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OBJECTIVES: To perform a multi-reader comparison of multiparametric dual-energy computed tomography (DECT) images reconstructed with deep-learning image reconstruction (DLIR) and standard-of-care adaptive statistical iterative reconstruction-V (ASIR-V). METHODS: This retrospective study included 100 patients undergoing portal venous phase abdominal CT on a rapid kVp switching DECT scanner. Six reconstructed DECT sets (ASIR-V and DLIR, each at three strengths) were generated. Each DECT set included 65 keV monoenergetic, iodine, and virtual unenhanced (VUE) images. Using a Likert scale, three radiologists performed qualitative assessments for image noise, contrast, small structure visibility, sharpness, artifact, and image preference. Quantitative assessment was performed by measuring attenuation, image noise, and contrast-to-noise ratios (CNR). For the qualitative analysis, Gwet's AC2 estimates were used to assess agreement. RESULTS: DECT images reconstructed with DLIR yielded better qualitative scores than ASIR-V images except for artifacts, where both groups were comparable. DLIR-H images were rated higher than other reconstructions on all parameters (p-value < 0.05). On quantitative analysis, there was no significant difference in the attenuation values between ASIR-V and DLIR groups. DLIR images had higher CNR values for the liver and portal vein, and lower image noise, compared to ASIR-V images (p-value < 0.05). The subgroup analysis of patients with large body habitus (weight ≥ 90 kg) showed similar results to the study population. Inter-reader agreement was good-to-very good overall. CONCLUSION: Multiparametric post-processed DECT datasets reconstructed with DLIR were preferred over ASIR-V images with DLIR-H yielding the highest image quality scores. CLINICAL RELEVANCE STATEMENT: Deep-learning image reconstruction in dual-energy CT demonstrated significant benefits in qualitative and quantitative image metrics compared to adaptive statistical iterative reconstruction-V. KEY POINTS: Dual-energy CT (DECT) images reconstructed using deep-learning image reconstruction (DLIR) showed superior qualitative scores compared to adaptive statistical iterative reconstruction-V (ASIR-V) reconstructed images, except for artifacts where both reconstructions were rated comparable. While there was no significant difference in attenuation values between ASIR-V and DLIR groups, DLIR images showed higher contrast-to-noise ratios (CNR) for liver and portal vein, and lower image noise (p value < 0.05). Subgroup analysis of patients with large body habitus (weight ≥ 90 kg) yielded similar findings to the overall study population.
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OBJECTIVE: To assess the value of material density (MD) images generated from a rapid kilovoltage-switching dual-energy CT (rsDECT) in early detection of peritoneal carcinomatosis (PC). MATERIALS AND METHODS: Thirty patients (60 ± 13 years; 24 women) with PC detected on multiple abdominal DECT scans were included. Four separate DECTs with varying findings of PC from each patient were used for qualitative/quantitative analysis, resulting in a total of 120 DECT scans (n = 30 × 4). Three radiologists independently reviewed DECT images (65 keV alone and 65 keV + MD) for diagnosis of PC (diagnostic confidence, lesion conspicuity, sharpness/delineation and image quality) using a 5-point Likert scale. Quantitative estimation of contrast-to-noise ratio (CNR) was done. Wilcoxon signed-rank test and Odds ratio calculation were used to compare between the two protocols. Inter-observer agreement was evaluated using Kappa coefficient analysis. P values < 0.05 were considered statistically significant. RESULTS: 65 keV + MD images showed a slightly higher sensitivity (89%[95%CI:84,92]) for PC detection compared with 65 keV images alone without statistical significance (84%[95%CI:78,88], p = 0.11) with the experienced reader showing significant improvement (98%[95%CI:93,100] vs. 90%[95%CI:83,94], p = 0.02). On a per-patient basis, use of MD images allowed earlier diagnosis for PC in an additional 13-23% of patients. On sub-group analysis, earlier diagnosis of PC was particularly beneficial in patients with BMI ≤ 29.9 kg/m2. 65 keV + MD images showed higher diagnostic confidence, lesion conspicuity, and lesion sharpness for the experienced reader (p < 0.001). CNR was higher in MD images (1.7 ± 0.5) than 65 keV images (0.1 ± 0.02, p < 0.001). All readers showed moderate interobserver agreement for determining PC by both protocols (κ = 0.58 and κ = 0.47). CONCLUSION: MD images allow earlier and improved detection of PC with the degree of benefit varying based on reader experience and patient body habitus.
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Gender-affirming surgery (GAS) is increasingly being performed. GAS is tailored to the patient leading to a diverse spectrum of radiologic post-operative findings. Radiologists who are unfamiliar with expected anatomic alterations after GAS may misdiagnose important complications leading to adverse patient outcomes. This collaborative multi-institutional review aims to: Describe relevant embryology and native anatomy. Describe relevant Gender-Affirming Surgery (GAS) techniques and expected neo-anatomy with associated complications, including common terminology. Review expected imaging appearance of neo-anatomy/postoperative findings. Review multi-modality [ultrasound, plain film, retrograde urethrogram, computed tomography] emergent imaging findings. Understand unique patient evaluation and imaging protocol considerations in the GAS population. Discuss pearls and pitfalls of imaging in the acute post-GAS setting.
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Complicações Pós-Operatórias , Humanos , Complicações Pós-Operatórias/diagnóstico por imagem , Feminino , Cirurgia de Readequação Sexual , Masculino , Serviço Hospitalar de EmergênciaRESUMO
ABSTRACT: Recent advances in molecular pathology and an improved understanding of the etiology of neuroendocrine neoplasms (NENs) have given rise to an updated World Health Organization classification. Since gastroenteropancreatic NENs (GEP-NENs) are the most common forms of NENs and their incidence has been increasing constantly, they will be the focus of our attention. Here, we review the findings at the foundation of the new classification system, discuss how it impacts imaging research and radiological practice, and illustrate typical and atypical imaging and pathological findings. Gastroenteropancreatic NENs have a highly variable clinical course, which existing classification schemes based on proliferation rate were unable to fully capture. While well- and poorly differentiated NENs both express neuroendocrine markers, they are fundamentally different diseases, which may show similar proliferation rates. Genetic alterations specific to well-differentiated neuroendocrine tumors graded 1 to 3 and poorly differentiated neuroendocrine cancers of small cell and large-cell subtype have been identified. The new tumor classification places new demands and creates opportunities for radiologists to continue providing the clinically most relevant report and on researchers to design projects, which continue to be clinically applicable.
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Tumores Neuroendócrinos , Organização Mundial da Saúde , Humanos , Tumores Neuroendócrinos/diagnóstico por imagem , Tumores Neuroendócrinos/patologia , Tumores Neuroendócrinos/classificação , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/classificação , Neoplasias Pancreáticas/patologiaRESUMO
The visceral vasculature is inextricably intertwined with abdominopelvic disease staging, spread, and management in routine and emergent cases. Comprehensive evaluation requires specialized imaging techniques for abnormality detection and characterization. Vascular pathology is often encountered on nondedicated routine imaging examinations, which may obscure, mimic, or confound many vascular diagnoses. This review highlights normal arterial, portal venous, and systemic venous anatomy and clinically relevant variants; diagnostic pitfalls related to image-acquisition technique and disease mimics; and characteristics of common and rare vascular diseases to empower radiologists to confidently interpret the vascular findings and avoid misdiagnosis.
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Diagnóstico por Imagem , Veia Porta , Humanos , Veia Porta/diagnóstico por imagem , Erros de DiagnósticoRESUMO
INTRODUCTION: We investigated the incidence of secondary bladder (BCa) and rectal cancers (RCa) after external beam radiotherapy (EBRT) for prostate cancer (PCa) compared to radical prostatectomy (RP) alone, and compared cancer-specific survival (CSS) of these secondary neoplasms to their primary counterparts. METHODS: This retrospective cohort study included men in the SEER cancer registry with a diagnosis of non-metastatic, clinically node-negative PCa treated with either RP or EBRT from 1995-2011 and allowed a minimum five-year lag period for the development of secondary BCa or RCa. Patients were divided into two eras, 1995-2002 and 2003-2011, to examine differences in incidence of secondary malignancies over time. Univariable and multivariable competing risk analyses with Fine-Gray subdistribution hazard and cause-specific hazard models were used to examine the risk of developing a secondary BCa or RCa. Competing risks analyses were used to compare CSS of primary vs. secondary BCa and RCa. RESULTS: A total of 198 184 men underwent RP and 190 536 underwent EBRT for PCa. The cumulative incidence of secondary BCa at 10 years was 1.71% for RP, and 3.7% for EBRT (p<0.001), while that of RCa was 0.52% for RP and 0.99% for EBRT (p<0.001). EBRT was associated with almost twice the risk of developing a secondary BCa and RCa compared to RP. The hazard of secondary BCa following EBRT delivered during 2003-2011 was 20% less than from 1995-2002 (p<0.09, Fine-Gray model), while that of secondary RCa was 31% less (p<0.001) (hazard ratio 0.78, p<0.001) for Fine-Gray and cause-specific hazard models. In the Fine-Gray model, the risk of death from BCa was 27% lower for secondary BCa after RP compared to primary BCa, while the risk of death was 9% lower for secondary BCa after EBRT compared to primary BCa. There was no difference in RCa-specific survival between primary or secondary RCa after RP or EBRT. CONCLUSIONS: The risk of BCa and RCa is almost twice as high for men undergoing EBRT for localized PCa vs. RP, but that risk is declining, likely reflecting advances in radiation delivery. The development of secondary RCa or BCa does not confer elevated risk of death compared to their primary counterparts.
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BACKGROUND. The 2022 Society of Radiologists in Ultrasound (SRU) consensus conference recommendations for small gallbladder polyps support management that is less aggressive than earlier approaches and may help standardize evaluation of polyps by radiologists. OBJECTIVE. The purpose of the present study was to assess the interreader agreement of radiologists in applying SRU recommendations for management of incidental gallbladder polyps on ultrasound. METHODS. This retrospective study included 105 patients (75 women and 30 men; median age, 51 years) with a gallbladder polyp on ultrasound (without features highly suspicious for invasive or malignant tumor) who underwent cholecystectomy between January 1, 2003, and January 1, 2021. Ten abdominal radiologists independently reviewed ultrasound examinations and, using the SRU recommendations, assessed one polyp per patient to assign risk category (extremely low risk, low risk, or indeterminate risk) and make a possible recommendation for surgical consultation. Five radiologists were considered less experienced (< 5 years of experience), and five were considered more experienced (≥ 5 years of experience). Interreader agreement was evaluated. Polyps were classified pathologically as nonneoplastic or neoplastic. RESULTS. For risk category assignments, interreader agreement was substantial among all readers (k = 0.710), less-experienced readers (k = 0.705), and more-experienced readers (k = 0.692). For surgical consultation recommendations, inter-reader agreement was substantial among all readers (k = 0.795) and more-experienced readers (k = 0.740) and was almost perfect among less-experienced readers (k = 0.811). Of 10 readers, a median of 5.0 (IQR, 2.0-8.0), 4.0 (IQR, 2.0-7.0), and 0.0 (IQR, 0.0-0.0) readers classified polyps as extremely low risk, low risk, and indeterminate risk, respectively. Across readers, the percentage of polyps classified as extremely low risk ranged from 32% to 72%; as low risk, from 24% to 65%; and as indeterminate risk, from 0% to 8%. Of 10 readers, a median of zero change to 0 (IQR, 0.0-1.0) readers recommended surgical consultation; the percentage of polyps receiving a recommendation for surgical consultation ranged from 4% to 22%. Of a total of 105 polyps, 102 were nonneo-plastic and three were neoplastic (all benign). Based on readers' most common assessments for nonneoplastic polyps, the risk category was extremely low risk for 53 polyps, low risk for 48 polyps, and indeterminate risk for one polyp; surgical consultation was recommended for 16 polyps. CONCLUSION. Ten abdominal radiologists showed substantial agreement for polyp risk categorizations and surgical consultation recommendations, although areas of reader variability were identified. CLINICAL IMPACT. The findings support the overall reproducibility of the SRU recommendations, while indicating opportunity for improvement.
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Achados Incidentais , Pólipos , Ultrassonografia , Humanos , Feminino , Masculino , Pessoa de Meia-Idade , Pólipos/diagnóstico por imagem , Pólipos/cirurgia , Estudos Retrospectivos , Ultrassonografia/métodos , Adulto , Doenças da Vesícula Biliar/diagnóstico por imagem , Doenças da Vesícula Biliar/cirurgia , Idoso , Variações Dependentes do Observador , Radiologistas , Sociedades Médicas , Consenso , Guias de Prática Clínica como AssuntoRESUMO
Commercial ultrasound vascular phantoms lack the anatomic diversity required for robust pre-clinical interventional device testing. We fabricated individualized phantoms to test an artificial intelligence enabled ultrasound-guided surgical robotic system (AI-GUIDE) which allows novices to cannulate deep vessels. After segmenting vessels on computed tomography scans, vessel cores, bony anatomy, and a mold tailored to the skin contour were 3D-printed. Vessel cores were coated in silicone, surrounded in tissue-mimicking gel tailored for ultrasound and needle insertion, and dissolved with water. One upper arm and four inguinal phantoms were constructed. Operators used AI-GUIDE to deploy needles into phantom vessels. Two groin phantoms were tested due to imaging artifacts in the other two phantoms. Six operators (medical experience: none, 3; 1-5 years, 2; 5+ years, 1) inserted 27 inguinal needles with 81% (22/27) success in a median of 48 seconds. Seven operators performed 24 arm injections, without tuning the AI for arm anatomy, with 71% (17/24) success. After excluding failures due to motor malfunction and a defective needle, success rate was 100% (22/22) in the groin and 85% (17/20) in the arm. Individualized 3D-printed phantoms permit testing of surgical robotics across a large number of operators and different anatomic sites. AI-GUIDE operators rapidly and reliably inserted a needle into target vessels in the upper arm and groin, even without prior medical training. Virtual device trials in individualized 3-D printed phantoms may improve rigor of results and expedite translation.Clinical Relevance- Individualized phantoms enable rigorous and efficient evaluation of interventional devices and reduce the need for animal and human subject testing.
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Inteligência Artificial , Agulhas , Animais , Humanos , Ultrassonografia , Imagens de Fantasmas , Ultrassonografia de Intervenção/métodosRESUMO
Nonalcoholic fatty liver disease (NAFLD) is a common cause of morbidity and mortality. Nonfocal liver biopsy is the historical reference standard for evaluating NAFLD, but it is limited by invasiveness, high cost, and sampling error. Imaging methods are ideally situated to provide quantifiable results and rule out other anatomic diseases of the liver. MRI and US have shown great promise for the noninvasive evaluation of NAFLD. US is particularly well suited to address the population-level problem of NAFLD because it is lower-cost, more available, and more tolerable to a broader range of patients than MRI. Noninvasive US methods to evaluate liver fibrosis are widely available, and US-based tools to evaluate steatosis and inflammation are gaining traction. US techniques including shear-wave elastography, Doppler spectral imaging, attenuation coefficient, hepatorenal index, speed of sound, and backscatter-based estimation have regulatory clearance and are in clinical use. New methods based on channel and radiofrequency data analysis approaches have shown promise but are mostly experimental. This review discusses the advantages and limitations of clinically available and experimental approaches to sonographic liver tissue characterization for NAFLD diagnosis as well as future applications and strategies to overcome current limitations.
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Técnicas de Imagem por Elasticidade , Hepatopatia Gordurosa não Alcoólica , Humanos , Biópsia , InflamaçãoRESUMO
Post-operative urinary retention is a medical condition where patients cannot urinate despite having a full bladder. Ultrasound imaging of the bladder is used to estimate urine volume for early diagnosis and management of urine retention. Moreover, the use of bladder ultrasound can reduce the need for an indwelling urinary catheter and the risk of catheter-associated urinary tract infection. Wearable ultrasound devices combined with machine-learning based bladder volume estimation algorithms reduce the burdens of nurses in hospital settings and improve outpatient care. However, existing algorithms are memory and computation intensive, thereby demanding the use of expensive GPUs. In this paper, we develop and validate a low-compute memory-efficient deep learning model for accurate bladder region segmentation and urine volume calculation. B-mode ultrasound bladder images of 360 patients were divided into training and validation sets; another 74 patients were used as the test dataset. Our 1-bit quantized models with 4-bits and 6-bits skip connections achieved an accuracy within [Formula: see text] and [Formula: see text], respectively, of a full precision state-of-the-art neural network (NN) without any floating-point operations and with an [Formula: see text] and [Formula: see text] reduction in memory requirements to fit under 150 kB. The means and standard deviations of the volume estimation errors, relative to estimates from ground-truth clinician annotations, were [Formula: see text] ml and [Formula: see text] ml, respectively. This lightweight NN can be easily integrated on the wearable ultrasound device for automated and continuous monitoring of urine volume. Our approach can potentially be extended to other clinical applications, such as monitoring blood pressure and fetal heart rate.
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Bexiga Urinária , Retenção Urinária , Humanos , Bexiga Urinária/diagnóstico por imagem , Algoritmos , Redes Neurais de Computação , Ultrassonografia/métodos , Retenção Urinária/diagnóstico por imagemRESUMO
BACKGROUND AND OBJECTIVES: To assess the impact of Gadolinium-enhanced magnetic resonance imaging (MRI) sequences on Preoperative imaging evaluation and surgical planning parameters for osteosarcoma (OS) of the knee in pediatric and young adult patients. METHODS: Thirty MRI scans of patients with OS about the knee were reviewed by five orthopedic oncologists. Key preoperative parameters (neurovascular bundle involvement, intra-articular tumor extension, extent of intramedullary extension) and surgical plans were evaluated based on non-contrast versus Gd contrast enhanced sequences. Assessment agreement, inter-rater agreement, and intrarater agreement between pre and postcontrast images were evaluated via Kappa statistics. RESULTS: Moderate agreement was seen between non and contrast-enhanced assessment of neurovascular involvement and intra-articular tumor extension. Intrarater reproducibility was substantial for neurovascular bundle involvement (precontrast Kappa: 0.63, postcontrast Kappa: 0.69). Intrarater reproducibility was also substantial for precontrast (Kappa: 0.70) and moderate for postcontrast (Kappa: 0.50) assessment of intra-articular tumor extension. Planned resection length and choice of surgical approach were similar between sequences. The addition of Gd-enhanced sequences improved the inter-rater agreement across collected parameters. CONCLUSIONS: While some findings suggest that contrast enhanced sequences may not significantly alter the assessment of key preoperative planning parameters by orthopedic oncologists, they may help reduce variability among providers with differing experience levels.
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Non-alcoholic fatty liver disease (NAFLD) is a significant cause of diffuse liver disease, morbidity and mortality worldwide. Early and accurate diagnosis of NALFD is critical to identify patients at risk of disease progression. Liver biopsy is the current gold standard for diagnosis and prognosis. However, a non-invasive diagnostic tool is desired because of the high cost and risk of complications of tissue sampling. Medical ultrasound is a safe, inexpensive and widely available imaging tool for diagnosing NAFLD. Emerging sonographic tools to quantitatively estimate hepatic fat fraction, such as tissue sound speed estimation, are likely to improve diagnostic accuracy, precision and reproducibility compared with existing qualitative and semi-quantitative techniques. Various pulse-echo ultrasound speed of sound estimation methodologies have been investigated, and some have been recently commercialized. We review state-of-the-art in vivo speed of sound estimation techniques, including their advantages, limitations, technical sources of variability, biological confounders and existing commercial implementations. We report the expected range of hepatic speed of sound as a function of liver steatosis and fibrosis that may be encountered in clinical practice. Ongoing efforts seek to quantify sound speed measurement accuracy and precision to inform threshold development around meaningful differences in fat fraction and between sequential measurements.
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Hepatopatia Gordurosa não Alcoólica , Humanos , Hepatopatia Gordurosa não Alcoólica/patologia , Reprodutibilidade dos Testes , Ultrassom , Fígado/diagnóstico por imagem , Fígado/patologia , Ultrassonografia/métodos , Imageamento por Ressonância MagnéticaRESUMO
BACKGROUND: CT image reconstruction has evolved from filtered back projection to hybrid- and model-based iterative reconstruction. Deep learning-based image reconstruction is a relatively new technique that uses deep convolutional neural networks to improve image quality. OBJECTIVE: To evaluate and compare 1.25 mm thin-section abdominal CT images reconstructed with deep learning image reconstruction (DLIR) with 5 mm thick images reconstructed with adaptive statistical iterative reconstruction (ASIR-V). METHODS: This retrospective study included 52 patients (31 F; 56.9±16.9 years) who underwent abdominal CT scans between August-October 2019. Image reconstruction was performed to generate 5 mm images at 40% ASIR-V and 1.25 mm DLIR images at three strengths (low [DLIR-L], medium [DLIR-M], and high [DLIR-H]). Qualitative assessment was performed to determine image noise, contrast, visibility of small structures, sharpness, and artifact based on a 5-point-scale. Image preference determination was based on a 3-point-scale. Quantitative assessment included measurement of attenuation, image noise, and contrast-to-noise ratios (CNR). RESULTS: Thin-section images reconstructed with DLIR-M and DLIR-H yielded better image quality scores than 5 mm ASIR-V reconstructed images. Mean qualitative scores of DLIR-H for noise (1.77 ± 0.71), contrast (1.6 ± 0.68), small structure visibility (1.42 ± 0.66), sharpness (1.34 ± 0.55), and image preference (1.11 ± 0.34) were the best (p<0.05). DLIR-M yielded intermediate scores. All DLIR reconstructions showed superior ratings for artifacts compared to ASIR-V (p<0.05), whereas each DLIR group performed comparably (p>0.05, 0.405-0.763). In the quantitative assessment, there were no significant differences in attenuation values between all reconstructions (p>0.05). However, DLIR-H demonstrated the lowest noise (9.17 ± 3.11) and the highest CNR (CNRliver = 26.88 ± 6.54 and CNRportal vein = 7.92 ± 3.85) (all p<0.001). CONCLUSION: DLIR allows generation of thin-section (1.25 mm) abdominal CT images, which provide improved image quality with higher inter-reader agreement compared to 5 mm thick images reconstructed with ASIR-V. CLINICAL IMPACT: Improved image quality of thin-section CT images reconstructed with DLIR has several benefits in clinical practice, such as improved diagnostic performance without radiation dose penalties.
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Aprendizado Profundo , Humanos , Estudos Retrospectivos , Doses de Radiação , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Tomografia Computadorizada por Raios X/métodos , Processamento de Imagem Assistida por Computador/métodos , AlgoritmosRESUMO
Fatty liver disease has a high and increasing prevalence worldwide, is associated with adverse cardiovascular events and higher long-term medical costs, and may lead to liver-related morbidity and mortality. There is an urgent need for accurate, reproducible, accessible, and noninvasive techniques appropriate for detecting and quantifying liver fat in the general population and for monitoring treatment response in at-risk patients. CT may play a potential role in opportunistic screening, and MRI proton-density fat fraction provides high accuracy for liver fat quantification; however, these imaging modalities may not be suited for widespread screening and surveillance, given the high global prevalence. US, a safe and widely available modality, is well positioned as a screening and surveillance tool. Although well-established qualitative signs of liver fat perform well in moderate and severe steatosis, these signs are less reliable for grading mild steatosis and are likely unreliable for detecting subtle changes over time. New and emerging quantitative biomarkers of liver fat, such as those based on standardized measurements of attenuation, backscatter, and speed of sound, hold promise. Evolving techniques such as multiparametric modeling, radiofrequency envelope analysis, and artificial intelligence-based tools are also on the horizon. The authors discuss the societal impact of fatty liver disease, summarize the current state of liver fat quantification with CT and MRI, and describe past, currently available, and potential future US-based techniques for evaluating liver fat. For each US-based technique, they describe the concept, measurement method, advantages, and limitations. © RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.
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Inteligência Artificial , Hepatopatia Gordurosa não Alcoólica , Humanos , Fígado/diagnóstico por imagem , Hepatopatia Gordurosa não Alcoólica/diagnóstico por imagem , Imageamento por Ressonância Magnética/métodos , PrevalênciaRESUMO
GOALS: We sought to evaluate the association of steroids with nonalcoholic fatty liver disease (NAFLD) among patients with inflammatory bowel disease (IBD). BACKGROUND: Patients with IBD are at increased risk of NAFLD. Steroids may have a role in the pathogenesis of NAFLD. STUDY: We searched MEDLINE (through PubMed) and Embase for studies from inception to July 2021. We included published interventional and observational studies of adults 18 years or older with ulcerative colitis or Crohn's disease. We reported odds ratios, 95% confidence intervals, and generated forest plots. A random effects model generated a summary effect estimate. Publication bias was assessed by funnel plot and Egger's test. Study quality was examined using modified Newcastle-Ottawa scale (NOS) and Agency for Healthcare Research and Quality (AHRQ). RESULTS: A total of 12 observational studies with 3497 participants were included. NAFLD was identified in 1017 (29.1%) patients. The pooled odds ratio for the development of NAFLD in steroid users versus non-users was 0.87 (95% confidence interval: 0.72-1.04). There was no significant heterogeneity between studies ( I ²=0.00%, P =0.13). No publication bias was detected by funnel plot or Egger's test ( P =0.24). Findings were consistent among subgroup analyses stratified by study quality. CONCLUSION: In this meta-analysis, steroids were not associated with NAFLD in patients with IBD. Steroids may not need to be withheld from patients with IBD for the purposes of preventing NAFLD. Additional prospective studies that systematically document steroid exposure and important confounders among patients with IBD are warranted.
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Colite Ulcerativa , Doenças Inflamatórias Intestinais , Hepatopatia Gordurosa não Alcoólica , Adulto , Humanos , Hepatopatia Gordurosa não Alcoólica/complicações , Estudos Prospectivos , Doenças Inflamatórias Intestinais/complicações , Doenças Inflamatórias Intestinais/tratamento farmacológico , Colite Ulcerativa/complicações , Colite Ulcerativa/tratamento farmacológico , EsteroidesRESUMO
To develop an ultrasound-based machine learning classifier to diagnose benignity within indeterminate thyroid nodules (ITNs) by fine-needle aspiration, 180 patients with 194 ITNs (Bethesda classes III, IV and V) undergoing surgery over a 5-y study period were analyzed. The data set was randomly divided into training and testing data sets with 155 and 39 ITNs, respectively. All nodules were evaluated by ultrasound using the American College of Radiology Thyroid Imaging Reporting and Data System by manually scoring composition, echogenicity, shape, margin and echogenic foci. Nodule size, participant age and patient sex were recorded. A support vector machine (SVM) model with a cost-sensitive approach was developed using the aforementioned eight parameters with surgical histopathology as the reference standard. Surgical pathology determined 90 (46.4%) ITNs were malignant and 104 (53.6%) were benign. The SVM model classified 14 nodules as benign in the testing data set, of which 13 were correct (sensitivity = 93.8%, specificity = 56.5%). Considering malignancy prevalence by Bethesda group, the negative predictive values of this model for Bethesda III and IV categories were 93.9% and 93. 8%, respectively. The high negative predictive value of the SVM ultrasound-based model suggests a pathway by which surgical excision of Bethesda III and IV ITNs classified as benign may be avoided.
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Neoplasias da Glândula Tireoide , Nódulo da Glândula Tireoide , Biópsia por Agulha Fina , Humanos , Aprendizado de Máquina , Estudos Retrospectivos , Neoplasias da Glândula Tireoide/patologia , Nódulo da Glândula Tireoide/patologiaRESUMO
Hemorrhage is a leading cause of trauma death, particularly in prehospital environments when evacuation is delayed. Obtaining central vascular access to a deep artery or vein is important for administration of emergency drugs and analgesics, and rapid replacement of blood volume, as well as invasive sensing and emerging life-saving interventions. However, central access is normally performed by highly experienced critical care physicians in a hospital setting. We developed a handheld AI-enabled interventional device, AI-GUIDE (Artificial Intelligence Guided Ultrasound Interventional Device), capable of directing users with no ultrasound or interventional expertise to catheterize a deep blood vessel, with an initial focus on the femoral vein. AI-GUIDE integrates with widely available commercial portable ultrasound systems and guides a user in ultrasound probe localization, venous puncture-point localization, and needle insertion. The system performs vascular puncture robotically and incorporates a preloaded guidewire to facilitate the Seldinger technique of catheter insertion. Results from tissue-mimicking phantom and porcine studies under normotensive and hypotensive conditions provide evidence of the technique's robustness, with key performance metrics in a live porcine model including: a mean time to acquire femoral vein insertion point of 53 ± 36 s (5 users with varying experience, in 20 trials), a total time to insert catheter of 80 ± 30 s (1 user, in 6 trials), and a mean number of 1.1 (normotensive, 39 trials) and 1.3 (hypotensive, 55 trials) needle insertion attempts (1 user). These performance metrics in a porcine model are consistent with those for experienced medical providers performing central vascular access on humans in a hospital.
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Cateterismo Venoso Central , Procedimentos Cirúrgicos Robóticos , Ultrassonografia de Intervenção , Animais , Inteligência Artificial , Veia Femoral/diagnóstico por imagem , Humanos , SuínosRESUMO
OBJECTIVES: To investigate the image quality and perception of a sinogram-based deep learning image reconstruction (DLIR) algorithm for single-energy abdominal CT compared to standard-of-care strength of ASIR-V. METHODS: In this retrospective study, 50 patients (62% F; 56.74 ± 17.05 years) underwent portal venous phase. Four reconstructions (ASIR-V at 40%, and DLIR at three strengths: low (DLIR-L), medium (DLIR-M), and high (DLIR-H)) were generated. Qualitative and quantitative image quality analysis was performed on the 200 image datasets. Qualitative scores were obtained for image noise, contrast, small structure visibility, sharpness, and artifact by three blinded radiologists on a 5-point scale (1, excellent; 5, very poor). Radiologists also indicated image preference on a 3-point scale (1, most preferred; 3, least preferred). Quantitative assessment was performed by measuring image noise and contrast-to-noise ratio (CNR). RESULTS: DLIR had better image quality scores compared to ASIR-V. Scores on DLIR-H for noise (1.40 ± 0.53), contrast (1.41 ± 0.55), small structure visibility (1.51 ± 0.61), and sharpness (1.60 ± 0.54) were the best (p < 0.05) followed by DLIR-M (1.85 ± 0.52, 1.66 ± 0.57, 1.69 ± 0.59, 1.68 ± 0.46), DLIR-L (2.29 ± 0.58, 1.96 ± 0.61, 1.90 ± 0.65, 1.86 ± 0.46), and ASIR-V (2.86 ± 0.67, 2.55 ± 0.58, 2.34 ± 0.66, 2.01 ± 0.36). Ratings for artifacts were similar for all reconstructions (p > 0.05). DLIRs did not influence subjective textural perceptions and were preferred over ASIR-V from the beginning. All DLIRs had a higher CNR (26.38-102.30%) and lower noise (20.64-48.77%) than ASIR-V. DLIR-H had the best objective scores. CONCLUSION: Sinogram-based deep learning image reconstructions were preferred over iterative reconstruction subjectively and objectively due to improved image quality and lower noise, even in large patients. Use in clinical routine may allow for radiation dose reduction. KEY POINTS: ⢠Deep learning image reconstructions (DLIRs) have a higher contrast-to-noise ratio compared to medium-strength hybrid iterative reconstruction techniques. ⢠DLIR may be advantageous in patients with large body habitus due to a lower image noise. ⢠DLIR can enable further optimization of radiation doses used in abdominal CT.