Evaluating the diagnostic performance of non-contrast magnetic resonance angiography sequences in the pre-procedural comprehensive analysis of direct carotid cavernous fistula

PURPOSE

Endovascular treatment of direct carotid cavernous fistula (DCCF) requires invasive diagnostic cerebral angiography for diagnosis and planning; however, a less invasive modality like magnetic resonance angiography (MRA) can be useful, especially in high-risk cases. This single-centre study evaluated a newer MR angiography (MRA) sequence, silent MRA and the traditional time of flight (TOF) MRA for pre-procedural treatment planning of DCCF.

METHODS

All consecutive DCCF patients who underwent TOF, silent MRA and diagnostic cerebral angiography were included in the study. Angiographic features like rent size, location, draining veins and collateral communicating arteries were analysed and compared between the two MRA sequences, with digital subtraction angiography (DSA) as the gold standard.

RESULTS

Fifteen patients were included in the study. TOF MRA exhibited better sensitivity (76.9% vs 69.2%) in identifying the rent location, correctly pinpointing the location in 93.3% compared to 73.3% with silent MRA. Both MRA sequences showed good agreement with DSA for primary sac and rent size. TOF MRA correctly identified 86.2% of 210 total venous structures compared to 96% by silent MRA. Silent MRA demonstrated higher sensitivity (90% vs 76%) and accuracy (87.69 vs 94.36) in visualisation of involved veins compared to TOF MRA.

CONCLUSION

Arterial characteristics of DCCF like rent location and rent size were better assessed by TOF MRA. Although both MRA identified venous features, silent MRA correlated better with DSA irrespective of the size and proximity to the site of the fistula. Combining both sequences can evaluate various angioarchitectural features of DCCF useful for therapeutic planning.

Different Ectopic Endocrine Tumors on Renal Hilum Detected by 68 Ga-DOTATATE PET

ABSTRACT

Renal hilum is a very rare location for primary adrenocortical adenoma or pheochromocytoma. We report 68 Ga-DOTATATE PET/CT findings of primary renal hilar adrenocortical adenoma in one patient and 68 Ga-DOTATATE PET/MR findings of pheochromocytoma in another patient.

Clinical and cardiac CT characteristics of congenital coronary abnormalities occasionally detected in a middle-aged population: A long-term follow-up study

INTRODUCTION

Congenital coronary artery anomalies (CCAA) represent one of the most challenging conditions as their clinical presentation may range from sudden cardiac death to a complete subclinical form. The aim of the present study was to evaluate the diagnostic and prognostic role of cardiac CT (CCT) evaluation in patients with CCAA, focusing on anomalies of origin.

MATERIAL AND METHODS

The present is a retrospective analysis of a prospective clinical registry including a consecutive cohort of patients who underwent clinically indicated CCT from January 2007 to October 2015 for suspected but unknown coronary artery disease (CAD) and were diagnosed for having a congenital coronary abnormality compared to a control group matched for age, sex and segment stenosis score (SSS). Dedicated analysis of all CCT was performed for the present study and only coronary anomalies of origin were considered and included in the study. Two different composite end-points were identified for the present analysis: major cardiovascular events (MACE) and all-cause of death.

RESULTS

Among the 81 patients with CCAAs enrolled the most frequent anomaly was left main artery absence, which was identified in 41 individuals (50.6%). Forty-five subjects (55.5%) have an anomalous origin of the coronary artery from a different sinus of Valsalva and 45 subjects had also an anomalous course with the retro-aortic being the most common (32%). Eleven participants (13.6%) displayed also an intramural segment, while 10 (10.3%) had a slit-like ostial morphology. At multivariate analysis CT identification of ARCA, anomalous inter-arterial course and abnormal ostial morphology were significantly associated with MACE even when adjusted for age and SSS, without any differences in all-cause mortality between the two groups (6.2% vs 2.4% p ​= ​0.2478).

CONCLUSION

The result of the present study is that CCT can be successfully used to define the anatomy and features of CAA. It suggested that in middle-aged patients, the identification of high risk characteristics at CT may have a prognostic value in term of cardiovascular events occurrence at follow-up even if the rate of events strictly linked to CCAA is low.

[Multiparametric MRI in hepatocellular carcinoma, part 2 : Diffusion-weighted imaging in the primary diagnostics and treatment monitoring]

In addition to morphology and tissue perfusion, diffusion-weighted imaging (DWI) is the third pillar of multiparametric diagnostics in oncology. Due to the strong correlation between the apparent diffusion coefficient (ADC) and cell count in hepatocellular carcinoma (HCC), it can be used as a surrogate marker for tumor cell quantity. Therefore, ADC effectively reflects the effects of cytoreductive treatment, such as transarterial chemoembolization (TACE) and systemic chemotherapy and becomes an important clinical marker for treatment response. The DWI should remain an integral part of a magnetic resonance imaging (MRI) protocol in primary HCC diagnostics and treatment monitoring but is of secondary clinical importance compared to contrast-enhanced MRI perfusion sequences and the use of liver-specific contrast agents. For the future, standardization of DWI sequences for better comparability of various study protocols would be desirable.

Angina pectoris? Fake news: a case report of infective endocarditis with giant aortic root abscess detected by cardiac magnetic resonance imaging

Background

Infective endocarditis (IE) is a rare disease associated with high mortality rates. Clinical presentation is highly variable with a time interval between first onset of symptoms and diagnosis > 1 month in 25% of patients. We present a case of aortic valve endocarditis with aortic root abscess (ARA) with chest pain and ischaemic changes on the electrocardiogram (ECG).

Case summary

A 59-year-old Caucasian male with a known bicuspid aortic valve presented at our emergency department with a 2-week history of malaise, subfebrile temperatures, and chest pain episodes. The ECG exhibited ischaemic changes, and laboratory workup showed elevated inflammatory markers and troponin levels. Coronary angiography revealed a one-vessel coronary artery disease with a borderline significant stenosis of the left circumflex artery. Cardiac magnetic resonance imaging showed a large aortic valve vegetation with an ARA expanding intramyocardially, which was not seen on bedside echocardiography. The patient was set on intravenous (i.v.) antibiotics and urgently referred for surgery. The patient received surgical aortic root and valve replacements, reconstruction of the anterior mitral leaflet, and a venous bypass. After successful surgical management followed by 6 weeks of i.v. antibiotics, the patient completely recovered.

Discussion

Diagnosing IE in atypical cases, such as those with ischaemic ECG changes, remains challenging. Infective endocarditis should be considered as an early differential diagnosis in individuals with prosthetic or native valve disease. Infective endocarditis poses a significant risk for perivalvular and ARA formation with high mortality. Aortic root abscess may present with unspecific symptoms or unusual ECG changes and might be missed in standard transthoracic echocardiography in up to 30% of cases. Multimodal imaging can help in establishing a prompt and accurate diagnosis, aid in timely treatment and mitigating the risk of complications of IE.

Best anticoagulation strategy with and without appendage occlusion for stroke-prophylaxis in postablation atrial fibrillation patients with cardiac amyloidosis

INTRODUCTION

Both atrial fibrillation (AF) and amyloidosis increase stroke risk. We evaluated the best anticoagulation strategy in AF patients with coexistent amyloidosis.

METHODS

Consecutive AF patients with concomitant amyloidosis were divided into two groups based on the postablation stroke-prophylaxis approach; group 1: left atrial appendage occlusion (LAAO) in eligible patients and group 2: oral anticoagulation (OAC). Group 1 patients were further divided into Gr. 1A: LAAO + half-does NOAC (HD-NOAC) for 6 months followed by aspirin 81 mg/day and Gr. 1B: LAAO + HD-NOAC. In group 1 patients, with complete occlusion at the 45-day transesophageal echocardiogram, patients were switched to aspirin, 81 mg/day at 6 months. In case of leak, or dense "smoke" in the left atrium (LA) or enlarged LA, they were placed on long-term half-dose (HD) NOAC. Group 2 patients remained on full-dose NOAC during the whole study period.

RESULTS

A total of 92 patients were included in the analysis; group 1: 56 and group 2: 36. After the 45-day TEE, 31 patients from group 1 remained on baby-aspirin and 25 on HD NOAC. At 1-year follow-up, four stroke, one TIA and six device-thrombus were reported in group 1A, compared to none in patients in group 1B (5/31 vs. 0/25, p = .03). No bleeding events were reported in group 1, whereas group 2 had five bleeding events (one subdural hematoma, one retinal hemorrhage, and four GI bleedings). Additionally, one stroke was reported in group 2 that happened during brief discontinuation of OAC.

CONCLUSION

In patients with coexistent AF and amyloidosis, half-dose NOAC following LAAO was observed to be the safest stroke-prophylaxis strategy.

A patient-specific circle of Willis blood flow model in predicting outcomes of balloon test occlusion

BACKGROUND AND PURPOSE

Balloon test occlusion (BTO) evaluates cerebral ischemic tolerance before internal carotid artery (ICA) sacrifice but carries risks like dissection and thrombosis. This study introduces a new approach using a patient-specific circle of Willis (COW) blood flow model, based on non-invasive quantitative MR angiography (qMRA) measurements, to predict the outcomes of BTO.

METHODS

We developed individualized COW blood flow models for 43 patients undergoing BTO. These models simulated blood flow and pressure under normal conditions and with the ICA occlusion. We then compared the model's predictions of blood flow changes due to the simulated ICA occlusion to actual qMRA measurements before the BTO.

RESULTS

For all 31 BTO failures, the ipsilateral hemisphere showed an average flow decrease of 15 ± 10% (mean ± standard deviation), compared to 3 ± 2% in the contralateral hemisphere. In all 12 BTO passes, these figures were 6 ± 3% and 1 ± 0.8%, respectively. Notably, all BTO passes had less than a 10% reduction in the ipsilateral hemisphere. In contrast, 65% of BTO failures and 67% single-photon emission computed tomography (SPECT) failures exhibited a decrease of 10% or more in the same region.

CONCLUSION

Blood flow reduction exceeding 10% in the ipsilateral hemisphere during BTO is a strong predictor of failure in both BTO and SPECT. Our patient-specific COW blood flow models, incorporating detailed flow and arterial geometry data, offered valuable insights for predicting BTO outcomes. These models are especially beneficial for situations where conducting BTO or SPECT is clinically impractical.

Pictorial review: challenges in distinguishing bilateral metaphyseal marrow abnormalities on magnetic resonance imaging

The paediatric metaphysis is afflicted by a wide range of pathological processes as it is the most metabolically active and well-vascularised part of the developing skeleton. This review focuses on metaphyseal marrow signal change detected with magnetic resonance imaging, which is most often occult on radiographs. When bilateral, these imaging appearances frequently present a diagnostic quandary. This review assists the radiologist to confidently dismiss physiological signal change and confidently work through the differential diagnosis. This is achieved by illustrating a practical method of classifying signal change into four categories: physiological red marrow, red marrow reconversion, marrow infiltration, and oedema-like marrow signal intensity. In doing so, various pathological entities are reviewed along with imaging pearls and next-step investigations.

Can convolutional neural networks identify external carotid artery calcifications?

OBJECTIVE

We developed and evaluated the accuracy and reliability of a convolutional neural network (CNN) in detecting external carotid artery calcifications (ECACs) in cone beam computed tomography scans.

STUDY DESIGN

Using TensorFlow, we developed a program to identify calcification in 427 cone beam computed tomography scans evaluated to determine the presence of ECACs. We compared the results to the findings of a human evaluator. Using an 80:20 training-to-validation ratio, we calculated the k-fold cross-validation accuracy of the initial dataset and extrapolated the F1 score and Matthews Correlation Coefficient.

RESULTS

We calculated a k-fold cross-validation accuracy of 76%, with a recall and precision of 66% and 79%, respectively, and a combined F1 score of 0.72. We extrapolated a Matthews correlation coefficient of 0.53, showing a strong balance between confusion matrix categories.

CONCLUSION

Our CNN model can reliably identify ECACs in cone beam computed tomography scans.

Greybox: A hybrid algorithm for direct estimation of tracer kinetic parameters from undersampled DCE-MRI data

BACKGROUND

A variety of deep learning-based and iterative approaches are available to predict Tracer Kinetic (TK) parameters from fully sampled or undersampled dynamic contrast-enhanced (DCE) MRI data. However, both the methods offer distinct benefits and drawbacks.

PURPOSE

To propose a hybrid algorithm (named as 'Greybox'), using both model- as well as DL-based, for solving a multi-parametric non-linear inverse problem of directly estimating TK parameters from undersampled DCE MRI data, which is invariant to undersampling rate.

METHODS

The proposed algorithm was inspired by plug-and-play algorithms used for solving linear inverse imaging problems. This technique was tested for its effectiveness in solving the nonlinear ill-posed inverse problem of generating 3D TK parameter maps from four-dimensional (4D; Spatial + Temporal) retrospectively undersampled k-space data. The algorithm learns a deep learning-based prior using UNET to estimate theK trans $\mathbf {K_{trans}}$ andV p $\mathbf {V_{p}}$ parameters based on the Patlak pharmacokinetic model, and this trained prior was utilized to estimate the TK parameter maps using an iterative gradient-based optimization scheme. Unlike the existing DL models, this network is invariant to the undersampling rate of the input data. The proposed method was compared with the total variation-based direct reconstruction technique on brain, breast, and prostate DCE-MRI datasets for various undersampling rates using the Radial Golden Angle (RGA) scheme. For the breast dataset, an indirect estimation using the Fast Composite Splitting algorithm was utilized for comparison. Undersampling rates of 8 × $\times$ , 12 × $\times$ and 20 × $\times$ were used for the experiments, and the results were compared using the PSNR and SSIM as metrics. For the breast dataset of 10 patients, data from four patients were utilized for training (1032 samples), two for validation (752 samples), and the entire volume of four patients for testing. Similarly, for the prostate dataset of 18 patients, 10 patients were utilized for training (720 samples), five for validation (216 samples), and the whole volume of three patients for testing. For the brain dataset of nineteen patients, ten patients were used for training (3152 samples), five for validation (1168 samples), and the whole volume of four patients for testing. Statistical tests were also conducted to assess the significance of the improvement in performance.

RESULTS

The experiments showed that the proposed Greybox performs significantly better than other direct reconstruction methods. The proposed algorithm improved the estimatedK trans $\mathbf {K_{trans}}$ andV p $\mathbf {V_{p}}$ in terms of the peak signal-to-noise ratio by up to 3 dB compared to other standard reconstruction methods.

CONCLUSION

The proposed hybrid reconstruction algorithm, Greybox, can provide state-of-the-art performance in solving the nonlinear inverse problem of DCE-MRI. This is also the first of its kind to utilize convolutional neural network-based encodings as part of the plug-and-play priors to improve the performance of the reconstruction algorithm.

Diagnostic Anatomic Imaging for Neuroendocrine Neoplasms: Maximizing Strengths and Mitigating Weaknesses

ABSTRACT

Neuroendocrine neoplasms are a heterogeneous group of gastrointestinal and lung tumors. Their diverse clinical manifestations, variable locations, and heterogeneity present notable diagnostic challenges. This article delves into the imaging modalities vital for their detection and characterization. Computed tomography is essential for initial assessment and staging. At the same time, magnetic resonance imaging (MRI) is particularly adept for liver, pancreatic, osseous, and rectal imaging, offering superior soft tissue contrast. The article also highlights the limitations of these imaging techniques, such as MRI's inability to effectively evaluate the cortical bone and the questioned cost-effectiveness of computed tomography and MRI for detecting specific gastric lesions. By emphasizing the strengths and weaknesses of these imaging techniques, the review offers insights into optimizing their utilization for improved diagnosis, staging, and therapeutic management of neuroendocrine neoplasms.

Sporadic neurofibroma of facial nerve presenting as parotid gland tumor: a rare case report

Intraparotid gland neurofibroma is a rare benign tumor that arises from Schwann cells of the facial nerve within the parotid gland. This case report discusses a 41-year-old woman who experienced a painless preauricular swelling on her right side for over 5 years. Clinical examination and ultrasound revealed a well-defined mass in the parotid gland. The patient underwent total mass excision, resulting in transient facial nerve dysfunction but complete recovery. These tumors often manifest as solitary masses in the parotid region and may compress nearby structures, causing facial paralysis or numbness. Their diagnosis can be challenging due to similarities with other parotid gland tumors and possible associations with neurofibromatosis. Managing intraparotid tumors, including neurofibromas, involves a multidisciplinary approach with input from cytopathologists, radiologists, and surgeons.

Eosinophil-mucus interplay in severe asthma: Implications for treatment with biologicals

Airway mucus is a hydrogel with unique biophysical properties due to its primary water composition and a small proportion of large anionic glycoproteins or mucins. The predominant mucins in human mucus, MUC5AC and MUC5B, are secreted by specialized cells within the airway epithelium both in normal conditions and in response to various stimuli. Their relative proportions are correlated with specific inflammatory responses and disease mechanisms. The dysregulation of mucin expression is implicated in numerous respiratory diseases, including asthma, COPD, and cystic fibrosis, where the pathogenic role of mucus has been extensively described yet often overlooked. In airway diseases, excessive mucus production or impaired mucus clearance leads to mucus plugging, with secondary airway occlusion that contribute to airflow obstruction, asthma severity and poor control. Eosinophils and Charcot Leyden crystals in sputum contribute to the mucus burden and tenacity. Mucin may also contribute to eosinophil survival. Other mechanisms, including eosinophil-independent IL-13 release, mast-cell activation and non-type-2 (T2) cytokines, are also likely to participate in mucus pathobiology. An accurate assessment of mucus and its clinical and functional consequences require a thorough approach that includes evaluation of cellular predominance in sputum, airway cytokines and other inflammatory markers, mucus characteristics and composition and structural and functional impact measured by advanced lung imaging. This review, illustrated with clinical scenarios, provides an overview of current methods to assess mucus and its relevance to the choice of biologics to treat patients with severe asthma.

Does surgery improve quality of life in patients with ongoing- or recurrent diverticulitis; a systematic review and meta-analysis

BACKGROUND

Recurrences or persistent symptoms after an initial episode of diverticulitis are common, yet surgical treatment is rarely performed. Current guidelines lack clear recommendations on whether or not to operate, even though recent studies suggest an improved quality of life following surgery. The aim of this study is therefore to compare quality of life in patients with recurrent or ongoing diverticulitis treated conservatively versus surgically, giving a more definitive answer to the question of whether or not to operate on these patients.

METHODS

A systematic literature search was conducted in EMBASE, MEDLINE and Cochrane. Only comparative studies reporting on quality of life were included. Statistical analysis included calculation of weighted mean differences and pooled odds ratios.

RESULTS

Five studies were included; two RCT's and three retrospective observational studies. Compared to conservative treatment, the SF-36 scores were higher in the surgically treated group at each follow-up moment but only the difference in SF-36 physical scores at six months follow-up was statistically significant (MD 6.02, 95%CI 2.62-9.42). GIQLI scores were also higher in the surgical group with a MD of 14.01 (95%CI 8.15-19.87) at six months follow-up and 7.42 (95%CI 1.23-12.85) at last available follow-up. Also, at last available follow-up, significantly fewer recurrences occurred in the surgery group (OR 0.10, 95%CI 0.05-0.23, p < 0.001).

CONCLUSION

Although surgery for recurrent diverticulitis is not without risk, it might improve long-term quality of life in patients suffering from recurrent- or ongoing diverticulitis when compared to conservative treatment. Therefore, it should be considered in this patient group.

Pancreatic ductal adenocarcinoma: the latest on diagnosis, molecular profiling, and systemic treatments

Pancreatic ductal adenocarcinoma (PDAC) is currently the fourth leading cause of death in the United States and is expected to be ranked second in the next 10 years due to poor prognosis and a rising incidence. Distant metastatic PDAC is associated with the worst prognosis among the different phases of PDAC. The diagnostic options for PDAC are convenient and available for staging, tumor response evaluation, and management of resectable or borderline resectable PDAC. However, imaging is crucial in PDAC diagnosis, monitoring, resectability appraisal, and response evaluation. The advancement of medical technologies is evolving, hence the use of imaging in PDAC treatment options has grown as well as the utilization of ctDNA as a tumor marker. Treatment options for metastatic PDAC are minimal with the primary goal of therapy limited to symptom relief or palliation, especially in patients with low functional capacity at the point of diagnosis. Molecular profiling has shown promising potential solutions that would push the treatment boundaries for patients with PDAC. In this review, we will discuss the latest updates from evidence-based guidelines regarding diagnosis, therapy response evaluation, prognosis, and surveillance, as well as illustrating novel therapies that have been recently investigated for PDAC, in addition to discussing the molecular profiling advances in PDAC.

The speech neuroprosthesis

Loss of speech after paralysis is devastating, but circumventing motor-pathway injury by directly decoding speech from intact cortical activity has the potential to restore natural communication and self-expression. Recent discoveries have defined how key features of speech production are facilitated by the coordinated activity of vocal-tract articulatory and motor-planning cortical representations. In this Review, we highlight such progress and how it has led to successful speech decoding, first in individuals implanted with intracranial electrodes for clinical epilepsy monitoring and subsequently in individuals with paralysis as part of early feasibility clinical trials to restore speech. We discuss high-spatiotemporal-resolution neural interfaces and the adaptation of state-of-the-art speech computational algorithms that have driven rapid and substantial progress in decoding neural activity into text, audible speech, and facial movements. Although restoring natural speech is a long-term goal, speech neuroprostheses already have performance levels that surpass communication rates offered by current assistive-communication technology. Given this accelerated rate of progress in the field, we propose key evaluation metrics for speed and accuracy, among others, to help standardize across studies. We finish by highlighting several directions to more fully explore the multidimensional feature space of speech and language, which will continue to accelerate progress towards a clinically viable speech neuroprosthesis.

Improvements and future perspective in diagnostic tools for neuroendocrine neoplasms

INTRODUCTION

Neuroendocrine neoplasms (NENs) represent a complex group of tumors arising from neuroendocrine cells, characterized by heterogeneous behavior and challenging diagnostics. Despite advancements in medical technology, NENs present a major challenge in early detection, often leading to delayed diagnosis and variable outcomes. This review aims to provide an in-depth analysis of current diagnostic methods as well as the evolving and future directions of diagnostic strategies for NENs.

AREA COVERED

The review extensively covers the evolution of diagnostic tools for NENs, from traditional imaging and biochemical tests to advanced genomic profiling and next-generation sequencing. The emerging role of technologies such as artificial intelligence, machine learning, and liquid biopsies could improve diagnostic precision, as could the integration of imaging modalities such as positron emission tomography (PET)/magnetic resonance imaging (MRI) hybrids and innovative radiotracers.

EXPERT OPINION

Despite progress, there is still a significant gap in the early diagnosis of NENs. Bridging this diagnostic gap and integrating advanced technologies and precision medicine are crucial to improving patient outcomes. However, challenges such as low clinical awareness, limited possibility of noninvasive diagnostic tools and funding limitations for rare diseases like NENs are acknowledged.

Differentiating Gastrointestinal Stromal Tumors From Leiomyomas of Upper Digestive Tract Using Convolutional Neural Network Model by Endoscopic Ultrasonography

BACKGROUND

Gastrointestinal stromal tumors (GISTs) and leiomyomas are the most common submucosal tumors of the upper digestive tract, and the diagnosis of the tumors is essential for their treatment and prognosis. However, the ability of endoscopic ultrasonography (EUS) which could correctly identify the tumor types is limited and closely related to the knowledge, operational level, and experience of the endoscopists. Therefore, the convolutional neural network (CNN) is used to assist endoscopists in determining GISTs or leiomyomas with EUS.

MATERIALS AND METHODS

A model based on CNN was constructed according to GoogLeNet architecture to distinguish GISTs or leiomyomas. All EUS images collected from this study were randomly sampled and divided into training set (n=411) and testing set (n=103) in a ratio of 4:1. The CNN model was trained by EUS images from the training set, and the testing set was utilized to evaluate the performance of the CNN model. In addition, there were some comparisons between endoscopists and CNN models.

RESULTS

It was shown that the sensitivity and specificity in identifying leiomyoma were 95.92%, 94.44%, sensitivity and specificity in identifying GIST were 94.44%, 95.92%, and accuracy in total was 95.15% of the CNN model. It indicates that the diagnostic accuracy of the CNN model is equivalent to skilled endoscopists, or even higher than them.

CONCLUSION

While identifying GIST or leiomyoma, the performance of CNN model was robust, which is highlighting its promising role in supporting less-experienced endoscopists and reducing interobserver agreement.

A World Update of Progress in Lower Extremity Transplantation: What's Hot and What's Not

ABSTRACT

The field of vascularized composite allotransplantation (VCA) is the new frontier of solid organ transplantation (SOT). VCA spans life-enhancing/life-changing procedures such as upper extremity, craniofacial (including eye), laryngeal, tracheal, abdominal wall, penis, and lower extremity transplants. VCAs such as uterus transplants are life giving unlike any other SOT. Of all VCAs that have shown successful intermediate- to long-term graft survival with functional and immunologic outcomes, lower extremity VCAs have remained largely underexplored. Lower extremity transplantation (LET) can offer patients with improved function compared to the use of conventional prostheses, reducing concerns of phantom limb pain and stump complications, and offer an option for eligible amputees that either fail prosthetic rehabilitation or do not adapt to prosthetics. Nevertheless, these benefits must be carefully weighed against the risks of VCA, which are not trivial, including the adverse effects of lifelong immunosuppression, extremely challenging perioperative care, and delayed nerve regeneration. There have been 5 lower extremity transplants to date, ranging from unilateral or bilateral to quadrimembral, progressively increasing in risk that resulted in fatalities in 3 of the 5 cases, emphasizing the inherent risks. The advantages of LET over prosthetics must be carefully weighed, demanding rigorous candidate selection for optimal outcomes.

A Histological and Biomechanical Analysis of Human Acellular Dermis (HAD) Created Using a Novel Processing and Preservation Technique

Background

Large and complex defects requiring reconstruction are challenging for orthopaedic surgeons. The use of human acellular dermal (HAD) matrices to augment large soft tissue defects such as those seen in massive rotator cuff tears, knee extensor mechanism failures and neglected Tendo-Achilles tears has proven to be a valuable tool in surgeons reconstructive armamentarium. Different methods for allograft decellularization and preservation alter the native properties of the scaffold. Traditional processing and preservation methods have shown to have drawbacks that preclude its widespread use. Some of the common issues include inferior biomechanical properties, the risk of rejection, limited customization, difficulty in storing and transporting, the requirement of pre-operative preparation, and last but not the least increased cost.

Methods

We describe a novel processing and preservation method utilizing a two-step non-denaturing decellularization method coupled with preservation using a water-sequestering agent (glycerol) to remove immunogenic components while retaining biomechanical properties. The efficiency of this novel process was compared with the traditional freeze-drying method and verified by histological evaluation and biomechanical strength analysis.

Results

The absence of cellular components and matrix integrity in hematoxylin and eosin-stained glycerol-preserved HAD (gly-HAD) samples compared to freeze-dried HAD (FD-HAD) demonstrated effective yet gentle decellularization. Biomechanical strength analysis revealed that gly-HADs are stronger with an ultimate tensile load to the failure strength of 210 N compared to FD-HAD (124N). The gly-HADs were found to have an optimal suture-retention strength of 126 N. Finally, sterility testing of the resultant grafts was checked to ensure a sterility assurance level of 10-6 to establish implantability.

Conclusion

The novel processing and preservation technique is described in this paper to create a Human Acellular Dermis with higher biomechanical strength and superior histological characteristics. The processing and preservation technique ensured high sterility assurance levels to establish implantability.

Prevalence and clinical implications of coronary artery calcium scoring on non-gated thoracic computed tomography: a systematic review and meta-analysis

OBJECTIVES

Coronary artery calcifications (CACs) indicate the presence of coronary artery disease. CAC can be found on thoracic computed tomography (CT) conducted for non-cardiac reasons. This systematic review and meta-analysis of non-gated thoracic CT aims to assess the clinical impact and prevalence of CAC.

METHODS

Online databases were searched for articles assessing prevalence, demographic characteristics, accuracy and prognosis of incidental CAC on non-gated thoracic CT. Meta-analysis was performed using a random effects model.

RESULTS

A total of 108 studies (113,406 patients) were included (38% female). Prevalence of CAC ranged from 2.7 to 100% (pooled prevalence 52%, 95% confidence interval [CI] 46-58%). Patients with CAC were older (pooled standardised mean difference 0.88, 95% CI 0.65-1.11, p < 0.001), and more likely to be male (pooled odds ratio [OR] 1.95, 95% CI 1.55-2.45, p < 0.001), with diabetes (pooled OR 2.63, 95% CI 1.95-3.54, p < 0.001), hypercholesterolaemia (pooled OR 2.28, 95% CI 1.33-3.93, p < 0.01) and hypertension (pooled OR 3.89, 95% CI 2.26-6.70, p < 0.001), but not higher body mass index or smoking. Non-gated CT assessment of CAC had excellent agreement with electrocardiogram-gated CT (pooled correlation coefficient 0.96, 95% CI 0.92-0.98, p < 0.001). In 51,582 patients, followed-up for 51.6 ± 27.4 months, patients with CAC had increased all cause mortality (pooled relative risk [RR] 2.13, 95% CI 1.57-2.90, p = 0.004) and major adverse cardiovascular events (pooled RR 2.91, 95% CI 2.26-3.93, p < 0.001). When CAC was present on CT, it was reported in between 18.6% and 93% of reports.

CONCLUSION

CAC is a common, but underreported, finding on non-gated CT with important prognostic implications.

CLINICAL RELEVANCE STATEMENT

Coronary artery calcium is an important prognostic indicator of cardiovascular disease. It can be assessed on non-gated thoracic CT and is a commonly underreported finding. This represents a significant population where there is a potential missed opportunity for lifestyle modification recommendations and preventative therapies. This study aims to highlight the importance of reporting incidental coronary artery calcium on non-gated thoracic CT.

KEY POINTS

• Coronary artery calcification is a common finding on non-gated thoracic CT and can be reliably identified compared to gated-CT. • Coronary artery calcification on thoracic CT is associated with an increased risk of all cause mortality and major adverse cardiovascsular events. • Coronary artery calcification is frequently not reported on non-gated thoracic CT.

Association between Personal Abiotic Airborne Exposures and Body Composition Changes among Healthy Adults (60-69 Years Old): A Combined Exposome-Wide and Lipidome Mediation Approach from the China BAPE Study

BACKGROUND

Evidence suggested that abiotic airborne exposures may be associated with changes in body composition. However, more evidence is needed to identify key pollutants linked to adverse health effects and their underlying biomolecular mechanisms, particularly in sensitive older adults.

OBJECTIVES

Our research aimed to systematically assess the relationship between abiotic airborne exposures and changes in body composition among healthy older adults, as well as the potential mediating mechanisms through the serum lipidome.

METHODS

From September 2018 to January 2019, we conducted a monthly survey among 76 healthy adults (60-69 years old) in the China Biomarkers of Air Pollutant Exposure (BAPE) study, measuring their personal exposures to 632 abiotic airborne pollutions using MicroPEM and the Fresh Air wristband, 18 body composition indicators from the InBody 770 device, and lipidomics from venous blood samples. We used an exposome-wide association study (ExWAS) and deletion/substitution/addition (DSA) model to unravel complex associations between exposure to contaminant mixtures and body composition, a Bayesian kernel machine regression (BKMR) model to assess the overall effect of key exposures on body composition, and mediation analysis to identify lipid intermediators.

RESULTS

The ExWAS and DSA model identified that 2,4,5-T methyl ester (2,4,5-TME), 9,10-Anthracenedione (ATQ), 4b,8-dimethyl-2-isopropylphenanthrene, and 4b,5,6,7,8,8a,9,10-octahydro-(DMIP) were associated with increased body fat mass (BFM), fat mass indicators (FMI), percent body fat (PBF), and visceral fat area (VFA) in healthy older adults [Bonferroni-Hochberg false discovery rate ( FD R BH ) < 0.05 ]. The BKMR model demonstrated a positive correlation between contaminants (anthracene, ATQ, copaene, di-epi-α -cedrene, and DMIP) with VFA. Mediation analysis revealed that phosphatidylcholine [PC, PC(16:1e/18:1), PC(16:2e/18:0)] and sphingolipid [SM, SM(d18:2/24:1)] mediated a significant portion, ranging from 12.27% to 26.03% (p-value < 0.05 ), of the observed increase in VFA.

DISCUSSION

Based on the evidence from multiple model results, ATQ and DMIP were statistically significantly associated with the increased VFA levels of healthy older adults, potentially regulated through lipid intermediators. These findings may have important implications for identifying potentially harmful environmental chemicals and developing targeted strategies for the control and prevention of chronic diseases in the future, particularly as the global population is rapidly aging. https://doi.org/10.1289/EHP13865.

Application of radiomics model based on ultrasound image features in the prediction of carpal tunnel syndrome severity

OBJECTIVE

The aim of our study is to develop and validate a radiomics model based on ultrasound image features for predicting carpal tunnel syndrome (CTS) severity.

METHODS

This retrospective study included 237 CTS hands (106 for mild symptom, 68 for moderate symptom and 63 for severe symptom). There were no statistically significant differences among the three groups in terms of age, gender, race, etc. The data set was randomly divided into a training set and a test set in a ratio of 7:3. Firstly, a senior musculoskeletal ultrasound expert measures the cross-sectional area of median nerve (MN) at the scaphoid-pisiform level. Subsequently, a recursive feature elimination (RFE) method was used to identify the most discriminative radiomic features of each MN at the entrance of the carpal tunnel. Eventually, a random forest model was employed to classify the selected features for prediction. To evaluate the performance of the model, the confusion matrix, receiver operating characteristic (ROC) curves, and F1 values were calculated and plotted correspondingly.

RESULTS

The prediction capability of the radiomics model was significantly better than that of ultrasound measurements when 10 robust features were selected. The training set performed perfect classification with 100% accuracy for all participants, while the testing set performed accurate classification of severity for 76.39% of participants with F1 values of 80.00, 63.40, and 84.80 for predicting mild, moderate, and severe CTS, respectively. Comparably, the F1 values for mild, moderate, and severe CTS predicted based on the MN cross-sectional area were 76.46, 57.78, and 64.00, respectively..

CONCLUSION

This radiomics model based on ultrasound images has certain value in distinguishing the severity of CTS, and was slightly superior to using only MN cross-sectional area for judgment. Although its diagnostic efficacy was still inferior to that of neuroelectrophysiology. However, this method was non-invasive and did not require additional costs, and could provide additional information for clinical physicians to develop diagnosis and treatment plans.

Formal Radiologist Interpretations of Intraoperative Spine Radiographs Have Low Clinical Value

STUDY DESIGN

Retrospective cohort.

OBJECTIVE

To evaluate the clinical relevance, usefulness, and financial implications of intraoperative radiograph interpretation by radiologists in spine surgery.

SUMMARY OF BACKGROUND DATA

Due to rising health care costs, spine surgery is under scrutiny to maximize value-based care. Formal radiographic analysis remains a potential source of unnecessary health care costs, especially for intraoperative radiographs.

MATERIALS AND METHODS

A retrospective cohort analysis was performed on all adult elective spine surgeries at a single institution between July 2020 and July 2021. Demographic and radiographic data were collected, including intraoperative localization and post-instrumentation radiographs. Financial data were obtained through the institution's price estimator. Radiographic characteristics included time from radiographic imaging to completion of radiologist interpretation report, completion of radiologist interpretation report before the conclusion of surgical procedure, clinical relevance, and clinical usefulness. Reports were considered clinically relevant if the spinal level of the procedure was described and clinically useful if completed before the conclusion of the procedure and deemed clinically relevant.

RESULTS

Four hundred eighty-one intraoperative localization and post-instrumentation radiographs from 360 patients revealed a median delay of 128 minutes between imaging and completion of the interpretive report. Only 38.9% of reports were completed before the conclusion of surgery. There were 79.4% deemed clinically relevant and only 33.5% were clinically useful. Localization reports were completed more frequently before the conclusion of surgery (67.2% vs. 34.4%) but with lower clinical relevance (90.1% vs. 98.5%) and clinical usefulness (60.3% vs. 33.6%) than post-instrumentation reports. Each patient was charged $32 to $34 for the interpretation fee, cumulating a minimum total cost of $15,392.

CONCLUSIONS

Formal radiographic interpretation of intraoperative spine radiographs was of low clinical utility for spine surgeons. Institutions should consider optimizing radiology workflows to improve timeliness and clinical relevance or evaluate the necessity of reflexive consultation to radiology for intraoperative imaging interpretation to ensure that value-based care is maximized during spine surgeries.

LEVEL OF EVIDENCE

3.

Evaluation of Ethos intelligent optimization engine for left locally advanced breast cancer

Purpose

To evaluate the feasibility to use a standard Ethos planning template to treat left-sided breast cancer with regional lymph nodes.

Material/Methods

The tuning cohort of 5 patients was used to create a planning template. The validation cohort included 15 patients treated for a locally advanced left breast cancer randomly enrolled. The Ethos planning template was tuned using standard 3 partial arc VMAT and two collimator rotation configurations: 45/285/345° and 30/60/330°. Re-planning was performed automatically using the template without editing. The study was conducted with a schedule of 42.3 Gy in 18 fractions to the breast/chestwall, internal mammary chain (IMC) and regional lymph nodes ("Nodes"). The PTV was defined as a 3D extension of the CTV with a margin of 7 mm, excluding the 5mm below the skin. The manual treatment plans were performed using Eclipse treatment planning system with AAA and PO algorithms (v15.6) and a manual arc VMAT configuration and imported in Ethos TPS (v1.1) for a dose calculation with Ethos Acuros algorithm. The automated plans were compared with the manual plans using PTV and CTV coverage, homogeneity and conformity indices (HI and CN) and doses to organs at risk (OAR) via DVH metrics. For each plan, the patient quality assurance (QA) were performed using Mobius3D and gamma index. Finally, two breast radiation oncologists performed a blinded assessment of the clinical acceptability of each of the three plans (manual and automated) for each patient.

Results

The manual and automated plans provided suitable treatment planning as regards dose constraints. The dosimetric comparison showed the CTV_breast D99% were significantly improved with both automated plans (p< 0,002) while PTV coverage was comparable. The doses to the organs at risk were equivalent for the three plans. Concerning treatment delivery, the Ethos-45° and Ethos-30° plans led to an increase in MUs compared to the manual plans, without affecting the beam on time. The average gamma index pass rates remained consistently above 98% regardless of the type of plan utilized. In the blinded evaluation, clinicians 1 and 2 assessed 13 out of 15 plans for Ethos 45° and 11 out of 15 plans for Ethos 30° as clinically acceptable.

Conclusion

Using a standard planning template for locally advanced breast cancer, the Ethos TPS provided automated plans that were clinically acceptable and comparable in quality to manually generated plans. Automated plans also dramatically reduce workflow and operator variability.

Robustness of apparent diffusion coefficient-based lymph node classification for diagnosis of prostate cancer metastasis

OBJECTIVES

The aim of this proof-of-principle study combining data analysis and computer simulation was to evaluate the robustness of apparent diffusion coefficient (ADC) values for lymph node classification in prostate cancer under conditions comparable to clinical practice.

MATERIALS AND METHODS

To assess differences in ADC and inter-rater variability, ADC values of 359 lymph nodes in 101 patients undergoing simultaneous prostate-specific membrane antigen (PSMA)-PET/MRI were retrospectively measured by two blinded readers and compared in a node-by-node analysis with respect to lymph node status. In addition, a phantom and 13 patients with 86 lymph nodes were prospectively measured on two different MRI scanners to analyze inter-scanner agreement. To estimate the diagnostic quality of the ADC in real-world application, a computer simulation was used to emulate the blurring caused by scanner and reader variability. To account for intra-individual correlation, the statistical analyses and simulations were based on linear mixed models.

RESULTS

The mean ADC of lymph nodes showing PSMA signals in PET was markedly lower (0.77 × 10-3 mm2/s) compared to inconspicuous nodes (1.46 × 10-3 mm2/s, p < 0.001). High inter-reader agreement was observed for ADC measurements (ICC 0.93, 95%CI [0.92, 0.95]). Good inter-scanner agreement was observed in the phantom study and confirmed in vivo (ICC 0.89, 95%CI [0.84, 0.93]). With a median AUC of 0.95 (95%CI [0.92, 0.97]), the simulation study confirmed the diagnostic potential of ADC for lymph node classification in prostate cancer.

CONCLUSION

Our model-based simulation approach implicates a high potential of ADC for lymph node classification in prostate cancer, even when inter-rater and inter-scanner variability are considered.

CLINICAL RELEVANCE STATEMENT

The ADC value shows a high diagnostic potential for lymph node classification in prostate cancer. The robustness to scanner and reader variability implicates that this easy to measure and widely available method could be readily integrated into clinical routine.

KEY POINTS

• The diagnostic value of the apparent diffusion coefficient (ADC) for lymph node classification in prostate cancer is unclear in the light of inter-rater and inter-scanner variability. • Metastatic and inconspicuous lymph nodes differ significantly in ADC, resulting in a high diagnostic potential that is robust to inter-scanner and inter-rater variability. • ADC has a high potential for lymph node classification in prostate cancer that is maintained under conditions comparable to clinical practice.

Cervical cancer segmentation based on medical images: a literature review

Background and Objective

Cervical cancer clinical target volume (CTV) outlining and organs at risk segmentation are crucial steps in the diagnosis and treatment of cervical cancer. Manual segmentation is inefficient and subjective, leading to the development of automated or semi-automated methods. However, limitation of image quality, organ motion, and individual differences still pose significant challenges. Apart from numbers of studies on the medical images' segmentation, a comprehensive review within the field is lacking. The purpose of this paper is to comprehensively review the literatures on different types of medical image segmentation regarding cervical cancer and discuss the current level and challenges in segmentation process.

Methods

As of May 31, 2023, we conducted a comprehensive literature search on Google Scholar, PubMed, and Web of Science using the following term combinations: "cervical cancer images", "segmentation", and "outline". The included studies focused on the segmentation of cervical cancer utilizing computed tomography (CT), magnetic resonance (MR), and positron emission tomography (PET) images, with screening for eligibility by two independent investigators.

Key Content and Findings

This paper reviews representative papers on CTV and organs at risk segmentation in cervical cancer and classifies the methods into three categories based on image modalities. The traditional or deep learning methods are comprehensively described. The similarities and differences of related methods are analyzed, and their advantages and limitations are discussed in-depth. We have also included experimental results by using our private datasets to verify the performance of selected methods. The results indicate that the residual module and squeeze-and-excitation blocks module can significantly improve the performance of the model. Additionally, the segmentation method based on improved level set demonstrates better segmentation accuracy than other methods.

Conclusions

The paper provides valuable insights into the current state-of-the-art in cervical cancer CTV outlining and organs at risk segmentation, highlighting areas for future research.

Current Diagnostic Techniques for Pneumonia: A Scoping Review

Community-acquired pneumonia is one of the most lethal infectious diseases, especially for infants and the elderly. Given the variety of causative agents, the accurate early detection of pneumonia is an active research area. To the best of our knowledge, scoping reviews on diagnostic techniques for pneumonia are lacking. In this scoping review, three major electronic databases were searched and the resulting research was screened. We categorized these diagnostic techniques into four classes (i.e., lab-based methods, imaging-based techniques, acoustic-based techniques, and physiological-measurement-based techniques) and summarized their recent applications. Major research has been skewed towards imaging-based techniques, especially after COVID-19. Currently, chest X-rays and blood tests are the most common tools in the clinical setting to establish a diagnosis; however, there is a need to look for safe, non-invasive, and more rapid techniques for diagnosis. Recently, some non-invasive techniques based on wearable sensors achieved reasonable diagnostic accuracy that could open a new chapter for future applications. Consequently, further research and technology development are still needed for pneumonia diagnosis using non-invasive physiological parameters to attain a better point of care for pneumonia patients.

Unveiling May-Thurner Syndrome in a Case of Recurrent Deep Venous Thrombosis With Bilateral Pulmonary Embolism

May-Thurner syndrome (MTS) is a rare cause of deep venous thrombosis (DVT), characterized by the external compression of the left common iliac vein by the right common iliac artery against bony structures. Risk factors for MTS include female sex (postpartum, multiparous, and using oral contraceptive pills), spinal abnormalities like scoliosis, prior aortoiliac vascular stent placement, dehydration, and hypercoagulability. MTS patients with partial obstruction can be asymptomatic, but progression to extensive symptomatic DVT and/or chronic venous insufficiency can occur. MTS can be diagnosed by non-invasive imaging studies including ultrasound (US), computed tomography (CT) scan, magnetic resonance imaging (MRI), venogram, catheter-based venogram, and intravascular US. For MTS patients with moderate to severe symptoms, we suggest thrombectomy, angioplasty, and stenting of the affected segment. In this case report, we highlight a 44-year-old male with a recent diagnosis of left-sided DVT on apixaban who presented with worsening leg swelling. DVT, pulmonary embolism (PE), and MTS were diagnosed with a lower extremity US, chest CT angiography, and abdominal/pelvic CT scan and venography, respectively. The patient underwent interventional radiology-guided local thrombolysis, thrombectomy, and venoplasty along with stent placement in the left common iliac vein. Subsequently, the patient was discharged on rivaroxaban.

Logistic regression analysis of multiple rapid admission hematological indicators to determine the risk of osteomyelitis in infected children

To analyze the differences of multiple rapid admission hematological indicators between children with acute osteomyelitis (AO) and children with other orthopedic infectious diseases and clarify the characteristics of admission inspection hematological indicators of children with AO. Retrospective analysis of this pilot study was proceeded on 144 children with limbs infectious diseases, who were treated in our hospital. According to their final diagnosis, they were divided into osteomyelitis group (n = 57) and non-osteomyelitis group (n = 87). Case data were collected, including sex, age, body temperature, white blood cell (WBC), C-reactive protein (CRP), etc. The differences in these indexes between the two groups of patients were compared, and then, the index with significant differences was selected for univariate and multivariate logistic regression analysis. There were significant differences between the two groups in age, body temperature, CRP, ESR, fibrinogen, total bilirubin, alanine aminotransferase, aspartate aminotransferase (AST), glutamyl transpeptidase, creatinine, PCT, albumin (ALB), and ALB globulin ratio (A/G) ( P  < 0.05). The results of univariate and multivariate logistic regression analysis showed that the age of ≥5 years (4.592, 1.711-12.324), WBC (>1.5 × 10 9 /L) (0.271, 0.102-0.718), ESR (>50 mm/h) (6.410, 2.291-17.936), PCT (>0.06 µg/L) (3.139, 1.066-9.243), and AST (>40 U/L) (11.174, 1.718-72.666) was an independent risk factor of AO in children with orthopedic infectious diseases ( P  < 0.05). For newly admitted children with orthopedic infectious diseases, if the age ≥ 5 years, WBC ≤ 1.5 × 10 9 /L, ESR > 50 mm/h, PCT > 0.06 µg/L, and AST > 40 U/L, the occurrence of AO should be alerted.

Comparison of radiological and clinical characteristics of COVID-19 positive and negative ischemic stroke patients undergoing revascularization: A single-centre Turkish study

OBJECTIVE

We aimed to compare the radiological and clinical characteristics of COVID-19-positive and -negative acute ischemic stroke (AIS) patients who underwent revascularization and to evaluate whether COVID-19 has an effect on revascularization and outcome in AIS patients with COVID-19 infection.

METHODS

Consecutive COVID-19 positive and negative AIS patients who underwent intravenous thrombolysis and/or endovascular therapy in our hospital between March 2020 and February 2022 were included in this study. Our study is retrospective and 23 COVID-19 positive patients and 108 COVID-19 negative patients were compared in terms of radiological and clinical characteristics.

RESULTS

Hypertension was lower in the COVID-19 positive ischemic stroke group (p=0.029). Admission NIHSS score was higher in COVID-19 positive patients (p=0.041). ASPECTS was found to be lower in COVID-19 positive ischemic stroke patients (p=0.019). The rate of hyperdense artery sign differed between groups (p=0.014) and was higher in the COVID-19 positive ischemic stroke group. The incidence of multi-vessel occlusion was found to be significantly higher in the COVID-19-positive ischemic stroke group (p=0.002). In terms of prognostic features, only the 3-month good outcome rate was statistically significantly lower in the COVID-19-positive ischemic stroke group (p=0.011).

CONCLUSION

This study found that radiologically, COVID-19 may be associated with lower ASPECTS in ischemic stroke patients receiving revascularization treatment and may predispose to multivessel occlusion and hyperdense artery sign. Clinically, COVID-19 may be associated with a more severe initial presentation and worse prognosis at 3 months in ischemic stroke patients undergoing revascularization, but may not affect long-term mortality.

AI-enabled cardiac chambers volumetry in coronary artery calcium scans (AI-CACTM) predicts heart failure and outperforms NT-proBNP: The multi-ethnic study of Atherosclerosis

INTRODUCTION

Coronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC score that is not currently reported. We recently reported that artificial intelligence (AI)-enabled cardiac chambers volumetry in CAC scans (AI-CAC™) predicted incident atrial fibrillation in the Multi-Ethnic Study of Atherosclerosis (MESA). In this study, we investigated the performance of AI-CAC cardiac chambers for prediction of incident heart failure (HF).

METHODS

We applied AI-CAC to 5750 CAC scans of asymptomatic individuals (52% female, White 40%, Black 26%, Hispanic 22% Chinese 12%) free of known cardiovascular disease at the MESA baseline examination (2000-2002). We used the 15-year outcomes data and compared the time-dependent area under the curve (AUC) of AI-CAC volumetry versus NT-proBNP, Agatston score, and 9 known clinical risk factors (age, gender, diabetes, current smoking, hypertension medication, systolic and diastolic blood pressure, LDL, HDL for predicting incident HF over 15 years.

RESULTS

Over 15 years of follow-up, 256 HF events accrued. The time-dependent AUC [95% CI] at 15 years for predicting HF with AI-CAC all chambers volumetry (0.86 [0.82,0.91]) was significantly higher than NT-proBNP (0.74 [0.69, 0.77]) and Agatston score (0.71 [0.68, 0.78]) (p ​< ​0.0001), and comparable to clinical risk factors (0.85, p ​= ​0.4141). Category-free Net Reclassification Index (NRI) [95% CI] adding AI-CAC LV significantly improved on clinical risk factors (0.32 [0.16,0.41]), NT-proBNP (0.46 [0.33,0.58]), and Agatston score (0.71 [0.57,0.81]) for HF prediction at 15 years (p ​< ​0.0001).

CONCLUSION

AI-CAC volumetry significantly outperformed NT-proBNP and the Agatston CAC score, and significantly improved the AUC and category-free NRI of clinical risk factors for incident HF prediction.

Frequently Encountered Artifacts in the Application of Dual-Energy Computed Tomography to Cardiovascular Imaging for Urate Crystals in Gout: A Matched-Control Study

OBJECTIVE

There is surging interest in using dual-energy computed tomography (DECT) to identify cardiovascular monosodium urate (MSU) deposits in patients with gout. We sought to examine the prevalence and characterization of cardiovascular DECT artifacts using non-electrocardiogram (EKG)-gated DECT pulmonary angiograms.

METHODS

We retrospectively reviewed non-EKG-gated DECT pulmonary angiograms performed on patients with and without gout at a single academic center. We noted the presence and locations of vascular green colorization using the default postprocessing two-material decomposition algorithm for MSU. The high- and low-energy grayscale images and advanced DECT measurements were used to determine whether they were true findings or artifacts. We classified artifacts into five categories: streak, contrast medium mixing, misregistration due to motion, foreign body, and noise.

RESULTS

Our study included CT scans from 48 patients with gout and 48 age- and sex-matched controls. The majority of patients were male with a mean age of 67 years. Two independent observers attributed all areas of vascular green colorization to artifacts. The most common types of artifacts were streak (56% vs 57% between patients and controls, respectively) and contrast medium mixing (51% vs 65%, respectively). Whereas some of the default DECT measurements of cardiovascular green colorization were consistent with values reported for subcutaneous tophi, advanced DECT measurements were not consistent with that of tophi.

CONCLUSION

Artifacts that could be misconstrued as cardiovascular MSU deposits were commonly identified in patients with and without gout on non-EKG-gated DECT pulmonary angiograms. These artifacts can inform future vascular DECT studies on patients with gout to minimize false-positive findings.

Evaluation of the performance of both machine learning models using PET and CT radiomics for predicting recurrence following lung stereotactic body radiation therapy: A single-institutional study

PURPOSE

Predicting recurrence following stereotactic body radiotherapy (SBRT) for non-small cell lung cancer provides important information for the feasibility of the individualized radiotherapy and allows to select the appropriate treatment strategy based on the risk of recurrence. In this study, we evaluated the performance of both machine learning models using positron emission tomography (PET) and computed tomography (CT) radiomic features for predicting recurrence after SBRT.

METHODS

Planning CT and PET images of 82 non-small cell lung cancer patients who performed SBRT at our hospital were used. First, tumors were delineated on each CT and PET of each patient, and 111 unique radiomic features were extracted, respectively. Next, the 10 features were selected using three different feature selection algorithms, respectively. Recurrence prediction models based on the selected features and four different machine learning algorithms were developed, respectively. Finally, we compared the predictive performance of each model for each recurrence pattern using the mean area under the curve (AUC) calculated following the 0.632+ bootstrap method.

RESULTS

The highest performance for local recurrence, regional lymph node metastasis, and distant metastasis were observed in models using Support vector machine with PET features (mean AUC = 0.646), Naive Bayes with PET features (mean AUC = 0.611), and Support vector machine with CT features (mean AUC = 0.645), respectively.

CONCLUSIONS

We comprehensively evaluated the performance of prediction model developed for recurrence following SBRT. The model in this study would provide information to predict the recurrence pattern and assist in making treatment strategies.

Systemic inflammation, lifestyle behaviours and dementia: A 10-year follow-up investigation

Objectives

Lifestyle behaviours have been linked to dementia incidence, but their cumulative impact on dementia and the underlying mechanisms remain poorly understood. This study investigated the association of co-occurring lifestyle behaviours with dementia incidence and the mediating role of systemic inflammation in this association.

Methods

The sample comprised 3131 participants (55.2% female) from the English Longitudinal Study of Ageing aged 52-92 years at baseline (2008/09). Self-reported baseline lifestyle behaviours (alcohol intake, fruit and vegetable consumption, smoking, physical activity, sleep duration, social engagement, and cognitive activity) were summed to derive an index of lifestyle behaviours, ranging from 0 to 7, with higher scores denoting a higher number of health-risk behaviours. Incident dementia cases (n = 130, 4.2%) were identified through doctor-diagnosed dementia, informant interviews, and health records between 2014/15 and 2018/19. Systemic inflammation was measured through fasting plasma concentrations of C-reactive protein in 2012/13.

Results

Binary logistic regression models indicated that the odds of subsequent dementia increased by 1.19 for each additional health-risk behaviour (95% confidence intervals: 1.04, 1.37, p = 0.014) after adjusting for age, sex, ethnicity, wealth, education, marital status, body mass index, coronary heart disease, hypertension, stroke, and depression. However, this association was not mediated by C-reactive protein.

Conclusions

Co-occurring health-risk behaviours were associated with higher dementia incidence up to 10 years later, underscoring the importance of modifying health-risk behaviours for the prevention of dementia. Systemic inflammation did not explain the association between behaviours and dementia.

Association between clinical symptoms and MRI image findings in symptomatic temporomandibular joint (TMJ) disease: A systematic review

To evaluate the association between clinical signs and symptoms of temporomandibular joint (TMJ) and magnetic resonance image (MRI) findings in patients with temporomandibular disorders (TMD). Relevant articles on humans over 18 years of age were obtained from five databases (Ovid MEDLINE, PubMed, Scopus, Web of Science, and Google Scholar) up to August 2022. Risk of bias assessment was completed using the Joanna Briggs Institute critical appraisal tools. The GRADEpro (Grading of Recommendations, Assessment, Development, and Evaluation) instrument was applied to assess the level of evidence across studies in a GRADE Summary of Findings table. In total, 22 studies were included in this systematic review. Of these, 11 studies highlighted that joint pain was positively associated with particular MRI findings: joint effusion, bone marrow edema, disk displacement with/without reduction, and condylar erosion. Masticatory muscle pain was found to have a strong positive correlation with disk displacement in four studies. Five studies found no significant association between MRI findings and masticatory muscle pain. Range of motion and MRI findings were examined in six studies. Limited mouth opening was found to be correlated with disk displacement in five studies. Of the 11 studies evaluating the correlation between joint noise and MRI findings, eight reported a significant association between disk displacement and TMJ noise. The results suggested that patients with joint pain and limited range of motion may benefit from MRI. Patients exhibiting primarily muscle pain are unlikely to benefit clinically from MRI. Future studies with improved quality are warranted.

In vivo endoscopic optical coherence elastography based on a miniature probe

Optical coherence elastography (OCE) is a functional extension of optical coherence tomography (OCT). It offers high-resolution elasticity assessment with nanoscale tissue displacement sensitivity and high quantification accuracy, promising to enhance diagnostic precision. However, in vivo endoscopic OCE imaging has not been demonstrated yet, which needs to overcome key challenges related to probe miniaturization, high excitation efficiency and speed. This study presents a novel endoscopic OCE system, achieving the first endoscopic OCE imaging in vivo. The system features the smallest integrated OCE probe with an outer diameter of only 0.9 mm (with a 1.2-mm protective tube during imaging). Utilizing a single 38-MHz high-frequency ultrasound transducer, the system induced rapid deformation in tissues with enhanced excitation efficiency. In phantom studies, the OCE quantification results match well with compression testing results, showing the system's high accuracy. The in vivo imaging of the rat vagina demonstrated the system's capability to detect changes in tissue elasticity continually and distinguish between normal tissue, hematomas, and tissue with increased collagen fibers precisely. This research narrows the gap for the clinical implementation of the endoscopic OCE system, offering the potential for the early diagnosis of intraluminal diseases.

Strategies for improving image quality in prostate MRI

Prostate magnetic resonance imaging (MRI) stands as the cornerstone in diagnosing prostate cancer (PCa), offering superior detection capabilities while minimizing unnecessary biopsies. Despite its critical role, global disparities in MRI diagnostic performance persist, stemming from variations in image quality and radiologist expertise. This manuscript reviews the challenges and strategies for enhancing image quality in prostate MRI, spanning patient preparation, MRI unit optimization, and radiology team engagement. Quality assurance (QA) and quality control (QC) processes are pivotal, emphasizing standardized protocols, meticulous patient evaluation, MRI unit workflow, and radiology team performance. Additionally, artificial intelligence (AI) advancements offer promising avenues for improving image quality and reducing acquisition times. The Prostate-Imaging Quality (PI-QUAL) scoring system emerges as a valuable tool for assessing MRI image quality. A comprehensive approach addressing technical, procedural, and interpretative aspects is essential to ensure consistent and reliable prostate MRI outcomes.

Central Vein Sign and Paramagnetic Rim Lesions: Susceptibility Changes in Brain Tissues and Their Implications for the Study of Multiple Sclerosis Pathology

Multiple sclerosis (MS) is the most common acquired inflammatory and demyelinating disease in adults. The conventional diagnostic of MS and the follow-up of inflammatory activity is based on the detection of hyperintense foci in T2 and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and lesions with brain-blood barrier (BBB) disruption in the central nervous system (CNS) parenchyma. However, T2/FLAIR hyperintense lesions are not specific to MS and the MS pathology and inflammatory processes go far beyond focal lesions and can be independent of BBB disruption. MRI techniques based on the magnetic susceptibility properties of the tissue, such as T2*, susceptibility-weighted images (SWI), and quantitative susceptibility mapping (QSM) offer tools for advanced MS diagnostic, follow-up, and the assessment of more detailed features of MS dynamic pathology. Susceptibility-weighted techniques are sensitive to the paramagnetic components of biological tissues, such as deoxyhemoglobin. This capability enables the visualization of brain parenchymal veins. Consequently, it presents an opportunity to identify veins within the core of multiple sclerosis (MS) lesions, thereby affirming their venocentric characteristics. This advancement significantly enhances the accuracy of the differential diagnostic process. Another important paramagnetic component in biological tissues is iron. In MS, the dynamic trafficking of iron between different cells, such as oligodendrocytes, astrocytes, and microglia, enables the study of different stages of demyelination and remyelination. Furthermore, the accumulation of iron in activated microglia serves as an indicator of latent inflammatory activity in chronic MS lesions, termed paramagnetic rim lesions (PRLs). PRLs have been correlated with disease progression and degenerative processes, underscoring their significance in MS pathology. This review will elucidate the underlying physical principles of magnetic susceptibility and their implications for the formation and interpretation of T2*, SWI, and QSM sequences. Additionally, it will explore their applications in multiple sclerosis (MS), particularly in detecting the central vein sign (CVS) and PRLs, and assessing iron metabolism. Furthermore, the review will discuss their role in advancing early and precise MS diagnosis and prognostic evaluation, as well as their utility in studying chronic active inflammation and degenerative processes.

Incidental 68Ga-PSMA Uptake in the Benign Enchondroma-A Rare Finding on 68Ga-PSMA PET/CT

ABSTRACT

68Ga-PSMA (prostate-specific membrane antigen)-HBED-CC (N,N'-bis[2-hydroxy-5-(carboxyethyl)benzyl]ethylenediamine-N,N'-diacetic acid) PET/CT is the new advancement in oncological imaging. However, false-positive uptake can be seen in benign lesions on 68Ga-PSMA PET/CT. We describe a rare case of intense 68Ga-PSMA uptake in an enchondroma confirmed on MRI.

Integrated multi-omics analysis and machine learning to refine molecular subtypes, prognosis, and immunotherapy in lung adenocarcinoma

Lung adenocarcinoma (LUAD) has a malignant characteristic that is highly aggressive and prone to metastasis. There is still a lack of suitable biomarkers to facilitate the refinement of precision-based therapeutic regimens. We used a combination of 10 known clustering algorithms and the omics data from 4 dimensions to identify high-resolution molecular subtypes of LUAD. Subsequently, consensus machine learning-related prognostic signature (CMRS) was developed based on subtypes related genes and an integrated program framework containing 10 machine learning algorithms. The efficiency of CMRS was analyzed from the perspectives of tumor microenvironment, genomic landscape, immunotherapy, drug sensitivity, and single-cell analysis. In terms of results, through multi-omics clustering, we identified 2 comprehensive omics subtypes (CSs) in which CS1 patients had worse survival outcomes, higher aggressiveness, mRNAsi and mutation frequency. Subsequently, we developed CMRS based on 13 key genes up-regulated in CS1. The prognostic predictive efficiency of CMRS was superior to most established LUAD prognostic signatures. CMRS demonstrated a strong correlation with tumor microenvironmental feature variants and genomic instability generation. Regarding clinical performance, patients in the high CMRS group were more likely to benefit from immunotherapy, whereas low CMRS were more likely to benefit from chemotherapy and targeted drug therapy. In addition, we evaluated that drugs such as neratinib, oligomycin A, and others may be candidates for patients in the high CMRS group. Single-cell analysis revealed that CMRS-related genes were mainly expressed in epithelial cells. The novel molecular subtypes identified in this study based on multi-omics data could provide new insights into the stratified treatment of LUAD, while the development of CMRS could serve as a candidate indicator of the degree of benefit of precision therapy and immunotherapy for LUAD.

Beyond the surface: how ex-vivo diffusion-weighted imaging reveals large animal brain microstructure and connectivity

Diffusion-weighted Imaging (DWI) is an effective and state-of-the-art neuroimaging method that non-invasively reveals the microstructure and connectivity of tissues. Recently, novel applications of the DWI technique in studying large brains through ex-vivo imaging enabled researchers to gain insights into the complex neural architecture in different species such as those of Perissodactyla (e.g., horses and rhinos), Artiodactyla (e.g., bovids, swines, and cetaceans), and Carnivora (e.g., felids, canids, and pinnipeds). Classical in-vivo tract-tracing methods are usually considered unsuitable for ethical and practical reasons, in large animals or protected species. Ex-vivo DWI-based tractography offers the chance to examine the microstructure and connectivity of formalin-fixed tissues with scan times and precision that is not feasible in-vivo. This paper explores DWI's application to ex-vivo brains of large animals, highlighting the unique insights it offers into the structure of sometimes phylogenetically different neural networks, the connectivity of white matter tracts, and comparative evolutionary adaptations. Here, we also summarize the challenges, concerns, and perspectives of ex-vivo DWI that will shape the future of the field in large brains.

A novel radiomics approach for predicting TACE outcomes in hepatocellular carcinoma patients using deep learning for multi-organ segmentation

Transarterial chemoembolization (TACE) represent the standard of therapy for non-operative hepatocellular carcinoma (HCC), while prediction of long term treatment outcomes is a complex and multifactorial task. In this study, we present a novel machine learning approach utilizing radiomics features from multiple organ volumes of interest (VOIs) to predict TACE outcomes for 252 HCC patients. Unlike conventional radiomics models requiring laborious manual segmentation limited to tumoral regions, our approach captures information comprehensively across various VOIs using a fully automated, pretrained deep learning model applied to pre-TACE CT images. Evaluation of radiomics random survival forest models against clinical ones using Cox proportional hazard demonstrated comparable performance in predicting overall survival. However, radiomics outperformed clinical models in predicting progression-free survival. Explainable analysis highlighted the significance of non-tumoral VOI features, with their cumulative importance superior to features from the largest liver tumor. The proposed approach overcomes the limitations of manual VOI segmentation, requires no radiologist input and highlight the clinical relevance of features beyond tumor regions. Our findings suggest the potential of this radiomics models in predicting TACE outcomes, with possible implications for other clinical scenarios.

The Hidden Agony of the Pancreas: A Comprehensive Case Study of Paraduodenal Pancreatitis

Paraduodenal pancreatitis (PP), also known as groove pancreatitis (GP), is a rare and distinct variant of chronic pancreatitis and presents significant diagnostic and therapeutic challenges. This comprehensive case study explores a 54-year-old male patient’s journey, highlighting the intricate relationship between clinical presentation, diagnostic modalities, and management strategies. Despite a history of smoking and alcohol consumption, the diagnosis of PP was primarily reliant on advanced imaging techniques, including computed tomography and magnetic resonance imaging, which revealed characteristic findings of GP. The case underscores the importance of a high index of suspicion and a step-up approach to management, starting with conservative treatment and progressing to surgical intervention as necessary. This study contributes to the growing body of knowledge on PP, emphasizing the need for awareness and understanding of this rare condition to improve patient outcomes.

Laryngotracheal trauma-induced Macklin effect: A case report

Laryngotracheal trauma is a relatively rare traumatic injury seen particularly in young male adults. Trauma due to strangulation is one of its most frequent circumstances. However rare, pneumomediastinum is a particular complication of severe blunt neck injuries leading to alveolar ruptures. This phenomenon, described as the Macklin effect, requires early diagnosis, and its management varies from conservative to surgical treatment depending on the severity of symptoms. Our aim is to describe the case of a 21-year-old male who presented with blunt neck trauma. Clinical and imaging findings revealed subcutaneous neck emphysema and pneumomediastinum. Treatment was conservative leading to complete resolution of the injuries and the patient was discharged after 2 weeks.

Hystero-Salphingography in current clinical practice-old flames, die hard!

Hysterosalpingography (HSG) remains a valuable diagnostic tool in current clinical practice, offering crucial insights into endometrial cavity, fallopian tubes and the adjoining part of the pelvic peritoneal cavity. Despite the emergence of alternative imaging and non-imaging options, HSG continues to be widely utilized due to its diagnostic accuracy, cost-effectiveness, and easy accessibility. Due attention to the correct technique and optimal image interpretation will further enhance its diagnostic accuracy and precision in the work-up of patients with fertility problems.

Splenic artery embolization complicated by pleural effusion

This case report and review describes a 31-year-old man with a history of chronic pancreatitis who presented to the hospital with shortness of breath and left-sided chest pain. Three days prior, he underwent mid-splenic artery embolization due to hematemesis attributed to a splenic artery pseudoaneurysm associated with a peripancreatic pseudocyst. Upon this presentation, the patient reported increasing shortness of breath, left-sided pleuritic chest pain, and epigastric and left upper quadrant abdominal pain. Imaging revealed left pleural effusion, splenic infarcts, and adjacent fluid collections. Thoracentesis confirmed an exudative effusion. The pleural effusion was attributed to recent splenic artery embolization, and the patient was discharged on appropriate medications in stable condition on the sixth day of hospitalization. This case underscores the importance of considering embolization-related complications in the differential diagnosis of pleural effusions following such procedures. The etiology, diagnosis, and management of splenic artery aneurysms are discussed in this review.