Contrast-enhanced MRI Examinations Research Articles

Ovarian–Adnexal Reporting and Data System (O-RADS) MRI Scoring: Diagnostic Accuracy, Interobserver Agreement, and Applicability to Machine Learning

Abstract Objectives To evaluate the interobserver agreement and diagnostic accuracy of ovarian–adnexal reporting and data system magnetic resonance imaging (O-RADS MRI) and applicability to machine learning. Material and methods Dynamic contrast-enhanced pelvic MRI examinations 471 lesions were retrospectively analyzed and assessed by three radiologists according to O-RADS MRI criteria. Radiomic data were extracted from T2, and post-contrast fat-suppressed T1-weighted images. Using these data, an artificial neural network (ANN), support vector machine, random forest, and naive Bayes models were constructed. Results Among all readers, the lowest agreement was found for the O-RADS 4 group (kappa: 0.669 (95% confidence interval [CI] 0.634–0.733)), followed by the O-RADS 5 group (kappa: 0.709 (95% CI 0.678–0.754)). O-RADS 4 predicted a malignancy with an area under the curve (AUC) value of 74.3% (95% CI 0.701–0.782), and O-RADS 5 with an AUC of 95.5% (95% CI 0.932–0.972),(p < 0.001). Among the machine learning models, ANN achieved the highest success, distinguishing O-RADS groups with an AUC of 0.948, a precision of 0.861, and a recall of 0.824. Conclusion The interobserver agreement and diagnostic sensitivity of the O-RADS MRI in assigning O-RADS 4–5 were not perfect, indicating a need for structural improvement. Integrating artificial intelligence into MRI protocols may enhance their performance. Advances in knowledge Machine learning can achieve high accuracy in the correct classification of O-RADS MRI. Malignancy prediction rates were 74% for O-RADS 4 and 95% for O-RADS 5.

Smart forecasting of artifacts in contrast-enhanced breast MRI before contrast agent administration

ObjectivesTo evaluate whether artifacts on contrast-enhanced (CE) breast MRI maximum intensity projections (MIPs) might already be forecast before gadolinium-based contrast agent (GBCA) administration during an ongoing examination by analyzing the unenhanced T1-weighted images acquired before the GBCA injection.Materials and methodsThis IRB-approved retrospective analysis consisted of n = 2884 breast CE MRI examinations after intravenous administration of GBCA, acquired with n = 4 different MRI devices at different field strengths (1.5 T/3 T) during clinical routine. CE-derived subtraction MIPs were used to conduct a multi-class multi-reader evaluation of the presence and severity of artifacts with three independent readers. An ensemble classifier (EC) of five DenseNet models was used to predict artifacts for the post-contrast subtraction MIPs, giving as the input source only the pre-contrast T1-weighted sequence. Thus, the acquisition directly preceded the GBCA injection. The area under ROC (AuROC) and diagnostics accuracy scores were used to assess the performance of the neural network in an independent holdout test set (n = 285).ResultsAfter majority voting, potentially significant artifacts were detected in 53.6% (n = 1521) of all breast MRI examinations (age 49.6 ± 12.6 years). In the holdout test set (mean age 49.7 ± 11.8 years), at a specificity level of 89%, the EC could forecast around one-third of artifacts (sensitivity 31%) before GBCA administration, with an AuROC = 0.66.ConclusionThis study demonstrates the capability of a neural network to forecast the occurrence of artifacts on CE subtraction data before the GBCA administration. If confirmed in larger studies, this might enable a workflow-blended approach to prevent breast MRI artifacts by implementing in-scan personalized predictive algorithms.Clinical relevance statementSome artifacts in contrast-enhanced breast MRI maximum intensity projections might be predictable before gadolinium-based contrast agent injection using a neural network.Key Points• Potentially significant artifacts can be observed in a relevant proportion of breast MRI subtraction sequences after gadolinium-based contrast agent administration (GBCA).• Forecasting the occurrence of such artifacts in subtraction maximum intensity projections before GBCA administration for individual patients was feasible at 89% specificity, which allowed correctly predicting one in three future artifacts.• Further research is necessary to investigate the clinical value of such smart personalized imaging approaches.

Uptake of Gadolinium-Based Contrast Agents by Blood Cells During Contrast-Enhanced MRI Examination.

Gadolinium-based contrast agents (GBCAs) are routinely used in magnetic resonance imaging (MRI) examinations. However, there is limited knowledge about the interaction with and distribution of the drug in human cells. This lack of knowledge is surprising, given that the first interaction of the drug occurs with blood cells. Moreover, recent studies reported gadolinium (Gd) deposition within organs, such as the brain. Hence, this study is aiming to determine the uptake of GBCA in blood cells of patients undergoing contrast-enhanced MRI (ce-MRI) examination. Human blood was exposed to either gadoterate meglumine (Gd-DOTA) or Eu-DOTA in vitro or was collected from patients undergoing ce-MRI with Gd-DOTA. Uptake of contrast agents (CAs) by blood cells was quantified by Gd measurements using single-cell inductively coupled plasma mass spectrometry (SC-ICP-MS) or, to confirm Gd-DOTA uptake, by a complementary method using Eu-DOTA by time-resolved fluorescence spectroscopy, respectively. Uptake of Gd-DOTA or Eu-DOTA into white blood cells (WBCs) ex vivo was detectable by SC-ICP-MS and time-resolved fluorescence spectroscopy. The intracellular concentrations were estimated to be in the range of 1-3 μM. However, no CA uptake into erythrocytes was detected with either method. In total, 42 patients between 30 and 84 years old (24 men, 18 women) were enrolled. White blood cells' uptake of Gd was measured by SC-ICP-MS. Isolated WBCs from patients who underwent ce-MRI examination showed substantial Gd uptake; however, the studied patient group showed an inhomogeneous distribution of Gd uptake. Measurements immediately after MRI examination indicated 21-444 attogram/WBC, corresponding to an intracellular Gd concentration in the range from 0.2 to 5.5 μM. This study confirms the ex vivo uptake of GBCA by WBCs and provides the first evidence that GBCA is indeed taken up by WBCs in vivo by patients undergoing ce-MRI examination. However, the observed Gd uptake in WBCs does not follow a log-normal distribution commonly observed in the fields of environmental studies, biology, and medicine. Whether cellular uptake of GBCA is linked to the observed deposition of Gd remains unclear. Therefore, studying the interaction between GBCA and human cells may clarify crucial questions about the effects of Gd on patients after MRI examinations.

Where does the gadolinium go? A review into the excretion and retention of intravenous gadolinium.

Gadolinium-based contrast agents (GBCAs) are commonly used in medical imaging. Most intravenously (IV) administered gadolinium is excreted via the kidneys, and pathological retention in renal failure leading to nephrogenic systemic fibrosis (NSF) is well described. More recently, retention of gadolinium in the body in the absence of renal disease has been identified, with unknown clinical consequences. Many patients are aware of this, either through the media or via comprehensive consent documentation. Some internet sites, without hard evidence, have suggested a constellation of possible symptoms associated with GBCA retention. Recent experience with patients ascribing symptoms to a contrast-enhanced MRI examination prompted this review of the fate of injected GBCA after MRI study, and of information available to patients online regarding gadolinium retention.

Assessing synchronous ovarian metastasis in gastric cancer patients using a clinical-radiomics nomogram based on baseline abdominal contrast-enhanced CT: a two-center study

BackgroundTo build and validate a radiomics nomogram based on preoperative CT scans and clinical data for detecting synchronous ovarian metastasis (SOM) in female gastric cancer (GC) cases.MethodsPathologically confirmed GC cases in 2 cohorts were retrospectively enrolled. All cases had presurgical abdominal contrast-enhanced CT and pelvis contrast-enhanced MRI and pathological examinations for any suspicious ovarian lesions detected by MRI. Cohort 1 cases (n = 101) were included as the training set. Radiomics features were obtained to develop a radscore. A nomogram combining the radscore and clinical factors was built to detect SOM. The bootstrap method was carried out in cohort 1 as internal validation. External validation was carried out in cohort 2 (n = 46). Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA) and the confusion matrix were utilized to assess the performances of the radscore, nomogram and subjective evaluation model.ResultsThe nomogram, which combined age and the radscore, displayed a higher AUC than the radscore and subjective evaluation (0.910 vs 0.827 vs 0.773) in the training cohort. In the external validation cohort, the nomogram also had a higher AUC than the radscore and subjective evaluation (0.850 vs 0.790 vs 0.675). DCA and the confusion matrix confirmed the nomogram was superior to the radscore in both cohorts.ConclusionsThis pilot study showed that a nomogram model combining the radscore and clinical characteristics is useful in detecting SOM in female GC cases. It may be applied to improve clinical treatment and is superior to subjective evaluation or the radscore alone.

Accuracy of Diffusion Weighted Imaging in Assessment of Pelvic Lymphnode Metastasis in Patients with Endometrial Cancer.

To evaluate the sensitivity and specificity of diffusion-weighted imaging in determining metastatic pelvic lymph nodes in patients of endometrial cancer and comparing its accuracy with contrast-enhanced sequence of MRI, taking histopathology as gold standard. Retrospective Study. Place and Duration of the Study: Department of Radiology, the Aga Khan University Hospital Karachi, from January to December 2021. Fifty-eight adult females with biopsy proven endometrial carcinoma and complete medical records were included through convenience sampling. Patients who did not have complete medical records were excluded. Studied variables included signal characteristics of lymph nodes and their short axis diameter. The sensitivity and specificity of DWI and contrast-enhanced MRI for evaluation of diseased lymph nodes were calculated using histopathology as the gold standard. Among 58 patients with histopathologically proven endometrial cancer, 14 had metastatic lymphadenopathy. DWI-weighted imaging in the evaluation of metastatic and non-metastatic lymph nodes had sensitivity of 81.1% while specificity, the positive and negative predictive value of 88.8%, 72.2%, and 82.5% and on contrast-enhanced imaging as 66.6%, 58.1%, 35.7%, and 83.3%, respectively. The DWI shows better accuracy in evaluation and discrimination between metastatic and non-metastatic lymph nodes as compared to contrast-enhanced MRI examination for the evaluation of diseased lymph nodes in patients with endometrial cancer. DWI, Contrast-enhanced MRI, Lymph node, Endometrial cancer.

Post treatment and 3 month contrast enhanced MRI findings following HIFU of submucosal fibroids: a retrospective study

Purpose This study used contrast-enhanced MRI (CE-MRI) examination to assess the efficacy of high-intensity focused ultrasound (HIFU) for submucosal fibroids. Methods A total of 81 submucosal fibroids, including 33 cases of type 1, 29 cases of type 2, and 19 cases of type 2–5, treated by HIFU were retrospectively reviewed. CE-MRI was performed in all cases immediately after HIFU, the non-perfused volume ratio (NPVR) and the degree of endometrial impairment were recorded. Thereafter, CE-MRI was repeated in all cases after three months, and the change of fibroid volume shrinkage rate (FVSR), NPVR and the degree of endometrial impairment were recorded. Results The immediate NPVR was 86.4 ± 19.3% in type 1, 90.0 ± 13.3% in type 2 and 90.3 ± 7.2% in type 2–5. Among 81 fibroids, grades 0, 1, 2 and 3 endometrial impairments were observed in 38.3%, 16.1%, 14.8% and 30.9%, respectively. Three months later, NPVR was 68.0 ± 36.4% in type 1, 74.3 ± 27.7% in type 2 and 85.0 ± 16.1% in type 2–5. Grades 0, 1, 2 and 3 endometrial impairments were observed in 64.2%, 23.5%, 9.9% and 2.4%.FVSR was 49.0 ± 1.3% in type 1, 39.6 ± 1.7% in type 2 and 37.2 ± 2.1% in type 2–5. The FVSR in submucosal fibroid type 1 was superior to type 2 and type 2–5 (p < 0.05). The NPVR of submucosal fibroids in type 2–5 were higher than type 1 (p < 0.05) .There was no difference among different types of submucosal fibroids in endometrial impairment (p > 0.05) three months after HIFU. Conclusions At three months after HIFU, FVSR was better for submucosal fibroid type 1 than for type 2 and type 2–5. And there was no difference in endometrial impairment among the different types of submucosal fibroid groups.

Artificial Intelligence to Reduce or Eliminate the Need for Gadolinium-Based Contrast Agents in Brain and Cardiac MRI: A Literature Review.

Brain and cardiac MRIs are fundamental noninvasive imaging tools, which can provide important clinical information and can be performed without or with gadolinium-based contrast agents (GBCAs), depending on the clinical indication. It is currently a topic of debate whether it would be feasible to extract information such as standard gadolinium-enhanced MRI while injecting either less or no GBCAs. Artificial intelligence (AI) is a great source of innovation in medical imaging and has been explored as a method to synthesize virtual contrast MR images, potentially yielding similar diagnostic performance without the need to administer GBCAs. If possible, there would be significant benefits, including reduction of costs, acquisition time, and environmental impact with respect to conventional contrast-enhanced MRI examinations. Given its promise, we believe additional research is needed to increase the evidence to make these AI solutions feasible, reliable, and robust enough to be integrated into the clinical framework. Here, we review recent AI studies aimed at reducing or replacing gadolinium in brain and cardiac imaging while maintaining diagnostic image quality.

Evaluation of Hepatotoxicity from Peptide Receptor Radionuclide Therapy in Patients with Gastroenteropancreatic Neuroendocrine Tumors and a Very High Liver Tumor Burden.

The aim of the current study was to describe the risk of hepatotoxicity for patients with gastroenteropancreatic neuroendocrine tumors undergoing peptide receptor radionuclide therapy (PRRT) with a very high liver tumor burden, defined as tumor involving more than 75% of the liver. Methods: We conducted a retrospective analysis of 371 patients who received at least 1 cycle of 177Lu-DOTATATE at Mayo Clinic for advanced gastroenteropancreatic neuroendocrine tumors. We identified 15 total patients with more than 75% liver involvement on 68Ga-DOTATATE PET/CT and with either a contrast-enhanced abdominal MRI or dual-phase abdominal CT examination. Results: Of the 15 patients with more than 75% liver involvement, 1 experienced hepatotoxicity (i.e., worsening liver enzymes or bilirubin) as defined by the Common Terminology Criteria for Adverse Events, version 5.0. No patients had grade 3-5 hepatotoxicity (i.e., clinical signs of liver failure). Conclusion: When considering the risk of liver injury from PRRT due to burden of disease, our data suggest that PRRT may be a safe option in patients with more than 75% liver involvement. Future efforts should be made to determine the safety profile of PRRT in patients with varying degrees of liver involvement.

External validation of a machine learning based algorithm to differentiate hepatic mucinous cystic neoplasms from benign hepatic cysts.

To externally validate an algorithm for non-invasive differentiation of hepatic mucinous cystic neoplasms (MCN) from benign hepatic cysts (BHC), which differ in management. Patients with cystic liver lesions pathologically confirmed as MCN or BHC between January 2005 and March 2022 from multiple institutions were retrospectively included. Five readers (2 radiologists, 3 non-radiologist physicians) independently reviewed contrast-enhanced CT or MRI examinations before tissue sampling and applied the 3-feature classification algorithm described by Hardie et al. to differentiate between MCN and BHC, which had a reported accuracy of 93.5%. The classification was then compared to the pathology results. Interreader agreement between readers across different levels of experience was evaluated with Fleiss' Kappa. The final cohort included 159 patients, median age of 62years (IQR [52.0, 70.0]), 66.7% female (106). Of all patients, 89.3% (142) had BHC, and the remaining 10.7% (17) had MCN on pathology. Agreement for class designation between the radiologists was almost perfect (Fleiss' Kappa 0.840, p < 0.001). The algorithm had an accuracy of 98.1% (95% CI [94.6%, 99.6%]), a positive predictive value of 100.0% (95% CI [76.8%, 100.0%]), a negative predictive value of 97.9% (95% CI [94.1%, 99.6%]), and an area under the receiver operator characteristic curve (AUC) of 0.911 (95% CI [0.818, 1.000]). The evaluated algorithm showed similarly high diagnostic accuracy in our external, multi-institutional validation cohort. This 3-feature algorithm is easily and rapidly applied and its features are reproducible among radiologists, showing promise as a clinical decision support tool.

The effects of radiotherapy on arterial diameters in patients with high-grade glial tumors who have undergone adjuvant radiotherapy.

Our purpose was to evaluate the M2 branch of the middle cerebral artery (MCA) in high-grade glial tumor patients who undergo adjuvant radiotherapy (RT). For this purpose, the diameter of the M2 branch was measured and evaluated by means of contrast-enhanced magnetic resonance imaging (CE-MRI) before and after RT. Post-radiotherapeutical measurements were made 1, 3, 5, and 7 months after the procedure; and vascular diameter alterations were evaluated. CE-MRI examinations were performed on the 32 patients enrolled in the study, who had undergone radiotherapy of the temporoparietal region. MRI examinations were performed prior to RT (RT0) and 1 (RT1), 3 (RT2), 5 (RT3), and 7 (RT4) months after RT. The M2 branch of the MCA was evaluated on MRI images, and the vessel diameter was measured in millimeters (mm), and then comparisons were made. Statistically significant results were obtained during RT0-RT1, RT0-RT2, RT0-RT3, RT0-RT4, RT1-RT2, RT2-RT4, and RT3-RT4, and comparisons of the diameters of the M2 branch of the right MCA were performed (P < 0.05). When the same measurements and comparisons were made for the M2 branch of the left MCA, statistically significant results were found for the RT1-RT2, RT1-RT3, and RT1-RT4 comparisons (P < 0.05). Our study showed that the MCA M2 branch diminished in size following RT. This was demonstrated by means of CE-MRI controls performed up to 7 months after the completion of the RT procedures.

Outcomes of Bosniak Classification Version 2019 Class IIF Cystic Renal Masses at Imaging Surveillance.

BACKGROUND. Bosniak classification system version 2019 (v2019) recommends that class IIF masses undergo follow-up imaging at 6 months, 12 months, and then annually for 5 years. The frequency and timing of upgrade on follow-up imaging are incompletely understood. OBJECTIVE. The purpose of this article is to describe the temporal evolution of Bosniak v2019 class IIF cystic renal masses, with attention to outcomes at 6-month follow-up, the time to class upgrade, and malignant histologic diagnoses. METHODS. This retrospective study included 219 patients (91 women, 128 men; median age, 72 years) with 246 localized class IIF masses from January 2005 to June 2022. Patients underwent both a baseline and at least one follow-up renal-mass protocol contrast-enhanced CT or MRI examination. Two radiologists evaluated masses at all follow-up time points to categorize masses as downgraded (class I or II), stable (localized class IIF), or upgraded (class III or IV, solid, or category T3a, N1, or M1 or higher disease); a third radiologist resolved discrepancies. Incidence rate of upgrade was determined. Histopathologic outcomes were assessed for resected masses. RESULTS. Median follow-up was 28.4 months (IQR, 13.7-59.4 months). At 6-month follow-up, five (2%) masses were downgraded, 241 (98%) were stable, and none were upgraded. On the basis of final follow-up, 14 (6%) masses were downgraded, 223 (91%) were stable, and nine (4%) were upgraded. All upgrade events entailed a class increase to III (n = 7) or IV (n = 2); no mass became solid or developed T3, N1, or M1 disease. Among the nine upgraded masses, median time to upgrade was 53.5 months (IQR, 23.2-63.7 months). Incidence rate of upgrade was 3.006 per 100,000 person-days (95% CI, 1.466-5.516). Ten masses were resected; histopathology was benign in six and malignant in four. Of the four malignant masses, one was upgraded to class III after 15 months of preoperative follow-up imaging, and three remained class IIF on preoperative follow-up imaging. No resected malignant mass developed postoperative recurrence. CONCLUSION. Bosniak v2019 class IIF masses are unlikely to represent aggressive malignancy; only 4% were upgraded over time and never on initial 6-month follow-up. CLINICAL IMPACT. The currently recommended initial 6-month follow-up imaging examination for class IIF masses is of questionable clinical utility.

Combining 99mTc-GSA single-photon emission-computed tomography and Gd-EOB-DTPA-enhanced magnetic resonance imaging for staging liver fibrosis.

Preoperative assessment of the degree of liver fibrosis is important to determine treatment strategies. In this study, galactosyl human serum albumin single-photon emission-computed tomography and ethoxybenzyl (EOB) contrast-enhanced magnetic resonance imaging (MRI) were used to assess the changes in hepatocyte function after liver fibrosis, and the standardized uptake value (SUV) was combined with gadolinium EOB-diethylenetriaminepentaacetic acid to evaluate its added value for liver fibrosis staging. A total of 484 patients diagnosed with hepatocellular carcinoma who underwent liver resection between January 2010 and August 2018 were included. Resected liver specimens were classified based on pathological findings into nonfibrotic and fibrotic groups (stratified according to the Ludwig scale). Galactosyl human serum albumin-single-photon emission-computed tomography and EOB contrast-enhanced MRI examinations were performed, and the mean SUVs (SUVmean) and contrast enhancement indices (CEIs) were obtained. The diagnostic value of the acquired SUV and CEIs for fibrosis was assessed by calculating the area under the receiver operating characteristic curve (AUC). In the receiver operating characteristic analysis, SUV + CEI showed the highest AUC in both fibrosis groups. In particular, in the comparison between fibrosis groups, SUV + CEI showed significantly higher AUCs than SUV and CEI alone in discriminating between fibrosis (F3 and 4) and no or mild fibrosis (F0 and 2) (AUC: 0.879, vs SUV [P = 0.008], vs. CEI [P = 0.023]), suggesting that the combination of SUV + CEI has greater diagnostic performance than the individual indices. Combining the SUV and CEI provides high accuracy for grading liver fibrosis, especially in differentiating between grades F0 and 2 and F3-4. SUV and gadolinium EOB-diethylenetriaminepentaacetic acid-enhanced MRI can be noninvasive diagnostic methods to guide the selection of clinical treatment options for patients with liver diseases.

Deep Learning to Simulate Contrast-enhanced Breast MRI of Invasive Breast Cancer.

Background There is increasing interest in noncontrast breast MRI alternatives for tumor visualization to increase the accessibility of breast MRI. Purpose To evaluate the feasibility and accuracy of generating simulated contrast-enhanced T1-weighted breast MRI scans from precontrast MRI sequences in biopsy-proven invasive breast cancer with use of deep learning. Materials and Methods Women with invasive breast cancer and a contrast-enhanced breast MRI examination that was performed for initial evaluation of the extent of disease between January 2015 and December 2019 at a single academic institution were retrospectively identified. A three-dimensional, fully convolutional deep neural network simulated contrast-enhanced T1-weighted breast MRI scans from five precontrast sequences (T1-weighted non-fat-suppressed [FS], T1-weighted FS, T2-weighted FS, apparent diffusion coefficient, and diffusion-weighted imaging). For qualitative assessment, four breast radiologists (with 3-15 years of experience) blinded to whether the method of contrast was real or simulated assessed image quality (excellent, acceptable, good, poor, or unacceptable), presence of tumor enhancement, and maximum index mass size by using 22 pairs of real and simulated contrast-enhanced MRI scans. Quantitative comparison was performed using whole-breast similarity and error metrics and Dice coefficient analysis of enhancing tumor overlap. Results Ninety-six MRI examinations in 96 women (mean age, 52 years ± 12 [SD]) were evaluated. The readers assessed all simulated MRI scans as having the appearance of a real MRI scan with tumor enhancement. Index mass sizes on real and simulated MRI scans demonstrated good to excellent agreement (intraclass correlation coefficient, 0.73-0.86; P < .001) without significant differences (mean differences, -0.8 to 0.8 mm; P = .36-.80). Almost all simulated MRI scans (84 of 88 [95%]) were considered of diagnostic quality (ratings of excellent, acceptable, or good). Quantitative analysis demonstrated strong similarity (structural similarity index, 0.88 ± 0.05), low voxel-wise error (symmetric mean absolute percent error, 3.26%), and Dice coefficient of enhancing tumor overlap of 0.75 ± 0.25. Conclusion It is feasible to generate simulated contrast-enhanced breast MRI scans with use of deep learning. Simulated and real contrast-enhanced MRI scans demonstrated comparable tumor sizes, areas of tumor enhancement, and image quality without significant qualitative or quantitative differences. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Slanetz in this issue. An earlier incorrect version appeared online. This article was corrected on January 17, 2023.

Concordance of histopathological and radiological grading in soft tissue sarcomas

Aim: The grade of the tumor is essential for planning the treatment strategy in soft-tissue sarcomas (STS). The goal of this study is to determine magnetic resonance imaging features related to histopathological grade and aggressiveness of STS.&#x0D; Material and Method: This retrospective single-center study involved preoperative contrast-enhanced MRI examinations of 64 patients with STS. MRI findings evaluated were; heterogeneity, necrosis, hemorrhage, and relationship with surrounding tissue in T1-weighted (T1W), T2-weighted (T2W), and T1W post-contrast sequences of the lesion. Histological grade was determined with the Fédération Nationale des Centres de Lutte Contre Le Cancer (FNCLCC) grading system, and the aggressiveness of the lesion was measured with the Ki-67 index. &#x0D; Results: Sixty-four patients (mean age 45.5±21.6, M/F ratio 34/30) with STS were included. 33 (51.6%) patients graded as FNCLCC grade 3. On MRI examinations, the absence of necrosis was significantly associated with FNCLCC grade 1 and a low Ki-67 index (p

Differential diagnosis and management of hemangioma at geniculate ganglion

Objective: To investigate the clinical characteristics, differential diagnosis, treatments and prognosis of facial nerve hemangioma and schwannoma at genicular ganglion, so as to provide reference for clinical diagnosis and treatments of facial nerve tumor at genicular ganglion. Methods: Clinical data of 13 patients with facial nerve tumors at genicular ganglion confirmed by postoperative pathology in the Ninth People's Hospital affiliated to Shanghai Jiaotong University School of Medicine from March 2018 to April 2020 were retrospectively analyzed, including seven cases of hemangioma and six cases of schwannoma. There were eight males and five females. Their ages ranged from 20 to 65, with an average age of 40. The course of disease ranged from 3 to 118 months, with an average of 52 months. All the patients underwent preoperative HRCT of the temporal bone and facial nerve dynamic contrast-enhanced(DCE) MRI examinations. All the patients had detailed surgical procedures and at least one-year postoperative follow-up. Results: On HRCT of the temporal bone, (4/7) hemangioma at geniculate ganglion showed characteristic honeycomb appearance, while 6/6 schwannoma and 3/7 hemangiomas showed expansive bone changes. On DCE-MRI, geniculate ganglion hemangioma (7/7) showed characteristic "point-to-surface" enhancement, and schwannoma (6/6) showed characteristic "face-to-surface" enhancement. For five hemangioma-patients with HB-Ⅱ-Ⅳ before surgery, the facial nerve anatomy was completely preserved through transcanal endoscopic approach(TEA), and the facial nerve function improved one year after surgery (two cases of HB-I, two cases of HB-Ⅱ, and one case of HB-Ⅲ). For two patients, with preoperative facial nerve function HB-Ⅴ-Ⅵ, since their tumors was inseparable from the nerves, they were performed with facial nerve anastomosis during the surgery, and the facial nerve function was improved to HB-Ⅳ level one year after surgery. For six patients with meningioma whose facial nerve function was greater than or equal to HB-Ⅲ, based on the preoperative hearing level, the involved segments, and duration of facial paralysis, three of them were conducted surgeries through middle cranial fossa approach, one by translabyrinthine approach, and one via mastoid approach. Two patients among them with complete facial paralysis over three years preoperatively were not performed facial nerve anastomosis after total resections of the tumors, and there was no improvement in facial nerve function one year after surgery. Three patients underwent facial nerve anastomosis after total tumor resections, and their facial nerve function was HB-Ⅲ in one patient, HB-Ⅳ in two patients one year after surgery. One patient (preoperative HB-Ⅲ) had a normal hearing level preoperatively, and the tumor involved the labyrinth segment. To protect the hearing, partial tumor was resected through the middle cranial fossa approach, and facial nerve function improved to HB-Ⅱ one year after surgery. Conclusions: Temporal bone HRCT combined with DCE-MRI are useful for the differential diagnosis of hemangioma and schwannoma at geniculate ganglion and provide references for preoperative clinical decision makings. It is extremely necessary to select the appropriate surgical approach based on the patient's hearing and involved segments. For geniculate ganglion hemangioma, early surgery can improve the possibilities of anatomical integrity of facial nerve, thereby improving facial nerve function postoperatively.TEA is a kind of surgical method worth consideration, with the characteristics of minimally invasive, favorable postoperative features, and so on. For schwannoma, one-stage functional reconstruction of the facial nerve is recommended during the resection of the tumors because of the inevitable damage to the anatomical integrity of the facial nerve.

Contrast-enhanced Mammography versus Contrast-enhanced Breast MRI: A Systematic Review and Meta-Analysis.

Background Contrast-enhanced mammography (CEM) is a more accessible alternative to contrast-enhanced MRI (CE-MRI) in breast imaging, but a summary comparison of published studies is lacking. Purpose To directly compare the performance of CEM and CE-MRI regarding sensitivity, specificity, and negative predictive value in detecting breast cancer, involving all publicly available studies in the English language. Materials and Methods Two readers extracted characteristics of studies investigating the comparative diagnostic performance of CEM and CE-MRI in detecting breast cancer. Studies published until April 2021 were eligible. Sensitivity, specificity, negative predictive value, and positive and negative likelihood ratios were calculated using bivariate random effects models. A Fagan nomogram was used to identify the maximum pretest probability at which posttest probabilities of a negative CEM or CE-MRI examination were in line with the 2% malignancy rate benchmark for downgrading a Breast Imaging Reporting and Data System (BI-RADS) category 4 to a BI-RADS category 3 result. I 2 statistics, Deeks funnel plot asymmetry test for publication bias, and meta-regression were used. Results Seven studies investigating 1137 lesions (654 malignant, 483 benign) with an average cancer prevalence of 65.3% (range: 47.3%-82.2%) were included. No publication bias was found (P = .57). While the positive likelihood ratio was equal at a value of 3.1 for CE-MRI and 3.6 for CEM, the negative likelihood ratio of CE-MRI (0.04) was lower than that with CEM (0.12). CE-MRI had higher sensitivity for breast cancer than CEM (97% [95% CI: 86, 99] vs 91% [95% CI: 77, 97], respectively; P < .001) but lower specificity (69% [95% CI: 46, 85] vs 74% [95% CI: 52, 89]; P = .09). A Fagan nomogram demonstrated that the maximum pretest probability at which both tests could rule out breast cancer was 33% for CE-MRI and 14% for CEM. Furthermore, iodine concentration was positively associated with CEM sensitivity and negatively associated with its specificity (P = .04 and P < .001, respectively). Conclusion Contrast-enhanced MRI had superior sensitivity and negative likelihood ratios with higher pretest probabilities to rule out malignancy compared with contrast-enhanced mammography. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Mann and Veldhuis in this issue.

Image Quality of High-Resolution 3-Dimensional Neck MRI Using CAIPIRINHA-VIBE and GRASP-VIBE: An Intraindividual Comparative Study.

Acquiring high-quality magnetic resonance imaging (MRI) of the head and neck region is often challenging due to motion and susceptibility artifacts. This study aimed to compare image quality of 2 high-resolution three-dimensional (3D) MRI sequences of the neck, controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE), and golden-angle radial sparse parallel imaging (GRASP)-VIBE. One hundred seventy-three patients indicated for contrast-enhanced neck MRI examination were scanned using 3 T scanners and both CAIPIRINHA-VIBE and GRASP-VIBE with nearly isotropic 3D acquisitions (&lt;1 mm in-plane resolution with analogous acquisition times). Patients' MRI scans were independently rated by 2 radiologists using a 5-grade Likert scale for overall image quality, artifact level, mucosal and lesion conspicuity, and fat suppression degree at separate anatomical regions. Interobserver agreement was calculated using the Cohen κ coefficient. The quality ratings of both sequences were compared using the Mann-Whitney U test. Nonuniformity and contrast-to-noise ratio values were measured in all subjects. Separate MRI scans were performed twice for each sequence in a phantom and healthy volunteer without contrast injection to calculate the signal-to-noise ratio (SNR). The scores of overall image quality, overall artifact level, motion artifact level, and conspicuity of the nasopharynx, oropharynx, oral cavity, hypopharynx, and larynx were all significantly higher in GRASP-VIBE than in CAIPIRINHA-VIBE (all P 's &lt; 0.001). Moderate to substantial interobserver agreement was observed in overall image quality (GRASP-VIBE κ = 0.43; CAIPIRINHA-VIBE κ = 0.59) and motion artifact level (GRASP-VIBE κ = 0.51; CAIPIRINHA-VIBE κ = 0.65). Lesion conspicuity was significantly higher in GRASP-VIBE than in CAIPIRINHA-VIBE ( P = 0.005). The degree of fat suppression was weaker in the lower neck regions in GRASP-VIBE (3.90 ± 0.72) than in CAIPIRINHA-VIBE (4.97 ± 0.21) ( P &lt; 0.001). The contrast-to-noise ratio at hypopharyngeal level was significantly higher in GRASP-VIBE (6.28 ± 4.77) than in CAIPIRINHA-VIBE (3.14 ± 9.95) ( P &lt; 0.001). In the phantom study, the SNR of GRASP-VIBE was 12 times greater than that of CAIPIRINHA-VIBE. The in vivo SNR of the volunteer MRI scan was 13.6 in CAIPIRINHA-VIBE and 20.7 in GRASP-VIBE. Both sequences rendered excellent images for head and neck MRI scans. GRASP-VIBE provided better image quality, as well as mucosal and lesion conspicuities, with less motion artifacts, whereas CAIPIRINHA-VIBE provided better fat suppression in the lower neck regions.

Artificial Intelligence Algorithm in Classification and Recognition of Primary Hepatic Carcinoma Images under Magnetic Resonance Imaging.

This study aimed to discuss the application value of the bias field correction algorithm in magnetic resonance imaging (MRI) images of patients with primary hepatic carcinoma (PHC). In total, 52 patients with PHC were selected as the experimental group and divided into three subgroups: mild (15 cases), moderate (19 cases), and severe (18 cases) according to pathological grading. Another 52 patients with hepatic nodules in the same period were included in the control group. All the patients underwent dynamic contrast-enhanced (DCE) MRI examination, and the image qualities of MRI before and after bias field correction were compared. The DCE-MRI perfusion parameters were measured, including the transport constant Ktrans, reverse rate constant Kep, extravascular extracellular volume fraction (Ve), plasma volume (Vp), microvascular density (MVD), hepatic artery perfusion index (HPI), mean transit time of contrast agent (MTT), time to peak (TTP), blood volume (BV), hepatic arterial perfusion (HAP), full perfusion (FP), and portal venous perfusion (PVP). It was found that the sensitivity (93.63%), specificity (71.62%), positive predictive value (95.63%), negative predictive value (71.62%), and accuracy (90.01%) of MRI examination processed by the bias field correction algorithm were all significantly greater than those before processing (P < 0.05). The Ktrans, Kep, Ve, Vp, and MVD of patients in the experimental group were significantly larger than those of the control group, and severe group> moderate group> mild group (P < 0.05). HPI, MTT, TTP, BV, and HAP of patients in the experimental group were also significantly greater than those of the control group, which was shown as severe group > moderate group > mild group (P < 0.05). FP and PVP of the experimental group were significantly lower than those of the control group, and severe group < moderate group < mild group (P < 0.05). It was suggested that in MRI images of patients with PHC, the bias field correction algorithm could significantly improve the diagnosis rate. Each perfusion parameter was related to the pathological grading, which could be used to evaluate the prognosis of patients.

Magnetic resonance imaging evaluation of incidentally detected hyperechoic liver lesions: comparison of two modalities in terms of detection, diagnosis, and morphological features.

This study aimed to investigate and compare the ultrasonography and contrast-enhanced magnetic resonance imaging characteristics of incidentally detected hyperechoic focal liver lesions. Seventy-four patients (29 males and 45 females) who had undergone a B-mode ultrasonography and contrast-enhanced magnetic resonance imaging examination were included in this study. A total of 91 hyperechoic lesions detected on ultrasonography were evaluated. The ultrasonography features of these hyperechoic lesions were recorded, and the results were compared with those acquired from contrast-enhanced magnetic resonance imaging. The results were compared statistically using the Shapiro-Wilk, McNemar, and Wilcoxon signed-rank tests. A corresponding lesion was found on contrast-enhanced magnetic resonance imaging in 72 of the 91 (79.1%) hyperechoic lesions detected on ultrasonography. Forty-one (56.9%) of the magnetic resonance imaging-defined lesions were typical hemangiomas, while 10 (13.9%) were focal steatosis areas and 4 (5.6%) were diagnosed with hepatocellular carcinoma. In contrast, 6 lesions (8.3%) were diagnosed as simple hepatic cysts, 4 (5.6%) as sclerosing hemangioma, 2 (2.8%) as thrombosed hemangioma, 1 (1.4%) as focal nodular hyperplasia, 1 (1.4%) as hamartoma, 2 (2.8%) as hydatid cysts, and 1 (1.4%) as hepatic lipoma. No statistically significant differences were found between ultrasonography and magnetic resonance imaging in terms of the segmental classification of the true positive lesions based on contour structures and lesion area measurements (p=0.558, p=0.375, and p=0.636, respectively). Incidentally detected hyperechoic zones may not necessarily be detected on magnetic resonance imaging. This may be secondary to focal hepatic steatosis or false interpretation of the radiologist. Lesions requiring therapy must be considered in the differential diagnosis.