Diagnostic challenge and survival analysis of pulmonary oligometastases and primary lung cancer in breast cancer patients.

BACKGROUND: The aim of this study was to compare breast cancer patients with pulmonary oligometastases (POM) and primary lung cancer (PLC) and to assess whether there were differences in clinical features, CT features, and survival outcomes between the two groups. METHODS: From January 2010 to December 2021, the clinical records of 437 with malignant pulmonary nodules who had breast cancer patients were reviewed. POM was identified in 45 patients and PLC in 43 patients after the initial detection of pulmonary nodules. The clinicopathological characteristics, CT appearance of pulmonary nodules, and survival of the two groups were compared. RESULTS: Stage II to IV breast tumors (p < 0.001), high pathological grade of breast cancer (p = 0.001), low proportion of luminal-type breast cancer (p = 0.003), and the higher serum CYFRA 21-1 level (p = 0.046) were the clinical characteristics of pulmonary nodules suggestive of POM rather than PLC. The CT features of lung nodules indicative of PLC rather than POM were the subsolid component (p < 0.001), lobulation (p = 0.010), air bronchogram (p < 0.001) and pleural indentation (p = 0.004). Ten-year survival rate for PLC was 93.2%, which was higher compared with 57.8% in those with POM (p = 0.001). CONCLUSIONS: Elevated serum CYFRA 21-1 levels and late-stage breast cancer may be beneficial for the diagnosis of POM. CT imaging appearances of the subsolid component, lobulation, air bronchogram, and pleural indentation increase the likelihood of PLC. Breast cancer patients with PLC presented better survival with attentive monitoring than those with POM.

MRI-based Quantification of Intratumoral Heterogeneity for Predicting Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer.

Background Breast cancer is highly heterogeneous, resulting in different treatment responses to neoadjuvant chemotherapy (NAC) among patients. A noninvasive quantitative measure of intratumoral heterogeneity (ITH) may be valuable for predicting treatment response. Purpose To develop a quantitative measure of ITH on pretreatment MRI scans and test its performance for predicting pathologic complete response (pCR) after NAC in patients with breast cancer. Materials and Methods Pretreatment MRI scans were retrospectively acquired in patients with breast cancer who received NAC followed by surgery at multiple centers from January 2000 to September 2020. Conventional radiomics (hereafter, C-radiomics) and intratumoral ecological diversity features were extracted from the MRI scans, and output probabilities of imaging-based decision tree models were used to generate a C-radiomics score and ITH index. Multivariable logistic regression analysis was used to identify variables associated with pCR, and significant variables, including clinicopathologic variables, C-radiomics score, and ITH index, were combined into a predictive model for which performance was assessed using the area under the receiver operating characteristic curve (AUC). Results The training data set was comprised of 335 patients (median age, 48 years [IQR, 42-54 years]) from centers A and B, and 590, 280, and 384 patients (median age, 48 years [IQR, 41-55 years]) were included in the three external test data sets. Molecular subtype (odds ratio [OR] range, 4.76-8.39 [95% CI: 1.79, 24.21]; all P < .01), ITH index (OR, 30.05 [95% CI: 8.43, 122.64]; P < .001), and C-radiomics score (OR, 29.90 [95% CI: 12.04, 81.70]; P < .001) were independently associated with the odds of achieving pCR. The combined model showed good performance for predicting pCR to NAC in the training data set (AUC, 0.90) and external test data sets (AUC range, 0.83-0.87). Conclusion A model that combined an index created from pretreatment MRI-based imaging features quantitating ITH, C-radiomics score, and clinicopathologic variables showed good performance for predicting pCR to NAC in patients with breast cancer. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Rauch in this issue.

A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer.

Patients with hormone receptor (HR)-positive tumors breast cancer usually experience a relatively low pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). Here, we derived a 10-microRNA risk score (10-miRNA RS)-based model with better performance in the prediction of pCR and validated its relation with the disease-free survival (DFS) in 755 HR-positive breast cancer patients (273, 265, and 217 in the training, internal, and external validation sets, respectively). This model, presented as a nomogram, included four parameters: the 10-miRNA RS found in our previous study, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) status, and volume transfer constant (Ktrans). Favorable calibration and discrimination of 10-miRNA RS-based model with areas under the curve (AUC) of 0.865, 0.811, and 0.804 were shown in the training, internal, and external validation sets, respectively. Patients who have higher nomogram score (>92.2) with NAC treatment would have longer DFS (hazard ratio=0.57; 95%CI: 0.39-0.83; P=0.004). In summary, our data showed the 10-miRNA RS-based model could precisely identify more patients who can attain pCR to NAC, which may help clinicians formulate the personalized initial treatment strategy and consequently achieves better clinical prognosis for patients with HR-positive breast cancer.

Pretreatment DCE-MRI-Based Deep Learning Outperforms Radiomics Analysis in Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

Purpose: To compare the performances of deep learning (DL) to radiomics analysis (RA) in predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) based on pretreatment dynamic contrast-enhanced MRI (DCE-MRI) in breast cancer. Materials and Methods: This retrospective study included 356 breast cancer patients who underwent DCE-MRI before NAC and underwent surgery after NAC. Image features and kinetic parameters of tumors were derived from DCE-MRI. Molecular information was assessed based on immunohistochemistry results. The image-based RA and DL models were constructed by adding kinetic parameters or molecular information to image-only linear discriminant analysis (LDA) and convolutional neural network (CNN) models. The predictive performances of developed models were assessed by receiver operating characteristic (ROC) curve analysis and compared with the DeLong method. Results: The overall pCR rate was 23.3% (83/356). The area under the ROC (AUROC) of the image-kinetic-molecular RA model was 0.781 [95% confidence interval (CI): 0.735, 0.828], which was higher than that of the image-kinetic RA model (0.629, 95% CI: 0.595, 0.663; P < 0.001) and comparable to that of the image-molecular RA model (0.755, 95% CI: 0.708, 0.802; P = 0.133). The AUROC of the image-kinetic-molecular DL model was 0.83 (95% CI: 0.816, 0.847), which was higher than that of the image-kinetic and image-molecular DL models (0.707, 95% CI: 0.654, 0.761; 0.79, 95% CI: 0.768, 0.812; P < 0.001) and higher than that of the image-kinetic-molecular RA model (0.778, 95% CI: 0.735, 0.828; P < 0.001). Conclusions: The pretreatment DCE-MRI-based DL model is superior to the RA model in predicting pCR to NAC in breast cancer patients. The image-kinetic-molecular DL model has the best prediction performance.

Enhanced fluorescence/magnetic resonance dual imaging and gene therapy of liver cancer using cationized amylose nanoprobe.

Recently, various technologies for targeted gene release in cancer treatment have emerged. However, most of these strategies are facing the challenge of untraceable distribution and poor antitumour treatment effects. In this study, we constructed a gene delivery system that integrated a series of components to assemble multifunctional NPs, providing a promising theranostic nanoplatform for hepatocellular carcinoma (HCC) therapy. Cationized amylose (CA), superparamagnetic iron oxide (SPIO) nanoparticles (NPs), and tetraphenylethylene (TPE) were self-assembled to form nanospheres (CSP/TPE). The prepared NPs was modified with SP94 pepide through amidation reaction, and then survivin small interfering RNA (siRNA) were loaded into the NPs to form CSP/TPE@siRNA-SP94 NPs. Our results showed that the prepared NPs had good size distribution, high RNA condensation and transfection ability. CSP/TPE@siRNA-SP94 NPs exhibited excellent fluorescence and magnetic resonance (MR) imaging properties in vitro and in vivo. The prepared targeted NPs improved Huh-7 cellular uptake in vitro, and the biodistribution of CSP/TPE@siRNA-SP94 in vivo was observed through in/ex vivo fluorescence imaging system and MRI. As survivin siRNA effectively retained in tumour cells, CSP/TPE@siRNA-SP94 NPs considerably inhibited tumour growth in vivo. In addition, H&E staining results showed that all the prepared CSP-based NPs had good biocompatibilities, as few histological changes or tumour metastasis were observed in major organs of the mice in the treatment group. Therefore, we envisage that the prepared CSP/TPE@siRNA-SP94 NPs can represent a promising strategy for HCC diagnosis and treatment.

Assessment of quantitative dynamic contrast-enhanced MRI in distinguishing different histologic grades of breast phyllode tumor.

OBJECTIVES: To investigate whether quantitative DCE-MRI (qDCE-MRI) could help distinguish breast phyllodes tumor (PT) grades. MATERIALS AND METHODS: This retrospective study included 67 breast PTs (26 benign lesions, 25 borderline lesions, and 16 malignant lesions) from April 2016 to July 2020. MRI was performed with a 1.5-T MR system. Perfusion parameters (Ktrans, kep, ve, iAUC60) derived from qDCE-MRI, tumor size, and the mean ADC value were correlated with histologic grades using Spearman's rank correlation coefficient. Ktrans, kep, ve, and iAUC60 of three histologic grades were also calculated and compared. RESULTS: The Spearman correlation coefficient with histologic grade of the tumor size was 0.578 (p < 0.001); the ADC value was not correlated with histologic grades of breast PT (p = 0.059). The Ktrans, kep, ve, and iAUC60 of benign breast PTs were significantly lower than those of borderline breast PTs (p < 0.001) and lower than those of malignant breast PTs (p < 0.001). In comparison, the Ktrans, ve, and iAUC60 of borderline breast PTs were significantly lower than those of malignant breast PTs (p < 0.001, p < 0.001, p = 0.007, respectively). For ROC analysis, AUCs of Ktrans, ve, and iAUC60 were higher than tumor size and ADC value for differentiating three PT grades. CONCLUSION: Quantitative and semi-quantitative perfusion parameters (Ktrans, ve, and iAUC60, especially Ktrans) derived from qDCE-MRI showed better diagnosis efficiency than tumor size and ADC for grading breast PTs. Therefore, qDCE-MRI may be helpful for preoperative differentiating breast PT grades. KEY POINTS: • Quantitative dynamic contrast-enhanced MRI can be used as a complementary noninvasive method to improve the differential diagnosis of breast PT. • Ktrans, ve, and iAUC60 derived from qDCE-MRI showed better diagnosis efficiency than tumor size and ADC for grading breast PTs.

Quantification of pancreatic iron overload and fat infiltration and their correlation with glucose disturbance in pediatric thalassemia major patients.

BACKGROUND: Diabetes mellitus affects more than a quarter of patients with thalassemia major (TM) worldwide, and increases the risk for cardiac complications, contributing to significant morbidity. Pancreatic iron overload (IO) and fat infiltration have been correlated with this endocrinal complication in adult TM patients. It has been shown that in adult TM patients, iron accumulation and fat infiltration are found to be heterogeneous in the pancreatic head, body, and tail region. R2* and a fat fraction (FF) generated by gradient-echo imaging can be used as quantitative parameters to assess the iron and fat contents of the pancreas. This study aimed to determine the pattern of pancreatic iron accumulation and fat infiltration in pediatric TM patients with gradient-echo imaging and evaluate the association between pancreatic IO and fat infiltration and glucose disturbances. METHODS: A total of 90 children with TM (10.7±3.1 years) were included. All patients underwent pancreatic magnetic resonance imaging (MRI) using multi-echo gradient-echo sequences. IO was measured by R2* relaxometry in 90 patients, and FF values were measured using iterative decomposition of water and fat with echo asymmetry and the least-squares estimation (IDEAL) method in 40 patients. R2* and FF were assessed in the pancreatic head, body, and tail. The global R2* and global FF values were obtained by averaging the respective values from the pancreatic head, body, and tail. The correlations between global R2*, global FF, and fasting glucose were determined using Spearman's correlation analysis. The Friedman test was used to compare R2* and FF among different pancreatic regions. Receiver operating characteristic (ROC) analysis was used to determine the performance of global R2* and global FF in discriminating impaired fasting glucose from normal fasting glucose patients. RESULTS: The global R2* was positively correlated with the global FF in the pancreas (r=0.895, P<0.001). No significant differences were found in R2* among the 3 regions of the pancreas (χ2=4.050, P=0.132), but significant differences were found in FF among the 3 pancreatic regions (χ2=16.350, P<0.001). Both global pancreatic R2* (r=0.408, P<0.001) and global FF (r=0.523, P=0.001) were positively correlated with fasting glucose. ROC analysis showed that global pancreatic R2* and global FF had an area under the curve of 0.769 and 0.931 (both P<0.001), respectively, in discriminating between impaired and normal glucose function patients. CONCLUSIONS: Pediatric TM patients can have homogeneous iron siderosis and heterogeneous fat infiltration in the pancreas as measured by gradient-echo imaging, both of which are risk factors for diabetes.

Quantitative dynamic contrast-enhanced MR imaging can be used to predict the pathologic stages of oral tongue squamous cell carcinoma.

BACKGROUND: To investigate whether quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) pharmacokinetic parameters can be used to predict the pathologic stages of oral tongue squamous cell carcinoma (OTSCC). METHODS: For this prospective study, DCE-MRI was performed in participants with OTSCC from May 2016 to June 2017. The pharmacokinetic parameters, including Ktrans, Kep, Ve, and Vp, were derived from DCE-MRI by utilizing a two-compartment extended Tofts model and a three-dimensional volume of interest. The postoperative pathologic stage was determined in each patient based on the 8th AJCC cancer staging manual. The quantitative DCE-MRI parameters were compared between stage I-II and stage III-IV lesions. Logistic regression analysis was used to determine independent predictors of tumor stages, followed by receiver operating characteristic (ROC) analysis to evaluate the predictive performance. RESULTS: The mean Ktrans, Kep and Vp values were significantly lower in stage III-IV lesions compared with stage I-II lesions (p = 0.013, 0.005 and 0.011, respectively). Kep was an independent predictor for the advanced stages as determined by univariate and multivariate logistic analysis. ROC analysis showed that Kep had the highest predictive capability, with a sensitivity of 64.3%, a specificity of 82.6%, a positive predictive value of 81.8%, a negative predictive value of 65.5%, and an accuracy of 72.5%. CONCLUSION: The quantitative DCE-MRI parameter Kep can be used as a biomarker for predicting pathologic stages of OTSCC.

Breast fibromatosis: Imaging and clinical findings.

Breast fibromatosis is a rare histologically benign tumor with local aggressive potential, and imaging and clinical findings of breast fibromatosis require attention. We retrospectively evaluated the images of 20 patients with histologically proven breast fibromatosis on mammography, magnetic resonance imaging (MRI), and ultrasonography. The lesions were assessed concerning the location, fascia involvement, imaging characteristics, and follow-up outcomes. Altogether, there were 22 lesions: 10 lesions involved the superficial fascia system including four lesions additionally involving the deep fascia and pectoralis major, and 12 lesions were inside the glandular parenchyma with two lesions originated from the prior surgery site. The detection rates of mammography, ultrasound, and MRI for breast fibromatosis were 33.3% (3/9), 90% (18/20), and 100% (3/3), respectively. We found that fascia involvement may be a characteristic of breast fibromatosis. The lesion located inside glandular parenchyma is prone to be underestimated, whereas combined MR with ultrasound is recommended for the diagnosis. The complete excision with negative margins is important for a good prognosis.

The Usefulness of Bayesian Network in Assessing the Risk of Triple-Negative Breast Cancer.

RATIONALE AND OBJECTIVES: To evaluate a Bayesian network (BN) model learned from epidemiological and clinical information, and various MRI parameters for predicting the risk of triple-negative breast cancer (TNBC). MATERIALS AND METHODS: For this retrospective study, 214 women (mean age ± standard deviation, 50.5±10.6 years) with breast cancer were included between April 2016 and April 2018. All patients underwent MRI, including dynamic contrast-enhanced (DCE)-MRI. The morphologic MRI features, the pattern of the time-signal intensity curve (TIC) and the kinetic parameters were obtained for each lesion. The epidemiological and clinical parameters and those imaging parameters were used to construct BN model to estimate TNBC risk. ROC curves upon probability estimates were used to determine the performance of the BN using area under the ROC curves (Az), sensitivity, specificity, and accuracy. RESULTS: A BN model consisted of 16 epidemiological and clinical characteristics, morphologic MRI features, and quantitative DCE-MRI parameters were established. The posttest probability table showed that patients with age <35 years, mass-like lesions, type I TIC, and MaxCon ≥ 0.186 were at the highest risk of TNBC. The constructed BN model had an Az of 0.663 (95% confidence interval [CI]: 0.654, 0.672), sensitivity of 0.660 (95% CI: 0.644, 0.675), specificity of 0.740 (95% CI: 0.726, 0.753) and accuracy of 0.724 (95% CI: 0.714, 0.733) in classifying TNBC. CONCLUSION: The BN model integrating epidemiological and clinical characteristics, morphologic and kinetic MRI parameters provide a noninvasive analytical approach for preoperative prediction of the risk of TNBC.

A bibliometric-based analysis of the high-value application of Chlorella.

This bibliometric-based review analyses the trends in 1010 published articles (1990 to mid-2018) on the high-value application of Chlorella, and illustrates the evolution and latest tendencies at a global level by the number of publications and their distribution, issuing institutions and countries or regions, the sources and research direction, as well as the core-author and keywords. The results demonstrated that there is a burst in terms of the number of articles, and China, USA, Mexico, and Japan are the dominant countries in this area. The most relevant journals with this subject are Bioresource Technology and Hydrobiology, and the research mainly focuses on marine and freshwater biology, biotechnology and applied microbiology, energy and fuels, food science and technology, and environmental sciences. Overall, bibliometric analysis has shown that Chlorella application research is a very active field, and the future research will be conducted into construction of genetic engineering algae, high-density and low-cost culture systems, efficient harvesting and separation techniques, effective energy conversion, integrated photo-bioreactors, and molecular biology technology. Wastewater treatment, CO2 bio-fixation, biomass production, and biosynthesis of useful substances by cultivating microalgae are promising research fields.

Axillary Sentinel Lymph Nodes in Breast Cancer: Quantitative Evaluation at Dual-Energy CT.

Purpose To evaluate the diagnostic performance of quantitative parameters derived from dual-energy CT for the preoperative diagnosis of metastatic sentinel lymph nodes (SLNs) in participants with breast cancer. Materials and Methods For this prospective study, dual-phase contrast agent-enhanced CT was performed in female participants with breast cancer from June 2015 to December 2017. Quantitative dual-energy CT parameters and morphologic parameters were compared between metastatic and nonmetastatic SLNs. The quantitative parameters were fitted to univariable and multivariable logistic regression models. The diagnostic role of morphologic and quantitative parameters was analyzed by receiver operating characteristic curves and compared by using the McNemar test. Results This study included 193 female participants (mean age, 47.6 years ± 10.1; age range, 22-79 years). Quantitative dual-energy CT parameters including slope of the spectral Hounsfield unit curve (λHu) measured at both arterial and venous phases, normalized iodine concentration at both arterial and venous phase, and normalized effective atomic number at the venous phase were higher in metastatic than in nonmetastatic SLNs (P value range, ≤.001 to .031). Univariable and multivariable logistic regression analyses showed that venous phase λHu (in Hounsfield units per kiloelectron-volt) was the best single parameter for the detection of metastatic SLNs. The accuracy of the venous phase λHu for detecting metastatic SLNs was 90.5% on a per-lymph node basis and 87.0% on a per-patient basis. The accuracy and specificity at venous phase λHu was higher than their counterparts in the morphologic parameters (P < .001). Conclusion Dual-energy CT is a complementary means for the preoperative identification of sentinel lymph nodes metastases in participants with breast cancer. © RSNA, 2018 Online supplemental material is available for this article.

Discrimination between benign and malignant breast lesions using volumetric quantitative dynamic contrast-enhanced MR imaging.

OBJECTIVE: To determine the diagnostic performance of volumetric quantitative dynamic contrast-enhanced MRI (qDCE-MRI) in differentiation between malignant and benign breast lesions. METHODS: DCE-MRI was performed in 124 patients with 136 breast lesions. Quantitative pharmacokinetic parameters Ktrans, Kep, Ve, Vp and semi-quantitative parameters TTP, MaxCon, MaxSlope, AUC were obtained by using a two-compartment extended Tofts model and three-dimensional volume of interest. Morphologic features (lesion size, margin, internal enhancement pattern) and time-signal intensity curve (TIC) type were also assessed. Logistic regression analysis was used to determine predictors of malignancy, followed by receiver operating characteristics (ROC) analysis to evaluate the diagnostic performance. RESULTS: qDCE parameters (Ktrans, Kep, Vp, TTP, MaxCon, MaxSlope and AUC), morphological parameters and TIC type were significantly different between malignant and benign lesions (P≤0.001). Multivariate logistic regression analyses showed that Ktrans, Kep, MaxSlope, size, margin and TIC type were independent predictors of malignancy. The diagnostic accuracy of logistic models based on qDCE parameters alone, morphological features plus TIC type, and all parameters combined was 94.9%, 89.0%, and 95.6% respectively. CONCLUSION: qDCE-MRI can be used to improve diagnostic differentiation between benign and malignant breast lesions in relation to morphology and kinetic analysis. KEY POINTS: • qDCE-MRI parameters are useful for discriminating between malignant and benign breast lesions. • K trans , K ep and MaxSlope were independent predictors of breast malignancy. • qDCE-MRI has a better diagnostic ability than morphology and kinetic analysis. • qDCE-MRI can be used to improve the diagnostic accuracy of breast malignancy.

Magnetic Cationic Amylose Nanoparticles Used to Deliver Survivin-Small Interfering RNA for Gene Therapy of Hepatocellular Carcinoma In Vitro.

Amylose is a promising nanocarrier for gene delivery in terms of its good biocompatibility and high transfection efficiency. Small interfering RNA against survivin (survivin-siRNA) can cause tumor apoptosis by silencing a hepatocellular carcinoma (HCC)-specific gene at the messenger RNA level. In this study, we developed a new class of folate-functionalized, superparamagnetic iron oxide (SPIO)-loaded cationic amylose nanoparticles to deliver survivin-siRNA to HCC cells. The cellular uptake of nanocomplexes, cytotoxicity, cell apoptosis, and gene suppression mediated by siRNA-complexed nanoparticles were tested. The results demonstrated that folate-functionalized, SPIO-loaded cationic amylose nanoparticles can mediate a specific and safe cellular uptake of survivin-siRNA with high transfection efficiency, resulting in a robust survivin gene downregulation in HCC cells. The biocompatible complex of cationic amylose could be used as an efficient, rapid, and safe gene delivery vector. Upon SPIO loading, it holds a great promise as a theranostic carrier for gene therapy of HCC.

Assessment of Nonalcoholic Fatty Liver Disease in Rats Using Quantitative Dynamic Contrast-Enhanced MRI.

PURPOSE: To evaluate the usefulness of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in the assessment of nonalcoholic fatty liver disease (NAFLD) severity. MATERIALS AND METHODS: Liver DCE-MRI at 3.0T was performed in 36 adult Sprague-Dawley rats with methionine choline-deficient diet-induced NAFLD and 10 untreated control rats. Pharmacokinetic parameters of DCE-MRI including Ktrans , Kep , Ve , Vp , and hepatic portal index (HPoI) were measured using the dual-input extended Tofts model. Animals were categorized as normal (n = 10), simple steatosis (SS, n = 11), borderline nonalcoholic steatohepatitis (bNASH, n = 20), and NASH (n = 5) subgroups according to the NAFLD activity score system, and classified into F0 (n = 24), F1 (n = 11), F2 (n = 7), and F3 (n = 4) subgroups according to an established scoring system. DCE-MRI parameters were compared. Receiver operating characteristic analyses were performed to assess the diagnostic performance of various DCE-MRI parameters in grading NAFLD activity and staging liver fibrosis. RESULTS: Ktrans and HPoI were elevated with increasing severity of NAFLD activity and increased fibrosis stage. The areas under the receiver operating characteristic curve (AUROCs) of HPoI ranged from 0.895-0.951 for discriminating between different grades of NAFLD activity, and the AUROC was 0.852 for discriminating F0 stage from overall F1-F3 stages. The AUROC of Ktrans for discriminating non-NASH from bNASH and NASH groups was 0.968, and 0.898 for discriminating between normal and overall fibrosis groups. CONCLUSION: DCE-MRI may play a role in assessing NAFLD severity. LEVEL OF EVIDENCE: 1 J. MAGN. RESON. IMAGING 2017;45:1485-1493.

Comparison of multislice breath-hold and 3D respiratory triggered T1 ρ imaging of liver in healthy volunteers and liver cirrhosis patients in 3.0 T MRI.

PURPOSE: To compare visual quality and quantitative measurements of multislice (MS) breath-hold and 3D respiratory-triggered T1 ρ sequences. MATERIALS AND METHODS: T1 ρ scans including MS BLOCK T1 ρ, MS HS8 T1 ρ, and 3D BLOCK T1 ρ were performed on 40 healthy volunteers and 17 liver cirrhosis patients on 3.0T magnetic resonance imaging (MRI). The MS breath-hold methods scanned three slices while the 3D method covered 26 slices. Visual scores of image quality, T1 ρ measurements of the three sequences, and T1 ρ values of healthy volunteers and cirrhosis patients were compared using parametric tests. RESULTS: Average visual scores for volunteers and patients of the three sequences were 3.19 and 2.82 for MS BLOCK T1 ρ; 3.71 and 3.59 for MS HS8 T1 ρ; 3.29 and 3.59 for 3D BLOCK T1 ρ, respectively. Difference of visual scores among the three groups was significant (P < 0.001). Differences in T1 ρ values among the three methods were significant (P < 0.001). Difference of T1 ρ between MS BLOCK T1 ρ and 3D BLOCK T1 ρ was not significant (volunteer: P = 0.82, patient: 0.92) while the difference of T1 ρ between MS BLOCK T1 ρ and MS HS8 T1 ρ, MS HS8 T1 ρ and 3D BLOCK T1 ρ was significant in both volunteers and patients (P < 0.01). Differences of T1 ρ between healthy volunteers and patients were all significant in three T1 ρ sequences (P = 0.04, 0.004, 0.03). CONCLUSION: Of the tested sequences, the image quality of MS HS8 T1 ρ was best, but 3D BLOCK T1 ρ with respiratory triggering should also be considered as an alternative sequence for clinical diagnosis of liver cirrhosis due to its superior coverage. J. MAGN. RESON. IMAGING 2016;44:906-913.

Value of severe liver iron overload for assessing heart iron levels in thalassemia major patients.

PURPOSE: The relationship between severe liver iron overload (LIO) and heart iron overload (HIO) in transfusion-dependent patients with thalassemia major (TM) is uncertain. Whether severe LIO can serve as an index for assessing heart iron deposition has vital clinical significance. Therefore, our aim is to determine if a close relationship exists between severe LIO and HIO. MATERIALS AND METHODS: We examined 110 TM patients who underwent T2* measurement in the liver and heart on a 1.5 Tesla MRI scanner. Various statistical analysis methods were used to assess the relationship. RESULTS: Most of these patients suffered from severe LIO (58.18%, liver T2* < 1.4 ms). Both Pearson's and Spearman's tests showed a significant correlation between liver T2* and heart T2* values (with a correlation coefficient of 0.408 and 0.550, respectively, both P < 0.0001). A nonlinear model, with the equation of Heart T2* = 37.974-17.684 / Liver T2*, was found to be the best model to indicate the relationship between liver T2* and heart T2*. Receiver operating characteristic (ROC) analysis showed the area under the ROC curve of liver T2* and serum ferritin for predicting HIO was 0.812 (95% confidence interval [CI]: 0.731-0.892; P < 0.0001) and 0.69 (95% CI: 0.585-0.795; P = 0.001), respectively. CONCLUSION: Our preliminary data suggest the existence of a close relationship between severe LIO and HIO. High liver iron levels appear to increase the risk of heart iron deposition. This further supports the concept of critical liver iron concentration, above which elevated heart iron is present. J. MAGN. RESON. IMAGING 2016;44:880-889.

MRI assessment of excess cardiac iron in thalassemia major: When to initiate?

BACKGROUND: To determine optimal initial age of cardiac iron screening with magnetic resonance imaging (MRI) T2* in patients with thalassemia major (TM). METHODS: We retrospectively reviewed black blood cardiac T2* assessments from 102 TM patients from the ages of 3 to 32 years. Cases of patients under and above 7 years old with detectable cardiac iron overload were analyzed separately. Associations between cardiac T2* and various factors, such as serum ferritin (SF), patient age and hepatic T2*, were assessed using either scatterplots or regression. Images were evaluated by two independent radiologists. RESULTS: With a T2* cut-off value of 20 ms, no patient under 5 years old showed cardiac iron overload. Three of 19 (15.8%) patients under 7 years of age had a cardiac T2* ≤ 20 ms (5.5 to 7 years) but none had ≤10 ms, while 35 of 83 (42.2%) patients above 7 years old had a cardiac T2* ≤ 20 ms (8 to 32 years) and 18 of them ≤10 ms. Cardiac T2* correlated weakly with serum ferritin and liver T2* (r = -0.39 and 0.41, respectively, both P < 0.001), but not with patient age (P > 0.05). CONCLUSION: Cardiac iron overload can occur in young TM patients, even as young as 5.5 years old. Assessment of cardiac iron with T2* might need to begin as early as 5 years old if suboptimal chelation therapy is administered.