Morphologic Magnetic Resonance Imaging Features Research Articles

Texture analysis using machine learning-based 3-T magnetic resonance imaging for predicting recurrence in breast cancer patients treated with neoadjuvant chemotherapy.

To determine whether texture analysis for magnetic resonance imaging (MRI) can predict recurrence in patients with breast cancer treated with neoadjuvant chemotherapy (NAC). This retrospective study included 130 women who received NAC and underwent subsequent surgery for breast cancer between January 2012 and August 2017. We assessed common features, including standard morphologic MRI features and clinicopathologic features. We used a commercial software and analyzed texture features from pretreatment and midtreatment MRI. A random forest (RF) method was performed to build a model for predicting recurrence. The diagnostic performance of this model for predicting recurrence was assessed and compared with those of five other machine learning classifiers using the Wald test. Of the 130 women, 21 (16.2%) developed recurrence at a median follow-up of 35.4 months. The RF classifier with common features including clinicopathologic and morphologic MRI features showed the lowest diagnostic performance (area under the receiver operating characteristic curve [AUC], 0.83). The texture analysis with the RF method showed the highest diagnostic performances for pretreatment T2-weighted images and midtreatment DWI and ADC maps showed better diagnostic performance than that of an analysis of common features (AUC, 0.94 vs. 0.83, p < 0.05). The RF model based on all sequences showed a better diagnostic performance for predicting recurrence than did the five other machine learning classifiers. Texture analysis using an RF model for pretreatment and midtreatment MRI may provide valuable prognostic information for predicting recurrence in patients with breast cancer treated with NAC and surgery. • RF model-based texture analysis showed a superior diagnostic performance than traditional MRI and clinicopathologic features (AUC, 0.94 vs.0.83, p < 0.05) for predicting recurrence in breast cancer after NAC. • Texture analysis using RF classifier showed the highest diagnostic performances (AUC, 0.94) for pretreatment T2-weighted images and midtreatment DWI and ADC maps. • RF model showed a better diagnostic performance for predicting recurrence than did the five other machine learning classifiers.

The role of magnetic resonance imaging on evaluating response of neoadjuvant therapy for breast cancer

Breast magnetic resonance imaging (MRI) is always considered to be more accurate for evaluating neoadjuvant therapy (NAT) response than mammography, ultrasound and clinical examination. Preoperative MRI aims to evaluate residual disease to facilitate surgical planning. MRI scans performed before and/or during NAT aim to predict the treatment response and thus adjust the NAT plan at an early stage. MRI accuracy depends on tumor morphology, histology, shrinkage pattern and molecular subtype. Combining multiparameter functional MRI can improve the prediction accuracy. In addition, radiomics offers high-dimensional and high-throughput signatures and were shown to predict treatment response before NAT. This article reviews the indicators of breast MRI for evaluating NAT response, including morphological MRI features, enhancement and pharmacokinetic parameters, apparent diffusion coefficient (ADC), choline concentration, etc., even radiomic signatures and illustrates their advantages, limitations and future directions.

MRI Features of the Vomeronasal Organ in Dogs (Canis Familiaris).

According to current knowledge, the vomeronasal organ (VNO, Jacobson's organ) is the structure responsible for semiochemical signal detection. In dogs and other mammals, it is located close to the vomer and palatine processes of the incisive and maxillary bones. Although there are reports describing the anatomy and histology of this structure, there are limited available reports assessing this organ in live individuals and no direct visualization reports in dogs. The aim of this study was 2-fold: (1) preparation and optimization of a protocol for magnetic resonance imaging (MRI) examination of the VNO in a cadaver study with precise visualization and localization, and (2) characterization of the physiological VNO image features in MRI of live dogs. The first part of the study was performed on 10 beagle cadavers, the second on 8 live beagle dogs. For the VNO visualization, a 1.5T MRI (Philips® Ingenia) scanner and 20-channel digital head-neck spine coil were used (Philips®, Holland). The cadaver study allowed confirmation of the organ's location by the topical application of an MRI contrast agent (gadolinium) via the external entrance of the VNO canal. Accurate delineation of the VNO was obtained using a high resolution submillimeter three-dimensional T1-fast field echo (FFE) 3D sequence. Imaging of the VNO in 8 living dogs allowed the description of the morphological MRI features and direct evaluation of its shape and size. The results obtained demonstrate the ability to visualize the VNO in vivo and to evaluate its structure in dogs.

Differentiation of peripheral nerve sheath tumors in patients with neurofibromatosis type 1 using diffusion-weighted magnetic resonance imaging.

We sought to determine the value of diffusion-weighted (DW) magnetic resonance imaging (MRI) for characterization of benign and malignant peripheral nerve sheath tumors (PNSTs) in patients with neurofibromatosis type 1 (NF1). Twenty-six patients with NF1 and suspicion of malignant transformation of PNSTs were prospectively enrolled and underwent DW MRI at 3T. For a set of benign (n = 55) and malignant (n = 12) PNSTs, functional MRI parameters were derived from both biexponential intravoxel incoherent motion (diffusion coefficient D and perfusion fraction f) and monoexponential data analysis (apparent diffusion coefficients [ADCs]). A panel of morphological MRI features was evaluated using T1- and T2-weighted imaging. Mann-Whitney U-test, Fisher's exact test, and receiver operating characteristic (ROC) analyses were applied to assess the diagnostic accuracy of quantitative and qualitative MRI. Cohen's kappa was used to determine interrater reliability. Malignant PNSTs demonstrated significantly lower diffusivity (P < 0.0001) compared with benign PNSTs. The perfusion fraction f was significantly higher in malignant PNSTs (P < 0.001). In ROC analysis, functional MRI parameters showed high diagnostic accuracy for differentiation of PNSTs (eg, ADCmean, 92% sensitivity with 98% specificity, AUC 0.98; Dmean, 92% sensitivity with 98% specificity, AUC 0.98). By contrast, morphological imaging features had only limited sensitivity (18-94%) and specificity (18-82%) for identification of malignancy. Interrater reliability was higher for monoexponential data analysis. DW imaging shows better diagnostic performance than morphological features and allows accurate differentiation of benign and malignant peripheral nerve sheath tumors in NF1.

Magnetic Resonance Imaging-Based Grading of Cartilaginous Bone Tumors: Added Value of Quantitative Texture Analysis.

The aim of this study was to assess the interreader agreement and diagnostic accuracy of morphologic magnetic resonance imaging (MRI) analysis and quantitative MRI-based texture analysis (TA) for grading of cartilaginous bone tumors. This retrospective study was approved by our local ethics committee. Magnetic resonance imaging scans of 116 cartilaginous bone neoplasms were included (53 chondromas, 26 low-grade chondrosarcomas, 37 high-grade chondrosarcomas). Two musculoskeletal radiologists blinded to patient data separately analyzed 14 morphologic MRI features consisting of tumor and peritumoral characteristics. In addition, 2 different musculoskeletal radiologists separately performed TA including 19 quantitative TA parameters in a similar fashion. Interreader reliability, univariate, multivariate, and receiver operating characteristics analyses were performed for MRI and TA parameters separately and for combined models to determine independent predictors and diagnostic accuracy for grading of cartilaginous neoplasms. P values of 0.05 and less were considered statistically significant. Between both readers, MRI and TA features showed a mean kappa value of 0.49 (range, 0.08-0.82) and a mean intraclass correlation coefficient of 0.79 (range, 0.43-0.99), respectively. Independent morphological MRI predictors for grading of cartilaginous neoplasms were bone marrow edema, soft tissue mass, maximum tumor extent, and active periostitis, whereas TA predictors consisted of short-run high gray-level emphasis, skewness, and gray-level and run-length nonuniformity. Diagnostic accuracies for differentiation of benign from malignant as well as for benign from low-grade cartilaginous lesions were 87.0% and 77.4% using MRI predictors exclusively, 89.8% and 89.5% using TA predictors exclusively, and 92.9% and 91.2% using a combined model of MRI and TA predictors, respectively. For differentiation of low-grade from high-grade chondrosarcoma, no statistically significant independent TA predictors existed, whereas a model containing MRI predictors exclusively had a diagnostic accuracy of 84.8%. Texture analysis improves diagnostic accuracy for differentiation of benign and malignant as well as for benign and low-grade cartilaginous lesions when compared with morphologic MRI analysis.

Magnetic Resonance Imaging Evaluation in Neoadjuvant Therapy of Locally Advanced Rectal Cancer: A Systematic Review.

BackgroundThe aim of the study was to present an update concerning several imaging modalities in diagnosis, staging and pre-surgery treatment response assessment in locally advanced rectal cancer (LARC). Modalities include: traditional morphological magnetic resonance imaging (MRI), functional MRI such as dynamic contrast enhanced MRI (DCE-MRI) and diffusion weighted imaging (DWI). A systematic review about the diagnostic accuracy in neoadjuvant therapy response assessment of MRI, DCE-MRI, DWI and Positron Emission Tomography/Computed Tomography (PET/CT) has been also reported.MethodsSeveral electronic databases were searched including PubMed, Scopus, Web of Science, and Google Scholar. All the studies included in this review reported findings about therapy response assessment in LARC by means of MRI, DCE-MRI, DWI and PET/CT with details about diagnostic accuracy, true and false negatives, true and false positives. Forest plot and receiver operating characteristic (ROC) curves analysis were performed. Risk of bias and the applicability at study level were calculated.ResultsTwenty-five papers were identified. ROC curves analysis demonstrated that multimodal imaging integrating morphological and functional MRI features had the best accuracy both in term of sensitivity and specificity to evaluate preoperative therapy response in LARC. DCE-MRI following to PET/CT showed high diagnostic accuracy and their results are also more reliable than conventional MRI and DWI alone.ConclusionsMorphological MRI is the modality of choice for rectal cancer staging permitting a correct assessment of the disease extent, of the lymph node involvement, of the mesorectal fascia and of the sphincter complex for surgical planning. Multimodal imaging and functional DCE-MRI may also help in the assessment of treatment response allowing to guide the surgeon versus conservative strategies and/or tailored approach such as “wait and see” policy.

Conventional MRI features for predicting the clinical outcome of patients with invasive placenta.

We aimed to evaluate whether morphologic magnetic resonance imaging (MRI) features could help to predict the maternal outcome after uterine artery embolization (UAE)-assisted cesarean section (CS) in patients with invasive placenta previa. We retrospectively reviewed the MRI data of 40 pregnant women who have undergone UAE-assisted cesarean section due to suspected high risk of massive hemorrhage caused by invasive placenta previa. Patients were divided into two groups based on the maternal outcome (good-outcome group: minor hemorrhage and uterus preserved; poor-outcome group: significant hemorrhage or emergency hysterectomy). Morphologic MRI features were compared between the two groups. Multivariate logistic regression analysis was used to identify the most valuable variables, and predictive value of the identified risk factor was determined. Low signal intensity bands on T2-weighted imaging (P < 0.001), placenta percreta (P = 0.011), and placental cervical protrusion sign (P = 0.002) were more frequently observed in patients with poor outcome. Low signal intensity bands on T2-weighted imaging was the only significant predictor of poor maternal outcome in multivariate analysis (P = 0.020; odds ratio, 14.79), with 81.3% sensitivity and 84.3% specificity. Low signal intensity bands on T2-weighted imaging might be a predictor of poor maternal outcome after UAE-assisted cesarean section in patients with invasive placenta previa.

Morphologic MRI features, diffusion tensor imaging and radiation dosimetric analysis to differentiate pseudo-progression from early tumor progression

Pseudo-progression (PsP) refers to the paradoxical increase of contrast enhancement within 12 weeks of chemo-radiation therapy in gliomas attributable to treatment effects rather than early tumor progression (ETP). This study was performed to evaluate the utility of morphologic imaging features, diffusion tensor imaging (DTI) and radiation dosimetric analysis of magnetic resonance imaging (MRI) changes in differentiating PsP from ETP. Serial MRI examinations of 163 patients treated for high-grade glioma were reviewed. 46 patients showed a recurrent or progressive enhancing lesion within 12 weeks of radiotherapy. We used an in-house modified scoring system based on 20 different morphologic features (modified VASARI features) to assess the MRI studies. DTI analyses were performed in 24 patients. MRI changes were defined as recurrent volume (Vrec) and registered with pretreatment computed tomography dataset, and the actual dose received by the Vrec during treatment was calculated using dose-volume histograms. Bidimensional product of T2-FLAIR signal abnormality and enhancing component was larger in the ETP group. DTI metrics revealed no significant difference between the two groups. There was no statistically significant difference in the location of Vrec between PsP and ETP groups. Morphologic MRI features and DTI have a limited role in differentiating between PsP and ETP. The larger sizes of the T2-FLAIR signal abnormality and the enhancing component of the lesion favor ETP. There was no correlation between the pattern of MRI changes and radiation dose distribution between PsP and ETP groups.

Is MRI a useful tool to distinguish between serous and mucinous borderline ovarian tumours?

To analyse the morphological magnetic resonance imaging (MRI) features of borderline ovarian tumours (BOT) and to evaluate whether MRI can be used to distinguish serous from mucinous subtypes. A retrospective study of 72 patients who underwent BOT resection was undertaken. MRI images were reviewed blindly by two radiologists to assess MRI features: size, tumour type, grouped and irregular thickened septa, number of septa, loculi of different signal intensity, vegetations, solid portion, signal intensity of vegetations, normal ovarian parenchyma, and pelvic ascites. Statistical analysis was performed using Mann-Whitney and Fisher's exact tests. Logistic regression analysis was used to assess the predictive value of the MRI findings for histological subtypes. At histology, there were 33 serous BOT (SBOT) and 39 mucinous BOT (MBOT). Predictive MRI criteria for SBOT were bilaterality, predominantly solid tumour, and the presence of vegetations, especially exophytic or with a high T2 signal (p<0.01), whereas predictive MRI criteria for MBOT were multilocularity, number of septa, loculi of different signal intensity, and grouped and irregular thickened septa (p<0.01). Using multivariate analysis, vegetations were independently associated with SBOT [odds ratio (OR)=29.5] and multilocularity with MBOT (OR=3.9). Vegetations and multilocularity are two independent MRI features that can help to distinguish between SBOT and MBOT.

Morphologic magnetic resonance imaging features of therapy-induced cerebral necrosis

To describe the morphologic magnetic resonance imaging (MRI) findings in histologically proven therapy-induced cerebral necrosis. We retrospectively reviewed the morphologic MRI findings in patients with therapy-induced cerebral necrosis. Images were reviewed for size, location, and characteristics of signal intensity abnormalities and T1-contrast enhancement. Images were also assessed for mass effect, necrosis, cyst, atrophy, cortical thinning, and leukoencephalopathy. The individual imaging characteristics were correlated with clinical and treatment variables. There were 44 patients. Seventy percent had a glioma, all patients had received radiation, and 57% had received chemotherapy in close proximity to radiation. All images demonstrated contrast enhancement, predominantly in the white matter. Enhancement was present in the periventricular/subependymal region in 50% of cases and the corpus callosum in 27%. The most common pattern of lesion peripheral enhancement was "spreading wavefront" and of interior enhancement was "Swiss cheese/soap bubble." The enhancing lesion was single in 60% of cases. Mass effect was present in 93% of patients. Location and patterns of enhancement were significantly associated with the interval from brain radiation to the diagnosis of therapy-induced cerebral necrosis, tumor histology, patient age, type of radiation, and administration of systemic chemotherapy. This is the largest study of the morphologic conventional MRI findings in pathologically confirmed therapy-induced cerebral necrosis. We characterized the imaging findings in a variety of tumor types following a variety of radiation treatments and other antineoplastic therapy. These findings may be of value in identifying therapy-induced cerebral necrosis in patients treated for a brain tumor.

Imaging of malformations of cortical development

Malformations of cortical development (MCD) include a broad range of disorders that result from disruption of the major steps of cortical development: cell proliferation in germinal zones, neuronal migration and cortical organization. With the improvement and increased utilization of modern imaging techniques, MCD have been increasingly recognized as a major cause of seizure disorders. The advent of Magnetic Resonance Imaging (MRI), in particular, has revolutionized the investigation and the treatment of patients with epilepsy. High-resolution MRI may elucidate the type, the extension and the localization of MCD; therefore, in a group of patients suffering from drug-resistant partial epilepsy (DRPE), MRI greatly contributes to the identification of subjects who are suitable for surgical treatment. In the recent past, many efforts were addressed to establish the MRI diagnostic criteria for a peculiar group of MCD, namely focal cortical dysplasias (FCD), histopathologically distinguished as types I and II. Some subtle FCD, which were previously cryptic to imaging investigation, can now be recognized by MRI, however their detection and specification remains challenging. This review will re-visit the neuroimaging findings, including structural MRI, PET, co-registered PET/MRI, MEG and diffusion tensor imaging (DTI) of FCD types I and II. Three major issues will be discussed: 1) the morphological MRI features of the FCDs, 2) the utility of PET and MEG and the use of co-registration methods and 3) diffusion tensor imaging (DTI) as a future modality of investigation, which may add additional informations regarding the microstructure of the grey matter (GM) and white matter (WM) in cortical dysplasia.

MR Imaging of Arrhythmogenic Right Ventricular Cardiomyopathy: Morphologic Findings and Interobserver Reliability

Background: Magnetic resonance (MR) imaging is frequently used to diagnose arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D). However, the reliability of various MR imaging features for diagnosing ARVC/D is unknown. The purpose of this study was to determine which morphologic MR imaging features have the greatest interobserver reliability for diagnosing ARVC/D. Methods: Forty-five sets of films of cardiac MR images were sent to 8 radiologists and 5 cardiologists with experience in this field. There were 7 cases of definite ARVC/D as defined by the Task Force criteria. Six cases were controls. The remaining 32 cases had MR imaging because of clinical suspicion of ARVC/D. Readers evaluated the images for the presence of (a) right ventricle (RV) enlargement, (b) RV abnormal morphology, (c) left ventricle enlargement, (d) presence of high T₁ signal (fat) in the myocardium, and (e) location of high T₁ signal (fat) on a Likert scale with formatted responses. Results: Readers indicated that the Task Force ARVC/D cases had significantly more (χ² = 119.93, d.f. = 10, p < 0.0001) RV chamber size enlargement (58%) than either the suspected ARVC/D (12%) or no ARVC/D (14%) cases. When readers reported the RV chamber size as enlarged they were significantly more likely to report the case as ARVC/D present (χ²⁼33.98, d.f. = 1, p < 0.0001). When readers reported the morphology as abnormal they were more likely to diagnose the case as ARVC/D present (χ² = 78.4, d.f. = 1, p < 0.0001), and the Task Force ARVC/D (47%) cases received significantly more abnormal reports than either suspected ARVC/D (20%) or non-ARVC/D (15%) cases. There was no significant difference between patient groups in the reported presence of high signal intensity (fat) in the RV (χ² = 0.9, d.f. = 2, p > 0.05). Conclusions: Reviewers found that the size and shape of abnormalities in the RV are key MR imaging discriminates of ARVD. Subsequent protocol development and multicenter trials need to address these parameters. Essential steps in improving accuracy and reducing variability include a standardized acquisition protocol and standardized analysis with dynamic cine review of regional RV function and quantification of RV and left ventricle volumes.