 diabetes mellitus are two common conditions that are associated with an increased risk of atherosclerotic cardiovascular disease (ASCVD). In this review, we aimed to provide an in-depth and contemporary review of non-invasive approaches to assess subclinical atherosclerotic burden, predict cardiovascular risk, and guide appropriate treatment strategies. We focused this paper on two main imaging modalities: coronary artery calcium (CAC) score and computed tomography coronary angiography. Recent longitudinal studies have provided stronger evidence on the relationship between increased CAC, thoracic aorta calcification, and risk of cardiovascular events among those with primary hypercholesterolemia, highlighting the beneficial role of statin therapy. Interestingly, resilient profiles of individuals not exhibiting atherosclerosis despite dyslipidemia have been described. Non-conventional markers of dyslipidemia have also been associated with increased subclinical atherosclerosis presence and burden, highlighting the contribution of apolipoprotein B-100 (apoB)-rich lipoprotein particles, such as remnant cholesterol and lipoprotein(a), to the residual risk of individuals on-target for low-density lipoprotein cholesterol (LDL-C) goals. Regarding type 2 diabetes mellitus, variability in atherosclerotic burden has also been found, and CAC testing has shown significant predictive value in stratifying cardiovascular risk. Non-invasive assessment of subclinical atherosclerosis can help reveal the continuum of ASCVD risk in those with dyslipidemia and diabetes mellitus and can inform personalized strategies for cardiovascular disease prevention in the primary prevention setting.