Contrast-enhanced T1-weighted MRI Research Articles

Radiomics on multi-modalities MR sequences can subtype patients with non-metastatic nasopharyngeal carcinoma (NPC) into distinct survival subgroups.

To explore and evaluate the feasibility of radiomics in stratifying nasopharyngeal carcinoma (NPC) into distinct survival subgroups through multi-modalities MRI. A total of 658 patients (training cohort: 424; validation cohort: 234) with non-metastatic NPC were enrolled in the retrospective analysis. Each slice was considered as a sample and 4863 radiomics features on the tumor region were extracted from T1-weighted, T2-weighted, and contrast-enhanced T1-weighted MRI. Consensus clustering and manual aggregation were performed on the training cohort to generate a baseline model and classification reference used to train a support vector machine classifier. The risk of each patient was defined as the maximum risk among the slices. Each patient in the validation cohort was assigned to the risk model using the trained classifier. Harrell's concordance index (C-index) was used to measure the prognosis performance, and differences between subgroups were compared using the log-rank test. The training cohort was clustered into four groups with distinct survival patterns. Each patient was assigned to one of the four groups according to the estimated risk. Our method gave a performance (C-index = 0.827, p< .004 and C-index = 0.814, p< .002) better than the T-stage (C-index = 0.815, p= .002 and C-index = 0.803, p= .024), competitive to and more stable than the TNM staging system (C-index = 0.842, p= .003 and C-index = 0.765, p= .050) in the training cohort and the validation cohort. Through investigating a large one-institutional cohort, the quantitative multi-modalities MRI image phenotypes reveal distinct survival subtypes. • Radiomics phenotype of MRI revealed the subtype of nasopharyngeal carcinoma (NPC) patients with distinct survival patterns. • The slice-wise analysis method on MRI helps to stratify patients and provides superior prognostic performance over the TNM staging method. • Risk estimation using the highest risk among slices performed better than using the majority risk in prognosis.

Comparison of End-Expiration Versus End-Inspiration Breath-Holds With Respect to Respiratory Motion Artifacts on T1-Weighted Abdominal MRI.

OBJECTIVE. The purpose of this study was to compare respiratory motion artifact and diagnostic image quality between end-inspiration and end-expiration breath-holding techniques on unenhanced and contrast-enhanced axial T1-weighted MRI of the liver. MATERIALS AND METHODS. This retrospective observational study included 50 consecutive subjects undergoing axial T1-weighted liver MRI, with unenhanced images acquired with both end-inspiration and end-expiration breath-holding techniques, and with contrast-enhanced images acquired for 47 of the subjects with either the end-inspiration or the end-expiration breath-holding technique. Three radiologists performed blinded independent evaluations of each unenhanced sequence, contrast-enhanced sequence, and subtraction (contrast-enhanced minus unenhanced) image, using a scale ranging from 1 point (denoting nondiagnostic imaging) to 5 points (denoting no artifacts). Blinded side-by-side assessment of each pair of unenhanced sequences was also performed. Two-tailed Wilcoxon signed rank and Wilcoxon rank sum tests were used to assess statistical significance. RESULTS. A significant improvement in motion scores was noted for sequences acquired in end-expiration, compared with those acquired in end-inspiration, for unenhanced sequences (mean, 3.35 vs 2.80; p < 0.00001), contrast-enhanced sequences (mean, 4.02 vs 3.46; p = 0.0003), and subtraction images (mean, 3.67 vs 2.41; p < 0.00001). Severe degradation of image quality or nondiagnostic image quality was noted for 15% of unenhanced images (23/150), 0% of contrast-enhanced images, and 8% (5/63) of subtraction images acquired on end-expiration, whereas it was noted for 36% (54/150) of unenhanced images, 13% (10/78) of contrast-enhanced images, and 59% (46/78) of subtraction images acquired on end-inspiration. When side-by-side assessment of paired unenhanced sequences was performed, images acquired in end-expiration were significantly favored in 59% of paired sequences (88/150) (p < 0.00001), and no difference between images acquired with both breath-hold techniques was noted for 21% (32/150) of paired sequences. CONCLUSION. The end-expiration breath-holding technique leads to significant decreases in respiratory motion artifacts, compared with the end-inspiration technique, on unenhanced and contrast-enhanced T1-weighted liver MRI.

In-vivo treatment accuracy analysis of active motion-compensated liver SBRT through registration of plan dose to post-therapeutic MRI-morphologic alterations

Background/purposeIn-vivo-accuracy analysis (IVA) of dose-delivery with active motion-management (gating/tracking) was performed based on registration of post-radiotherapeutic MRI-morphologic-alterations (MMA) to the corresponding dose-distributions of gantry-based/robotic SBRT-plans. MethodsForty targets in two patient cohorts were evaluated: (1) gantry-based SBRT (deep-inspiratory breath-hold-gating; GS) and (2) robotic SBRT (online fiducial-tracking; RS). The planning-CT was deformably registered to the first post-treatment contrast-enhanced T1-weighted MRI. An isodose-structure cropped to the liver (ISL) and corresponding to the contoured MMA was created. Structure and statistical analysis regarding volumes, surface-distance, conformity metrics and center-of-mass-differences (CoMD) was performed. ResultsLiver volume-reduction was −43.1 ± 148.2 cc post-RS and −55.8 ± 174.3 cc post-GS. The mean surface-distance between MMA and ISL was 2.3 ± 0.8 mm (RS) and 2.8 ± 1.1 mm (GS). ISL and MMA volumes diverged by 5.1 ± 23.3 cc (RS) and 16.5 ± 34.1 cc (GS); the median conformity index of both structures was 0.83 (RS) and 0.80 (GS). The average relative directional errors were ≤0.7 mm (RS) and ≤0.3 mm (GS); the median absolute 3D-CoMD was 3.8 mm (RS) and 4.2 mm (GS) without statistically significant differences between the two techniques. Factors influencing the IVA included GTV and PTV (p = 0.041 and p = 0.020). Four local relapses occurred without correlation to IVA. ConclusionsFor the first time a method for IVA was presented, which can serve as a benchmarking-tool for other treatment techniques. Both techniques have shown median deviations <5 mm of planned dose and MMA. However, IVA also revealed treatments with errors ≥5 mm, suggesting a necessity for patient-specific safety-margins. Nevertheless, the treatment accuracy of well-performed active motion-compensated liver SBRT seems not to be a driving factor for local treatment failure.

Highly accelerated, model‐free diffusion tensor MRI reconstruction using neural networks

The purpose of this study was to develop a neural network that accurately performs diffusion tensor imaging (DTI) reconstruction from highly accelerated scans. This retrospective study was conducted using data acquired between 2013 and 2018 and was approved by the local institutional review board. DTI acquired in healthy volunteers (N=10) was used to train a neural network, DiffNet, to reconstruct fractional anisotropy (FA) and mean diffusivity (MD) maps from small subsets of acquired DTI data with between 3 and 20 diffusion-encoding directions. FA and MD maps were then reconstructed in volunteers and in patients with glioblastoma multiforme (GBM, N=12) using both DiffNet and conventional reconstructions. Accuracy and precision were quantified in volunteer scans and compared between reconstructions. The accuracy of tumor delineation was compared between reconstructed patient data by evaluating agreement between DTI-derived tumor volumes and volumes defined by contrast-enhanced T1-weighted MRI. Comparisons were performed using areas under the receiver operating characteristic curves (AUC). DiffNet FA reconstructions were more accurate and precise compared with conventional reconstructions for all acceleration factors. DiffNet permitted reconstruction with only three diffusion-encoding directions with significantly lower bias than the conventional method using six directions (0.01±0.01 vs 0.06±0.01, P<0.001). While MD-based tumor delineation was not substantially different with DiffNet (AUC range: 0.888-0.902), DiffNet FA had higher AUC than conventional reconstructions for fixed scan time and achieved similar performance with shorter scans (conventional, six directions: AUC=0.926, DiffNet, three directions: AUC=0.920). DiffNet improved DTI reconstruction accuracy, precision, and tumor delineation performance in GBM while permitting reconstruction from only three diffusion-encoding directions.&!#6.

3D T1-weighted contrast-enhanced brain MRI in children using a fat-suppressed golden angle radial acquisition: an alternative to Cartesian inversion-recovery imaging

BackgroundT1-weighted post-contrast MRI is essential in brain protocols. We demonstrate the feasibility and utility of a 3D non-Cartesian radial acquisition in children. PurposeTo compare bulk motion artifacts, image quality, and lesion conspicuity in 3D T1-weighted post-contrast brain MRI between a new fat-suppressed radial gradient-echo and a traditional non-fat-suppressed inversion-recovery Cartesian gradient-echo sequence. Material and methodsImages from 53 patients acquired at 3 Tesla were compared. Three radiologists rated the images in three categories, including the presence of bulk motion and whether it impacted diagnosis, whether one sequence was preferred over the other in overall image quality and conspicuity of vascular structures and lesions, and whether diagnosis was possible if only the new fat-suppressed radial acquisition was obtained. ResultsThe Fleiss' kappa for inter-rater agreement was 0.67 for bulk motion and 0.54 for sequence preference. Of the 53 cases, 56% were identified to have significant motion on conventional imaging, while only 13% had motion artifacts on the radial acquisition (p < 0.05). There were no cases where motion was seen on the radial acquisition but not on conventional imaging. Both sequences were equally preferred in 87% of the cases. All radiologists agreed that the radial approach had lower gray-white matter contrast than the conventional inversion-recovery method, but preferred the former for making diagnosis in uncooperative patients. ConclusionWe demonstrate the potential utility of a fat-suppressed 3D T1-weighted post-contrast brain gradient-echo sequence in children. The technique is useful in non-sedate pediatric imaging due to its reduced sensitivity to bulk motion.

An alternative approach to contrast-enhanced imaging: diffusion-weighted imaging and T1-weighted imaging identifies and quantifies necrosis in Wilms tumour

ObjectivesVolume of necrosis in Wilms tumour is informative of chemotherapy response. Contrast-enhanced T1-weighted MRI (T1w) provides a measure of necrosis using gadolinium. This study aimed to develop a non-invasive method of identifying non-enhancing (necrotic) tissue in Wilms tumour.MethodsIn this single centre, retrospective study, post-chemotherapy MRI data from 34 Wilms tumour patients were reviewed (March 2012–March 2017). Cases with multiple b value diffusion-weighted imaging (DWI) and T1w imaging pre- and post-gadolinium were included. Fractional T1 enhancement maps were generated from the gadolinium T1w data. Multiple linear regression determined whether fitted parameters from a mono-exponential model (ADC) and bi-exponential model (IVIM – intravoxel incoherent motion) (D, D*, f) could predict fractional T1 enhancement in Wilms tumours, using normalised pre-gadolinium T1w (T1wnorm) signal as an additional predictor. Measured and predicted fractional enhancement values were compared using the Bland-Altman plot. An optimum threshold for separating necrotic and viable tissue using fractional T1 enhancement was established using ROC.ResultsADC and D (diffusion coefficient) provided the strongest predictors of fractional T1 enhancement in tumour tissue (p < 0.001). Using the ADC-T1wnorm model (adjusted R2 = 0.4), little bias (mean difference = − 0.093, 95% confidence interval = [− 0.52, 0.34]) was shown between predicted and measured values of fractional enhancement and analysed via the Bland-Altman plot. The optimal threshold for differentiating viable and necrotic tissue was 33% fractional T1 enhancement (based on measured values, AUC = 0.93; sensitivity = 85%; specificity = 90%).ConclusionsCombining ADC and T1w imaging predicts enhancement in Wilms tumours and reliably identifies and measures necrotic tissue without gadolinium.Key Points• Alternative method to identify necrotic tissue in Wilms tumour without using contrast agents but rather using diffusion and T1weighted MRI.• A method is presented to visualise and quantify necrotic tissue in Wilms tumour without contrast.• The proposed method has the potential to reduce costs and burden to Wilms tumour patients who undergo longitudinal follow-up imaging as contrast agents are not used.

A Triple‐Classification Radiomics Model for the Differentiation of Primary Chordoma, Giant Cell Tumor, and Metastatic Tumor of Sacrum Based on T2‐Weighted and Contrast‐Enhanced T1‐Weighted MRI

Preoperative differentiation between primary sacral chordoma (SC), sacral giant cell tumor (SGCT), and sacral metastatic tumor (SMT) is important for treatment decisions. To develop and validate a triple-classification radiomics model for the preoperative differentiation of SC, SGCT, and SMT based on T2-weighted fat saturation (T2w FS) and contrast-enhanced T1-weighted (CE T1w) MRI. Retrospective. A total of 120 pathologically confirmed sacral patients (54 SCs, 30 SGCTs, and 36 SMTs) were retrospectively analyzed and divided into a training set (n = 83) and a validation set (n = 37). The 3.0T axial T2w FS and CE T1w MRI. Morphology, intensity, and texture features were assessed based on Formfactor, Haralick, Gray-level co-occurrence matrix (GLCM), Gray-level run-length matrix (GLRLM), histogram. Analysis of variance, least absolute shrinkage and selection operator (LASSO), Pearson correlation, Random Forest (RF), area under the receiver operating characteristic curve (AUC) and accuracy analysis. The median age of SGCT (33.5, 25.3-45.5) was significantly lower than those of SC (58.0, 48.8-64.3) and SMT (59.0, 46.3-65.5) groups (χ2 = 37.6; P < 0.05). No significant difference was found when compared in terms of genders, tumor locations, and tumor sizes of SC, SGCT, and SMT ( ; P1 = 0.15, P2 = 0.29, P3 = 0.06). For the differential value, features extracted from joint T2w FS and CE T1w images outperformed those from T2w FS or CE T1w images alone. Compared with CE T1w images, features derived from T2w FS images yielded higher AUC in both training and validating set. The best performance of radiomics model based on joint T2w FS and CE T1w images reached an AUC of 0.773, an accuracy of 0.711. Our 3.0T MRI-based triple-classification radiomics model is feasible to differentiate SC, SGCT, and SMT, which may be applied to improve the precision of preoperative diagnosis in clinical practice. 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:752-759.

Focused Ultrasound Induced-Blood-Brain Barrier Opening in Post-Radiosurgery Mouse Brain for Locally-Enhanced Systemic Therapy

Focused ultrasound (FUS) is a novel technique that is capable of non-invasively and transiently open the blood-brain barrier (BBB). It has been show that FUS can facilitate the delivery of systemically administered therapeutic agents. Our goal here is to investigate FUF induced BBB opening in a post stereotactic radiosurgery (SRS) mouse model for novel locally-enhanced systemic therapy. We hypothesized that microvascular effects of radiation could modulate the BBB-opening induced by FUS. In this study, normal brains of C57B5 mice were treated with a fractionated SRS dose, typically given to resected tumor cavities. A single beam radiation (6Gy x 5 daily fractions) was delivered through a 10×10 mm2 collimator to half of the mouse brain using the Small Animal Radiation Research Platform (SARRP). The dose delivered to the mice was verified via two mouse-like anthropomorphic phantoms in the axial and sagittal orientations. Upon the completion of SARRP treatments, mice were divided into two groups for FUS-induced BBB opening on day 7 (acute) and day 35 (chronic), respectively. A 1.5 MHz single element FUS transducer (-6dB focal zone was 1×1×7.5 mm3) was used for all sonications. The caudate-putamen (CPu) was the FUS target and four 30s sonications were delivered on each side of the brain. The BBB opening was confirmed with contrast-enhanced T1-weighted MRI scans, while dynamic MRI scans were also performed to evaluate the blood vessel permeability. The animals were sacrificed 2 hours post sonications and lectin was injected to label the vasculature. The isodose lines from the mouse-like phantom experiment agreed well with the projected values. BBB was successfully opened after FUS sonications on both sides of the brain (with or without radiation) as evidenced by contrast-enhanced MRI. In the acute group, higher gadolinium concentration (p = 0.072) was observed on the RT positive side. MR dynamic imaging revealed a similar trend in which RT positive side had a higher (p = 0.158) vascular permeability. Although the mean vessel area in the sonicated area remained similar between the two sides, significantly less lectin labeling (blood vessel density) was observed on the RT positive hemisphere (p = 0.003) in the acute group. These observations can be attributed to increased vasculature vulnerability immediately post SRS (within 2 days) resulting in more profound BBB opening. Interestingly, this difference diminished one month later in the chronic group, where FUS elicited comparable BBB openings and minimal vascular density changes in the CPu on both sides. Localized BBB opening can be successfully induced by FUS in previously stereotactically irradiated normal brains. BBB openings were evident in both acute and chronic settings with potentially more profound outcomes if FUS is performed within 2 days of RT treatment.

18F-FDG PET/CT and MRI in Necrotizing Autoimmune Myopathy

Necrotizing autoimmune myopathy (NAM) is a relatively newly recognized subgroup of idiopathic inflammatory myopathies. The common histopathologic features are myocyte necrosis without significant inflammation. Necrotizing autoimmune myopathy can be associated with connective tissue disorders but can also be triggered by viral infections such as human immunodeficiency virus or malignancy, be statin-induced NAM, or be idiopathic. Here, the authors present the case of a 58-year-old man who was referred to our PET unit for a suspected paraneoplastic syndrome in a context of NAM. Complementary contrast-enhanced CT and 3-dimensional T1-weighted MRI were carried out subsequently in order to resolve the PET/CT abnormalities.

Contrast-enhanced fluid-attenuated inversion recovery magnetic resonance imaging was useful in detecting inflammation of the meninges in neuropsychiatric systemic lupus erythematosus: a case report

A 49-year-old woman was admitted to our hospital with recurrent episodes of paresthesia attacks evolving in 5 to 15 minutes from the left hand to the left leg through the left trunk. Neurological examination revealed cortical sensory disturbance in her left hand. Although contrast-enhanced T1-weighted MRI findings were unremarkable, contrast-enhanced fluid-attenuated inversion recovery (FLAIR) MRI revealed abnormal leptomeningeal enhancement over the sulcus of the parietal lobe, including the sulcus around the postcentral gyrus. Because we assumed the cause of the recurrent sensory attack to be meningeal inflammation around the primary somatosensory cortex, we treated this patient by increasing the dose of prednisolone. The increase in prednisolone dose completely resolved the symptom, as well as the abnormal leptomeningeal enhancement on contrast-enhanced FLAIR MRI. In patients with suspected meningeal inflammation, contrast-enhanced FLAIR MRI, which is reported to be more sensitive than contrast-enhanced T1-weighted MRI in detecting subtle abnormal leptomeningeal enhancement, should be the modality of choice.

Effect of irreversible electroporation of prostate cancer on microcirculation: Imaging findings in contrast-enhanced T1-weighted 3D MRI.

Irreversible electroporation (IRE) is a novel focal ablation technique applicable for treatment of prostate cancer (PCa). We aim to evaluate imaging findings of T1-weighted contrast-enhanced MRI after percutaneous IRE of low-risk PCa. A total of 13 male patients underwent IRE of focal low-risk PCa and were included in this analysis. Prostate IRE was conducted using 2-4 electrodes being placed under CT-fluoroscopy guidance. Dynamic contrast-enhanced 3D isotropic fat-saturated T1-weighted MRI (DCE-MRI) was performed 24-72 hours before and 24-72 hours after ablation. Ablated prostate was either homogeneously (8/13 [62%]) or heterogeneously (5/13 [38%]) hypo attenuating. Peripheral contrast enhancement manifesting as a hyper attenuating margin was observed during the arterial (60 sec) (3/13 [23%]) and venous (240 sec) (10/13 [77%]) phase. The ablation defect showed a sharp (8/13 [62%]) or blurry (5/13 [38%]) margin. The results show a venous peripheral rim enhancement in most of the cases, indicating reactive hyperaemia. The heterogeneous appearance of the defect zone in some cases may be secondary to sustained vascularization.

Radiomics Features of Multiparametric MRI as Novel Prognostic Factors in Advanced Nasopharyngeal Carcinoma.

Purpose: To identify MRI-based radiomics as prognostic factors in patients with advanced nasopharyngeal carcinoma (NPC).Experimental Design: One-hundred and eighteen patients (training cohort: n = 88; validation cohort: n = 30) with advanced NPC were enrolled. A total of 970 radiomics features were extracted from T2-weighted (T2-w) and contrast-enhanced T1-weighted (CET1-w) MRI. Least absolute shrinkage and selection operator (LASSO) regression was applied to select features for progression-free survival (PFS) nomograms. Nomogram discrimination and calibration were evaluated. Associations between radiomics features and clinical data were investigated using heatmaps.Results: The radiomics signatures were significantly associated with PFS. A radiomics signature derived from joint CET1-w and T2-w images showed better prognostic performance than signatures derived from CET1-w or T2-w images alone. One radiomics nomogram combined a radiomics signature from joint CET1-w and T2-w images with the TNM staging system. This nomogram showed a significant improvement over the TNM staging system in terms of evaluating PFS in the training cohort (C-index, 0.761 vs. 0.514; P < 2.68 × 10-9). Another radiomics nomogram integrated the radiomics signature with all clinical data, and thereby outperformed a nomogram based on clinical data alone (C-index, 0.776 vs. 0.649; P < 1.60 × 10-7). Calibration curves showed good agreement. Findings were confirmed in the validation cohort. Heatmaps revealed associations between radiomics features and tumor stages.Conclusions: Multiparametric MRI-based radiomics nomograms provided improved prognostic ability in advanced NPC. These results provide an illustrative example of precision medicine and may affect treatment strategies. Clin Cancer Res; 23(15); 4259-69. ©2017 AACR.

Early trigeminal nerve involvement in Listeria monocytogenes rhombencephalitis: case series and systematic review.

Listeria monocytogenes is associated with rhombencephalitis. However, the exact mechanisms of brainstem invasion remains poorly understood. Here, we demonstrate clinical and radiological data suggesting that Listeria may invade the brainstem via the trigeminal nerve. Three females (41, 64 and 70years) with culture proven L. monocytogenes bacteremia and rhombencephalitis were investigated in the period of 2014-16. T2-weighted and contrast-enhanced T1-weighted MRI revealed a cerebellopontine abscess in all three patients, including the involvement of the trigeminal nerve root. In two patients, MRI also revealed selective contrast enhancement of the sensory trigeminal tract in the pons and medulla oblongata. Prior to any other neurological symptoms, two patients complained of hypoesthesia and a tingling sensation in the ipsilateral half of the face, consistent with sensory trigeminal nerve dysfunction on that side. In addition, we identified another 120 cases of Listeria rhombencephalitis following a systematic review. Cranial nerves VII, V, IX, and X, respectively, medulla oblongata, cerebellum and pons, were the most frequently involved brain structures. The present clinical and radiological findings corroborate earlier data from animal experiments, indicating that L. monocytogenes may be capable of retrograde intra-axonal migration along the cranial nerves. We suggest that in a subset of patients with rhombencephalitis L. monocytogenes enters the cerebellopontine angle through the trigeminal nerve, invading the brainstem via the sensory trigeminal nuclei.

Quantitative MR imaging biomarkers of tumor heterogeneity predict prognosis in metastatic colorectal lesions.

e15121 Background: Intra-tumor heterogeneity is an independent determinant of patient survival outcomes in several tumor subtypes. Spatial variations in tumor enhancement on MRI is a macroscopic imaging marker of tumor heterogeneity. The goal of this study is to evaluate the potential role of MRI-based enhancement heterogeneity measures as predictors of survival in patients with metastatic colorectal cancer. Methods: We retrospectively analyzed T1-weighted contrast-enhanced MRI images of metastatic hepatic lesions in 41 patients (mean age 57.2 ±14.2 years) who were diagnosed with stage IV colorectal cancer between 2007 and 2013. Tumor Kras mutation status and patient survival data for up to 95 months was available for all patients. The largest metastatic hepatic lesion was identified by a radiologist and manually segmented. 14 Haralick texture features were extracted from each lesion. Cox proportional hazards regression analysis was used to assess the association between the enhancement heterogeneity measures and patient survival, with adjustment for Kras mutation status as a potential confounder. Backward stepwise feature selection was performed using p &gt; 0.1 (Wald test) to select for statistically significant features. Results:Mean survival time was 39±3.9 months for the study population (51±4.1 months for Kras-wildtype and 37±5.1 for Kras-mutants). 68% of the patients had left-sided colon cancer; 21% had concurrent pulmonary metastases and 0.5% had concurrent brain metastasis. 61%, 27% and 12% of patients were on Flofox, Folfiri or other chemotherapeutic regimen, respectively. Texture matrix homogeneity (HR &gt; 10; p = 0.016), inverse difference moment (HR &lt; 0.1; p = 0.020), entropy (HR &lt; 0.1; p = 0.033) and standard deviation (HR &gt; 10; p = 0.006) exhibited significant independent association with patient survival. With the exception of entropy, these features maintained significant contribution to survival prediction independent of Kras mutation status. Conclusions: MRI-based quantitativeintra-metastasis heterogeneity measures are associated with patient survival and may add information beyond genetic mutation status to optimize prognosis prediction in metastatic colon cancer.

Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI

BackgroundIn this study, we evaluated the ability of radiomic textural analysis of intratumoral and peritumoral regions on pretreatment breast cancer dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict pathological complete response (pCR) to neoadjuvant chemotherapy (NAC).MethodsA total of 117 patients who had received NAC were retrospectively analyzed. Within the intratumoral and peritumoral regions of T1-weighted contrast-enhanced MRI scans, a total of 99 radiomic textural features were computed at multiple phases. Feature selection was used to identify a set of top pCR-associated features from within a training set (n = 78), which were then used to train multiple machine learning classifiers to predict the likelihood of pCR for a given patient. Classifiers were then independently tested on 39 patients. Experiments were repeated separately among hormone receptor-positive and human epidermal growth factor receptor 2-negative (HR+, HER2−) and triple-negative or HER2+ (TN/HER2+) tumors via threefold cross-validation to determine whether receptor status-specific analysis could improve classification performance.ResultsAmong all patients, a combined intratumoral and peritumoral radiomic feature set yielded a maximum AUC of 0.78 ± 0.030 within the training set and 0.74 within the independent testing set using a diagonal linear discriminant analysis (DLDA) classifier. Receptor status-specific feature discovery and classification enabled improved prediction of pCR, yielding maximum AUCs of 0.83 ± 0.025 within the HR+, HER2− group using DLDA and 0.93 ± 0.018 within the TN/HER2+ group using a naive Bayes classifier. In HR+, HER2− breast cancers, non-pCR was characterized by elevated peritumoral heterogeneity during initial contrast enhancement. However, TN/HER2+ tumors were best characterized by a speckled enhancement pattern within the peritumoral region of nonresponders. Radiomic features were found to strongly predict pCR independent of choice of classifier, suggesting their robustness as response predictors.ConclusionsThrough a combined intratumoral and peritumoral radiomics approach, we could successfully predict pCR to NAC from pretreatment breast DCE-MRI, both with and without a priori knowledge of receptor status. Further, our findings suggest that the radiomic features most predictive of response vary across different receptor subtypes.

18F-FCho PET and MRI for the prediction of response in glioblastoma patients according to the RANO criteria.

In this study, we investigated fluorine-18 fluoromethylcholine (F-FCho) PET and contrast-enhanced MRI for predicting therapy response in glioblastoma (GB) patients according to the Response Assessment in Neuro-Oncology criteria. Our second aim was to investigate which imaging modality enabled prediction of treatment response first. Eleven GB patients who underwent no surgery or debulking only and received concomitant radiation therapy (RT) and temozolomide were included. The gold standard Response Assessment in Neuro-Oncology criteria were applied 6 months after RT to define responders and nonresponders. F-FCho PET and MRI were performed before RT, during RT (week 2, 4, and 6), and 1 month after RT. The contrast-enhancing tumor volume on T1-weighted MRI (GdTV) and the metabolic tumor volume (MTV) were calculated. GdTV, standardized uptake value (SUV)mean, SUVmax, MTV, MTV×SUVmean, and percentage change of these variables between all time-points were assessed to differentiate responders from nonresponders. Absolute SUV values did not predict response. MTV must be taken into account. F-FCho PET could predict response with a 100% sensitivity and specificity using MTV×SUVmean 1 month after RT. A decrease in GdTV between week 2 and 6, week 4 and 6 during RT and week 2 during RT, and 1 month after RT of at least 31%, at least 18%, and at least 53% predicted response with a sensitivity and specificity of 100%. As such, the parameter that predicts therapy response first is MR derived, namely, GdTV. Our data indicate that both F-FCho PET and contrast-enhanced T1-weighted MRI can predict response early in GB patients treated with RT and temozolomide.

Detection of Local Tumor Recurrence After Definitive Treatment of Head and Neck Squamous Cell Carcinoma: Histogram Analysis of Dynamic Contrast-Enhanced T1-Weighted Perfusion MRI.

This study aimed to explore the added value of histogram analysis of the ratio of initial to final 90-second time-signal intensity AUC (AUCR) for differentiating local tumor recurrence from contrast-enhancing scar on follow-up dynamic contrast-enhanced T1-weighted perfusion MRI of patients treated for head and neck squamous cell carcinoma (HNSCC). AUCR histogram parameters were assessed among tumor recurrence (n = 19) and contrast-enhancing scar (n = 27) at primary sites and compared using the t test. ROC analysis was used to determine the best differentiating parameters. The added value of AUCR histogram parameters was assessed when they were added to inconclusive conventional MRI results. Histogram analysis showed statistically significant differences in the 50th, 75th, and 90th percentiles of the AUCR values between the two groups (p < 0.05). The 90th percentile of the AUCR values (AUCR90) was the best predictor of local tumor recurrence (AUC, 0.77; 95% CI, 0.64-0.91) with an estimated cutoff of 1.02. AUCR90 increased sensitivity by 11.7% over that of conventional MRI alone when added to inconclusive results. Histogram analysis of AUCR can improve the diagnostic yield for local tumor recurrence during surveillance after treatment for HNSCC.

Malignant peripheral nerve sheath tumor in the paraspinal region mimicking a benign peripheral nerve sheath tumor: a case report

Malignant peripheral nerve sheath tumors are extremely rare in the general population and display a predilection for metastasis to the lungs. Here, we present a rare case of a malignant peripheral nerve sheath tumor located in the paraspinal region and highlight the importance of preoperative biopsy in diagnosis of spinal epidural peripheral nerve sheath tumors. We describe the clinical course of the patient as well as the radiological and pathological findings of the tumor. A 14-year-old girl presented with a six-month history of sacral pain. Occasionally she experienced left leg pain and abnormal gait. General physical examination revealed sensorial loss in the L5-S1 regions. T1-weighted sagittal MRI showed a hypointense oval mass and the contrast-enhanced T1-weighted axial MRI image showed heterogeneous enhancement of the tumor. On CT imaging, this tumor characteristically appears as a dumbbell-like mass with punctate calcification and widening L5-S1 intervertebral foramen. Complete resection was performed using an anterior approach. Intraoperative pathological examination revealed evidence of malignancy and subsequent immunohistochemical analysis of the tumor confirmed the diagnosis of MPNST. The postoperative course was uneventful and the patient has had significant improvement in her symptoms 1month postoperatively. Preoperative biopsy should be routinely performed for pathological differential diagnosis of spinal epidural PNSTs as well as surgical decision-making. Furthermore a combination of clinical manifestation, radiological findings and biopsy should also be pursued for diagnosing these tumors.

Sparse patch-based method applied to mri-only radiotherapy planning

Introduction Replacing CT/MRI in radiotherapy chain with MRI-only will remove CT/MRI fusion uncertainties and avoid the patient the dose of ionizing radiation from CT. Purpose We propose to generate pseudo-CT (pCT) from conventional MRI and to assess it for MRI-only brain radiotherapy planning (RTP). Material/methods In twelve patients with brain tumors, CT and contrast-enhanced T1-weighted MRI were registered. A library of patches was built by extracting 2D patches, defined as MRI squares of 5 × 5voxels, in each voxel location and labelling them with corresponding HU values. Each patch in target MRI was reconstructed from a sparse linear combination of database patches locally searched. The sparse coefficients were estimated by optimizing the Elastic-Net (EN) objective function. EN was enhanced by additional penalty term based on the structural similarity between target and database patches. Radiological and dosimetric assessments of pCT were done for all patients using leave one out cross-validation. Mean absolute error between CT and pCT radiological paths (MAE WEPL ) over a grid were computed. VMAT planning was performed on CT and pCT for PTVs delineated in homogenous (PTV1) and heterogeneous regions (PTV2) and compared. Percentage of dose metrics deviations (PDMD) for PTVs and OARS were computed. Results Radiological path estimation was accurate with MAE WEPL = 2.6 ± 0.4 mm. Good agreement with conventional planning techniques was obtained; the highest PDMD were D 98% = 0.05 ± 0.1 for PTV1, D 98% = −0.81 ± 0.47 for PTV2 and D mean = 0.35 ± 0.7 for left lens. Conclusion We presented a novel technique to generate pCT for MRI-only brain RTP. In the future, we will investigate its use for PET/MR attenuation correction.

Retrieval of Brain Tumors by Adaptive Spatial Pooling and Fisher Vector Representation.

Content-based image retrieval (CBIR) techniques have currently gained increasing popularity in the medical field because they can use numerous and valuable archived images to support clinical decisions. In this paper, we concentrate on developing a CBIR system for retrieving brain tumors in T1-weighted contrast-enhanced MRI images. Specifically, when the user roughly outlines the tumor region of a query image, brain tumor images in the database of the same pathological type are expected to be returned. We propose a novel feature extraction framework to improve the retrieval performance. The proposed framework consists of three steps. First, we augment the tumor region and use the augmented tumor region as the region of interest to incorporate informative contextual information. Second, the augmented tumor region is split into subregions by an adaptive spatial division method based on intensity orders; within each subregion, we extract raw image patches as local features. Third, we apply the Fisher kernel framework to aggregate the local features of each subregion into a respective single vector representation and concatenate these per-subregion vector representations to obtain an image-level signature. After feature extraction, a closed-form metric learning algorithm is applied to measure the similarity between the query image and database images. Extensive experiments are conducted on a large dataset of 3604 images with three types of brain tumors, namely, meningiomas, gliomas, and pituitary tumors. The mean average precision can reach 94.68%. Experimental results demonstrate the power of the proposed algorithm against some related state-of-the-art methods on the same dataset.