Utilization of Radiomics Features Extracted From Preoperative Medical Images to Detect Metastatic Lymph Nodes in Cholangiocarcinoma and Gallbladder Cancer Patients: A Systemic Review and Meta-analysis.

OBJECTIVES: This study aimed to determine the methodological quality and evaluate the diagnostic performance of radiomics features in detecting lymph node metastasis on preoperative images in patients with cholangiocarcinoma and gallbladder cancer. METHODS: Publications between January 2005 and October 2022 were considered for inclusion. Databases such as Pubmed/Medline, Scopus, Embase, and Google Scholar were searched for relevant studies. The quality of the methodology of the manuscripts was determined using the Radiomics Quality Score and Quality Assessment of Diagnostic Accuracy Studies 2. Pooled results with corresponding 95% confidence intervals (CIs) were calculated using the DerSimonian-Liard method (random-effect model). Forest plots were used to visually represent the diagnostic profile of radiomics signature in each of the data sets pertaining to each study. Fagan plot was used to determine clinical applicability. RESULTS: Overall sensitivity was 0.748 (95% CI, 0.703-0.789). Overall specificity was 0.795 (95% CI, 0.742-0.839). The combined negative likelihood ratio was 0.299 (95% CI, 0.266-0.350), and the positive likelihood ratio was 3.545 (95% CI, 2.850-4.409). The combined odds ratio of the studies was 12.184 (95% CI, 8.477-17.514). The overall summary receiver operating characteristics area under the curve was 0.83 (95% CI, 0.80-0.86). Three studies applied nomograms to 8 data sets and achieved a higher pooled sensitivity and specificity (0.85 [0.80-0.89] and 0.85 [0.71-0.93], respectively). CONCLUSIONS: The pooled analysis showed that predictive models fed with radiomics features achieve good sensitivity and specificity in detecting lymph node metastasis in computed tomography and magnetic resonance imaging images. Supplementation of the models with biological correlates increased sensitivity and specificity in all data sets.

Diffuse infiltrative hepatocellular carcinoma: Multimodality imaging manifestations.

Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer, being the third most common cause of cancer-related death globally. HCC most frequently develops in the context of hepatic cirrhosis. HCC can manifest as various morphologic subtypes. Each pattern exhibits distinct behaviors in terms of imaging features, disease progression, response to therapy, and prognosis. While the nodular pattern is the most frequent subtype, infiltrative HCC is the least prevalent and makes up about 8%-20% of all HCC cases. Infiltrative HCC manifests as small tumor nodules that often spread across the entire liver or across a hepatic segment/lobe and is not identified as a focal tumor. On ultrasonography, infiltrative HCC presents as a markedly heterogeneous area with ill-defined echotexture, making it difficult to distinguish from background hepatic cirrhosis. On magnetic resonance imaging (MRI), infiltrating HCC typically manifests as a mild, poorly defined hepatic region with heterogeneous or homogenous aberrant signal intensity. Specifically, on T1-weighted MRI scans, infiltrating HCC frequently appears as largely hypointense and typically homogenous and mildly to moderately hyperintense on T2-weighted imaging. Infiltrative HCC frequently lacks a clearly defined boundary on cross-sectional imaging and can consequently fade into the background of the cirrhotic liver. As a result, infiltrating HCC is frequently not discovered until an advanced stage and has an associated poor prognosis. Thus, understanding imaging features associated with infiltrative HCC diagnosis is crucial for abdominal radiologists to ensure effective and timely care. We herein review imaging characteristics of infiltrative HCC.

Multimodality imaging of hepatocellular carcinoma and intrahepatic cholangiocarcinoma.

Hepatocellular carcinoma and intrahepatic cholangiocarcinoma are the two most common primary malignant tumors of the liver. The similarities and variations in imaging characteristics that may aid in distinguishing between these two primary tumors will be discussed and outlined in this review. Knowledge of imaging techniques that are currently available would assist in the differentiation between these primary malignancies.

Diagnosis of Metastatic Lymph Nodes in Patients With Papillary Thyroid Cancer: A Comparative Multi-Center Study of Semantic Features and Deep Learning-Based Models.

OBJECTIVES: Deep learning algorithms have shown potential in streamlining difficult clinical decisions. In the present study, we report the diagnostic profile of a deep learning model in differentiating malignant and benign lymph nodes in patients with papillary thyroid cancer. METHODS: An in-house deep learning-based model called "ClymphNet" was developed and tested using two datasets containing ultrasound images of 195 malignant and 178 benign lymph nodes. An expert radiologist also viewed these ultrasound images and extracted qualitative imaging features used in routine clinical practice. These signs were used to train three different machine learning algorithms. Then the deep learning model was compared with the machine learning models on internal and external validation datasets containing 22 and 82 malignant and 20 and 76 benign lymph nodes, respectively. RESULTS: Among the three machine learning algorithms, the support vector machine model (SVM) outperformed the best, reaching a sensitivity of 91.35%, specificity of 88.54%, accuracy of 90.00%, and an area under the curve (AUC) of 0.925 in all cohorts. The ClymphNet performed better than the SVM protocol in internal and external validation, achieving a sensitivity of 93.27%, specificity of 92.71%, and an accuracy of 93.00%, and an AUC of 0.948 in all cohorts. CONCLUSION: A deep learning model trained with ultrasound images outperformed three conventional machine learning algorithms fed with qualitative imaging features interpreted by radiologists. Our study provides evidence regarding the utility of ClymphNet in the early and accurate differentiation of benign and malignant lymphadenopathy.

Deep Radiomics Features of Median Nerves for Automated Diagnosis of Carpal Tunnel Syndrome With Ultrasound Images: A Multi-Center Study.

OBJECTIVES: Ultrasound is widely used in diagnosing carpal tunnel syndrome (CTS). However, the limitations of ultrasound in CTS detection are the lack of objective measures in the detection of nerve abnormality and the operator-dependent nature of ultrasound imaging. Therefore, in this study, we developed and proposed externally validated artificial intelligence (AI) models based on deep-radiomics features. METHODS: We have used 416 median nerves from 2 countries (Iran and Colombia) for the development (112 entrapped and 112 normal nerves from Iran) and validation (26 entrapped and 26 normal nerves from Iran, and 70 entrapped and 70 normal nerves from Columbia) of our models. Ultrasound images were fed to the SqueezNet architecture to extract deep-radiomics features. Then a ReliefF method was used to select the clinically significant features. The selected deep-radiomics features were fed to 9 common machine-learning algorithms to choose the best-performing classifier. The 2 best-performing AI models were then externally validated. RESULTS: Our developed model achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.910 (88.46% sensitivity, 88.46% specificity) and 0.908 (84.62% sensitivity, 88.46% specificity) with support vector machine and stochastic gradient descent (SGD), respectively using the internal validation dataset. Furthermore, both models consistently performed well in the external validation dataset, and achieved an AUC of 0.890 (85.71% sensitivity, 82.86% specificity) and 0.890 (84.29% sensitivity and 82.86% specificity), with SVM and SGD models, respectively. CONCLUSION: Our proposed AI models fed with deep-radiomics features performed consistently with internal and external datasets. This justifies that our proposed system can be employed for clinical use in hospitals and polyclinics.

Nanotechnology-based advances in the efficient delivery of melatonin.

N-[2-(5-methoxy-1H-indol-3-yl) ethyl] or simply melatonin is a biogenic amine produced by pineal gland and recently recognized various other organs. Because of a broad range of biological function melatonin is considered as a therapeutic agent with high efficacy in the treatment of multiple disorders, such as cancer, degenerative disorders and immune disease. However, since melatonin can affect receptors on the cellular membrane, in the nucleus and can act as an anti-oxidant molecule, some unwanted effects may be observed after administration. Therefore, the entrapment of melatonin in biocompatible, biodegradable and safe nano-delivery systems can prevent its degradation in circulation; decrease its toxicity with increased half-life, enhanced pharmacokinetic profile leading to improved patient compliance. Because of this, nanoparticles have been used to deliver melatonin in multiple studies, and the present article aims to cumulatively illustrate their findings.

Tumor Microenvironment, Radiology, and Artificial Intelligence: Should We Consider Tumor Periphery?

OBJECTIVES: The tumor microenvironment (TME) consists of cellular and noncellular components which enable the tumor to interact with its surroundings and plays an important role in the tumor progression and how the immune system reacts to the malignancy. In the present study, we investigate the diagnostic potential of the TME in differentiating benign and malignant lesions using image quantification and machine learning. METHODS: A total of 229 breast lesions and 220 cervical lymph nodes were included in the study. A group of expert radiologists first performed medical imaging and segmented the lesions, after which a rectangular mask was drawn, encompassing all of the contouring. The mask was extended in each axis up to 50%, and 29 radiomics features were extracted from each mask. Radiomics features that showed a significant difference in each contour were used to develop a support vector machine (SVM) classifier for benign and malignant lesions in breast and lymph node images separately. RESULTS: Single radiomics features extracted from extended contours outperformed radiologists' contours in both breast and lymph node lesions. Furthermore, when fed into the SVM model, the extended models also outperformed the radiologist's contour, achieving an area under the receiver operating characteristic curve of 0.887 and 0.970 in differentiating breast and lymph node lesions, respectively. CONCLUSIONS: Our results provide convincing evidence regarding the importance of the tumor periphery and TME in medical imaging diagnosis. We propose that the immediate tumor periphery should be considered for differentiating benign and malignant lesions in image quantification studies.

The diagnostic value of susceptibility-weighted imaging for identifying acute intraarticular hemorrhages.

PURPOSE: To evaluate the diagnostic performance of susceptibility-weighted imaging (SWI) in identifying acute intraarticular hemorrhages and differentiating blood from other types of joint effusions. METHODS: Thirty-two patients (21 men, 11 women; mean age 38.7 ± 16.5 SD) clinically suspected of having joint effusion were prospectively included. All the patients underwent both conventional MRI and SWI. Two radiologists independently reviewed the conventional MRI images and scored the likelihood of intraarticular hemorrhage using a 5-level scoring system. Immediately thereafter, SWI images of each patient were also provided for the radiologists, and the scoring was repeated evaluating the conventional MRI and SWI images together. The patients underwent joint aspiration or surgical operation as the reference standard. The area under the curve (AUC) of conventional MRI and conventional MRI + SWI methods were calculated and compared. The weighted kappa analysis was used to evaluate the interobserver agreement. RESULTS: Traumatic knee injury comprised the majority of study sample. Eighteen out of 32 of the patients were proven to have intraarticular hemorrhage. Using the conventional MRI, reader 1 and 2 achieved AUCs of 0.67 (p = 0.09) and 0.53 (p = 0.76), respectively. Following the addition of SWI, reader 1 and 2 achieved AUCs of 0.96 (p = 0.0001) and 0.95 (p = 0.0001), respectively, and interobserver agreement improved from Κ = 0.61 to Κ = 0.93. Accordingly, difference between the AUCs was 0.28 (p = 0.003) and 0.42 (p = 0.0001) for reader 1 and 2, respectively. CONCLUSIONS: If confirmed by future studies, SWI enables the reliable and accurate diagnosis of acute intraarticular hemorrhages.

Radiofrequency ablation of parathyroid adenomas causing primary hyperparathyroidism: A report of 27 patients.

PURPOSE: To study treatment outcome of parathyroid adenomas using ultrasound-guided radiofrequency ablation. METHODS: Twenty-seven patients with a single adenoma of the parathyroid gland were included in the study. Using color Doppler ultrasonography, the lesion and its characteristics were determined, and dextrose was injected to dissect the gland from the surrounding structures. The ablation process was done with 6-12 watts of power. RESULTS: No complications were seen in any of the subjects. A significant reduction was seen in serum parathyroid hormone (PTH) and calcium levels after treatment. PTH levels showed a median decrease of 13.8%, and a median decrease of 8.2% was seen in serum calcium levels (p < 0.001). Phosphorus levels did not change significantly after treatment. In 1-month follow-up of patients, the lesion size had decreased considerably. In long-term follow-up, 11 of 20 patients having subsequent imaging had indistinguishable lesions. CONCLUSION: Our results showed that RFA of parathyroid adenomas caused a significant reduction in biomedical indicators of disease and resulted in a significant reduction or disappearance of the lesion in the majority of the patients while having no considerable complications.

Angiotensin-converting enzyme as a new immunologic target for the new SARS-CoV-2.

The coronavirus disease 2019 (COVID-19) pandemic has affected the daily lives of millions of people worldwide and had caused significant mortality; hence, the assessment of therapeutic options is of great interest. The leading cause of death among COVID-19 patients is acute respiratory distress syndrome caused by hyperinflammation secondary to cytokine release syndrome (CRS). Cytokines, such as tumor necrosis factor-α, interleukin-6, interferon-γ and interleukin-10, are the main mediators of CRS. Based on recent evidence, the angiotensin-converting enzyme (ACE) II is known to be the target of the COVID-19 spike protein, which enables the virus to penetrate human cells. ACE II also possesses an anti-inflammatory role in many pathologies such as cardiovascular disease, hypertension, diabetes mellitus and other conditions, which are the main risk factors of poor prognosis in COVID-19 infection. Changes in tissue ACE II levels are associated with many diseases and hyperinflammatory states, and it is assumed that elevated levels of ACE II could aggravate the course of COVID-19 infection. Therefore, the use of renin-angiotensin-aldosterone system inhibitors (RASis) in COVID-19 patients could be hypothetically considered, though sufficient evidence is not presented by the scientific community. In this work, based on the most recent pieces of evidence, the roles of RAS and RASi in immunologic interactions are addressed. Furthermore, the molecular and immunologic aspects of RASi and their potential significance in COVID-19 are discussed.

A practical artificial intelligence system to diagnose COVID-19 using computed tomography: A multinational external validation study.

Computed tomography has gained an important role in the early diagnosis of COVID-19 pneumonia. However, the ever-increasing number of patients has overwhelmed radiology departments and has caused a reduction in quality of services. Artificial intelligence (AI) systems are the remedy to the current situation. However, the lack of application in real-world conditions has limited their consideration in clinical settings. This study validated a clinical AI system, COVIDiag, to aid radiologists in accurate and rapid evaluation of COVID-19 cases. 50 COVID-19 and 50 non-COVID-19 pneumonia cases were included from each of five centers: Argentina, Turkey, Iran, Netherlands, and Italy. The Dutch database included only 50 COVID-19 cases. The performance parameters namely sensitivity, specificity, accuracy, and area under the ROC curve (AUC) were computed for each database using COVIDiag model. The most common pattern of involvement among COVID-19 cases in all databases were bilateral involvement of upper and lower lobes with ground-glass opacities. The best sensitivity of 92.0% was recorded for the Italian database. The system achieved an AUC of 0.983, 0.914, 0.910, and 0.882 for Argentina, Turkey, Iran, and Italy, respectively. The model obtained a sensitivity of 86.0% for the Dutch database. COVIDiag model could diagnose COVID-19 pneumonia in all of cohorts with AUC of 0.921 (sensitivity, specificity, and accuracy of 88.8%, 87.0%, and 88.0%, respectively). Our study confirmed the accuracy of our proposed AI model (COVIDiag) in the diagnosis of COVID-19 cases. Furthermore, the system demonstrated consistent optimal diagnostic performance on multinational databases, which is critical to determine the generalizability and objectivity of the proposed COVIDiag model. Our results are significant as they provide real-world evidence regarding the applicability of AI systems in clinical medicine.

Application of shear wave elastography and median nerve cross-section area in the diagnosis and staging of carpal tunnel syndrome: a case-control study.

PURPOSE: Imaging is gaining a more prominent role in the diagnosis of carpal tunnel syndrome (CTS), especially ultrasonography. Shear wave elastography (SWE) is a novel qualitative method to study mechanical changes in tissue. In this study, we aim to assess the role of SWE in diagnosing and staining of the disease. MATERIAL AND METHODS: A total of 124 wrists were included in the study. Seventy wrists had CTS, and 54 were included as the control group. All of the wrists with CTS had staging done with nerve conduction study. All patients underwent ultrasonography by an expert radiologist and had the SWE and cross-section of the median nerve determined. These values were compared among the 2 groups and different stages of CTS. The receiver operating characteristic curve was utilized to assess the diagnostic role of each of the variables. RESULTS: Cross-section area (CSA) and SWE were significantly different between the 2 groups (p = 0.0001). CSA was also significantly different among various stages of CTS. SWE was not significantly different among moderate and severe stages of CTS. Both of the variables had a good ability to distinguish mild CTS from healthy wrists (p = 0.0001). CONCLUSION: SWE can be used in diagnosing CTS and in the staging of the disease.

Computed tomography imaging findings in hospitalized patients with coronavirus disease 2019 (COVID-19): a descriptive study of 81 cases.

PURPOSE: Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has proven to be a diagnostic challenge. Early studies have shown that computed tomography (CT) imaging may be useful in diagnosis of these patients. We aim to report CT findings in a series of hospitalized patients. MATERIAL AND METHODS: A total of 81 patients were included in this study. All of the patients were hospitalized and had SARS-CoV-2 infection proven by molecular assay. All patients had a CT scan on the first day of admission. Imaging results were reviewed by two separate radiologists, and imaging findings were documented. RESULTS: Seventy-eight patients had abnormal CT imaging, while 3 had normal CT imaging. The sensitivity of CT in diagnosing coronavirus disease 2019 (COVID-19) was estimated to be 96%. The most common imaging finding was ground glass opacities, followed by septal thickening. Most lesions were located at the periphery and posterior of the lungs. Most lesions were multifocal, and involved the right lower lobe more frequently. Chest X-rays were normal in 38 patients, and the sensitivity of chest X-ray in diagnosing SARS-Cov-2 was 54%. CONCLUSIONS: CT scans could be used in diagnosis of patients with a high sensitivity (93%). No common imaging findings may also be seen alongside ground glass opacities, based on the degree of disease progression.

Melatonin: An important anticancer agent in colorectal cancer.

Colorectal cancer is one of the most common cancers among the elderly, which is also seen in the forms of hereditary syndromes occurring in younger individuals. Numerous studies have been conducted to understand the molecular and cellular pathobiology underlying colorectal cancer. These studies have found that cellular signaling pathways are at the core of colorectal cancer pathology. Because of this, new agents have been proposed as possible candidates to accompany routine therapy regimens. One of these agents is melatonin, a neuro-hormone known best for its essential role in upholding the circadian rhythm and orchestrating the many physiologic changes it accompanies. Melatonin is shown to be able to modulate many signaling pathways involved in many essential cell functions, which if deregulated cause an accelerated pace towards cancer. More so, melatonin is involved in the regulation of immune function, tumor microenvironment, and acts as an antioxidant agent. Many studies have focused on the beneficial effects of melatonin in colorectal cancers, such as induction of apoptosis, increased sensitivity to chemotherapy agents and radiotherapy, limiting cellular proliferation, migration, and invasion. The present review aims to illustrate the known significance of melatonin in colorectal cancer and to address possible clinical use.

Overcoming multidrug resistance in cancer: Recent progress in nanotechnology and new horizons.

Multidrug resistance (MDR), defined as the ability of cancer cells to gain resistance to both conventional and novel chemotherapy agents, is an important barrier in treating malignancies. Initially, it was discovered that cellular pumps dependent on ATP were the cause of resistance to chemotherapy, and further studies have found that other mechanisms such as increased metabolism of drugs, decreased drug entry, and defective apoptotic pathways are involved in this process. MDR has been the focus of numerous initiatives and countless studies have been undertaken to better understand MDR and formulate strategies to overcome its effects. The current review highlights various nano-drug delivery systems including polymeric/solid lipid/mesoporous silica/metal nanoparticles, dendrimers, liposomes, micelles, and nanostructured lipid carriers to overcome the mechanism of MDR. Nanoparticles are novel gateways to enhance the therapeutic efficacy of anticancer agents at the target site of action due to their tumor-targeting abilities, which can limit the unwanted systemic effects of chemotherapy agents and also reduce drug resistance. Additionally, other innovative strategies including RNA interference as a biological process used to inhibit or silence specific gene expression, natural products as MDR modulators with little systemic toxic effects, which interfere with the functions of proteins involved in drug efflux, and physical approaches such as combination of conventional drug administration with thermal/ultrasound/photodynamic strategies are also highlighted.

Melatonin: An atypical hormone with major functions in the regulation of angiogenesis.

Melatonin (N-acetyl-5-methoxytryptamine), a pleotropic molecule with a wide distribution, has received considerable attention in recent years, mostly because of its various major effects on tissues or cells since it has both receptor-dependent and receptor-independent actions over a wide range of concentrations. These biological and physiological functions of melatonin include regulation of circadian rhythms by modulating the expression of core oscillator genes, scavenging the reactive oxygen species and reactive nitrogen species, modulating the immune system and inflammatory response, and exerting cytoprotective and antiapoptotic effects. Given the multiple critical roles of melatonin, dysregulation of its production or any disruption in signaling through its receptors may have contributed in the development of a wide range of disorders including type 2 diabetes, aging, immune-mediated diseases, hypertension, and cancer. Herein, we focus on the modulatory effects of melatonin on angiogenesis and its implications as a therapeutic strategy in cancer and related diseases.

MicroRNAs, DNA damage response and ageing.

Ageing is a multifactorial and integrated gradual deterioration affecting the most of biological process of cells. MiRNAs are differentially expressed in the cellular senescence and play important role in regulating of genes expression involved in features of ageing. The perception of miRNAs functions in ageing regulation can be useful in clarifying the mechanisms underlying ageing and designing of therapeutic strategies. The preservation of genomic integrity through DNA damage response (DDR) is related to the process of cellular senescence. The recent studies have shown that miRNAs has directly regulated the expression of numerous proteins in DDR pathways. In this review study, DDR pathways, miRNA biogenesis and functions, current finding on DDR regulations, molecular biology of ageing and the role of miRNAs in these processes have been studied. Finally, a brief explanation about the therapeutic function of miRNAs in ageing regarding its regulation of DDR has been provided.

Predictors of coronavirus disease 19 (COVID-19) pneumonitis outcome based on computed tomography (CT) imaging obtained prior to hospitalization: a retrospective study.

PURPOSE: Computed tomography (CT) has been utilized as a diagnostic modality in the coronavirus disease 19 (COVID-19), while some studies have also suggested a prognostic role for it. This study aimed to assess the diagnostic and prognostic value of computed tomography (CT) imaging in COVID-19 patients. METHODS: This was a retrospective study of fifty patients with COVID-19 pneumonia. Twenty-seven patients survived, while 23 passed away. CT imaging was performed in all of the patients on the day of admission. Imaging findings were interpreted based on current guidelines by two expert radiologists. Imaging findings were compared between surviving and deceased patients. Lung scores were assigned to patients based on CT chest findings. Then, the receiver operating characteristic curve was used to determine cutoff values for lung scores. RESULTS: The common radiologic findings were ground-glass opacities (82%) and airspace consolidation (42%), respectively. Air bronchogram was more commonly seen in deceased patients (p = 0.04). Bilateral and multilobar involvement was more frequently found in deceased patients (p = 0.049 and 0.014, respectively). The mean number of involved lobes was 3.46 ± 1.80 lobes in surviving patients and 4.57 ± 0.60 lobes in the deceased patients (p = 0.009). The difference was statistically significant. The area under the curve for a lung score cutoff of 12 was 0.790. CONCLUSION: Air bronchogram and bilateral and multilobar involvement were more frequently seen in deceased patients and may suggest a poor outcome for COVID-19 pneumonia.

Breast artery calcification as a predictor of coronary artery calcification: a cross-sectional study.

INTRODUCTION: Coronary artery disease is the main cause of burden of disease in the world. Coronary calcification is seen as an aetiopathological event in the pathogenesis of cardiovascular diseases. Studies have shown that breast artery calcification, which is routinely found in mammography of elderly women, could be predictive of coronary artery calcification. MATERIAL AND METHODS: In this cross-sectional study, 60 women over 40 years of age were included. All of these patients had undergone mammography after having an indication to undergo a computed tomography-angiography. Breast arterial calcification and calcium scores were determined for each patient, and the paired-t test was used to analyse the data. RESULTS: The mean age of patients was 49.52 ± 8.83 years. Of these 60 women, 50% were postmenopausal and 50% were not. In 37 (61.7%) cases, mild to severe coronary calcification was observed, and 50 (83.3%) had mild to severe breast arterial calcification. There was a significant correlation between coronary calcification and breast artery calcification (p = 0.001), and there was also a significant relationship between coronary calcification and postmenopausal calcification (p < 0.001). CONCLUSIONS: Breast artery calcification can be a suitable predictor for coronary artery calcification and is a valid method for predicting cardiovascular disease probability in the future.

Accuracy of diffusion-weighted imaging in discriminating atypical vertebral haemangiomas from malignant masses in patients with vertebral lesions: a cross-sectional study.

PURPOSE: Vertebral haemangiomas are incidental findings in imaging modalities. Atypical haemangiomas are haeman-giomas rich in vascular tissue, and they are found to be hypointense in T1 sequences and hyperintense in T2 sequences, mimicking the findings of metastatic lesions. In the present study we aim to evaluate the ability of diffusion- weighted imaging to differentiate these two groups of vertebral lesions. MATERIAL AND METHODS: In the present cross-sectional study, a total of 23 lesions were included, including 10 haemangiomas and 13 malignant lesions. Diffusion-weighted imaging was used to compare atypical haemangiomas and metastatic lesions. The apparent diffusion co-efficient was determined for each lesion, and then the mean of each group was calculated. The means were then compared. Receiver operating characteristic analysis was used to determine a cut-off ADC value to differentiate these lesions. RESULTS: The difference between the mean age of the two groups was not significant. The mean ADC value for atypical haemangiomas was 1884 ± 74 × 10-6 mm2/s and 1008 ± 81 × 10-6 mm2/s for the malignant lesions. The difference between the two groups was statistically significant (p < 10-3). ROC curve analysis determined an ADC value of 958 × 10-6 mm2/s to be able to differentiate between atypical haemangiomas and malignant lesions. CONCLUSIONS: Diffusion-weighted MRI could be used to differentiate between atypical haemangiomas and malignant metastatic lesions.