Axial T2 Research Articles

Interrater reliability of modified visual mrı rating scale assessing atrophy and white matter changes.

<p>Cortical atrophy and white matter changes are common findings on magnetic resonance imaging among elderly. Several visual scales have been proposed to evaluate these changes using neuroimaging. We have recently proposed a scale (Modified Visual Magnetic Resonance Rating Scale) recently which allows us to evaluate atrophy, white matter hyperintensities, basal ganglia and infratentorial infarcts together. Our aim in this study was to evaluate the interrater reliability of magnetic resonance visual assessment using this scale between two neurologists and a radiologist.&nbsp;</p>. <p>Randomly selected 30 patients in different ages who underwent brain magnetic resonance imaging between January 2014 and March 2015 were included. Axial T1, coronal T2, and axial FLAIR sequences were visually scored by two neurologists and one radiologist separately. Sulcal, ventricular and medial temporal lobe atrophy, periventricular and subcortical white matter hyperintensities, basal ganglia and infratentorial infarcts were graded according to our scale. The interrater reliability and internal consistency analysis were evaluated by using intraclass correlation coefficient and Cronbach&rsquo;s alpha tests.&nbsp;</p>. <p>The interrater agreements vary between good to excellent. The interrater correlations are moderate to excellent. Interrater correlations were excellent between two neurologists, especially on ventricular atrophy, medial temporal atrophy, basal ganglia infarcts, infratentorial infarcts. When assessing ventricular atrophy, interrater correlations between individual raters were higher than sulcal atrophy. We found good correlations between neurologists and radiologist, and excellent correlations between the two neurologists for medial temporal atrophy. We found excellent interrater correlations between neurologists and radiologist for white matter hyperintensities.</p>. <p>Our scale is a reliable tool assessing both atrophy and white matter hyperintensities with a good interrater reliability. Ventricular atrophy seems to be a more reliable marker than sulcal atrophy when assessing the atrophy on neuroimaging of a patient with memory decline. We think that the total score of the scale will also guide us in clinical practice.</p>.

The effect of lumbar multifidus cross-sectional areas on transforaminal epidural steroid injection: An observational clinical study.

Multifidus has an important role in spinal stability, and multifidus degeneration causes long-term disability and low back pain. This study aimed to investigate the effect of multifidus cross-sectional area on transforaminal epidural steroid injections (TFESI). Patients with single-level disc herniation were included in the study. Total multifidus cross-sectional area (TM-CSA) and functional cross-sectional area (FM-CSA) were measured from axial T2 MRI of the patients, and FM-CSA/TM-CSA ratio was calculated for determination of muscle degeneration or fat infiltration. Numerical Rating Scale (NRS) scores at the pre-injection, 3rd week, and 3rd month visits were recorded. A decrease of 50% or more in the NRS score in the 3rd month was accepted as a treatment success (TS), and patients were divided into TS and treatment failure groups. A total of 120 patients were included in the study; 57 of the patients were female, and 63 of them were male. Of the patients included in the study, 68 had herniation at the L5-S1 disc level and 52 had herniation at the L4-L5 disc level. FM-CSA and FM-CSA/TM-CSA ratio were found to be significantly lower below the disc herniation level on the affected side (p<0.05). The affected side TM-CSA and FM-CSA were higher in the TS group and TM-CSA/FM-CSA ratios were equal in both groups. Multifidus CSA was found to be lower on the affected side. However, the effect of multifidus CSA on the success of TFESI has not been determined.

Spinal Cord Delineation Based on Computed Tomography Myelogram Versus T2 Magnetic Resonance Imaging in Spinal Stereotactic Body Radiation Therapy

Spinal cord delineation is critical to the delivery of stereotactic body radiation therapy (SBRT). Although underestimating the spinal cord can lead to irreversible myelopathy, overestimating the spinal cord may compromise the planning target volume coverage. We compare spinal cord contours based on computed tomography (CT) simulation with a myelogram to spinal cord contours based on fused axial T2 magnetic resonance imaging (MRI). Eight patients with 9 spinal metastases treated with spinal SBRT were contoured by 8 radiation oncologists, neurosurgeons, and physicists, with spinal cord definition based on (1) fused axial T2 MRI and (2) CT-myelogram simulation images, yielding 72 sets of spinal cord contours. The spinal cord volume was contoured at the target vertebral body volume based on both images. The mixed-effect model assessed comparisons of T2 MRI- to myelogram-defined spinal cord in centroid deviations (deviations in the center point of the cord) through the vertebral body target volume, spinal cord volumes, and maximum doses (0.035 cc point) to the spinal cord applying the patient's SBRT treatment plan, in addition to in-between and within-subject variabilities. The estimate for the fixed effect from the mixed model showed that the mean difference between 72 CT volumes and 72 MRI volumes was 0.06 cc and was not statistically significant (95% confidence interval, -0.034, 0.153; P=.1832). The mixed model showed that the mean dose at 0.035 cc for CT-defined spinal cord contours was 1.24 Gy lower than that of MRI-defined spinal cord contours and was statistically significant (95% confidence interval, -2.292, -0.180; P=.0271). Also, the mixed model indicated no statistical significance for deviations in any of the axes between MRI-defined spinal cord contours and CT-defined spinal cord contours. CT myelogram may not be required when MRI imaging is feasible, although uncertainty at the cord-to-treatment volume interface may result in overcontouring and hence higher estimated cord dose-maximums with axial T2 MRI-based cord definition.

Classification of low- and high-grade gliomas using radiomic analysis of multiple sequences of MRI brain.

Gliomas are frequent tumors of brain parenchyma, which have histology similar to that of glial cells. Accurate glioma grading is required for determining clinical management. The background of this study is to investigate the accuracy of magnetic resonance imaging (MRI)-based radiomic features extracted from multiple MRI sequences in differentiating low and high-grade gliomas. This is a retrospective study. It includes two groups. Group A includes patients with confirmed histopathological diagnosis of low (23) and high-grade (58) gliomas from 2012 to 2020 were included. The MRI images were acquired using a Signa HDxt 1.5 Tesla MRI (GE Healthcare, Milwaukee, USA). Group B includes an external test set consisting of low- (20) and high-grade gliomas (20) obtained from The Cancer Genome Atlas (TCGA). The radiomic features were extracted from axial T2, apparent diffusion coefficient map, axial T2 fluid-attenuated inversion recovery, and axial T1 post-contrast sequences for both the groups. The Mann - Whitney U test was performed to assess the significant radiomic features useful for distinguishing the glioma grades for Group A. To determine the accuracy of radiomic features for differentiating gliomas, AUC was calculated from receiver operating characteristic curve analysis for both groups. Our study noticed in Group A, fourteen MRI-based radiomic features from four MRI sequences showed a significant difference (p < 0.001) in differentiating gliomas. In Group A, we noticed T1 post-contrast radiomic features such as first-order variance (FOV) (sensitivity - 94.56%, specificity - 97.51%, AUC - 0.969) and GLRLM long-run gray-level emphasis (sensitivity - 97.54%), specificity - 96.53%, AUC - 0.972) had the highest discriminative power for distinguishing the histological subtypes of gliomas. Our study noticed no statistical significant difference between ROC curves of significant radiomic features for both groups. In Group B, the T1 post-contrast radiomic features such as FOV (AUC-0.933) and GLRLM long-run gray-level emphasis (AUC-0.981) had also shown high discriminative power for distinguishing the gliomas. Our study concludes that MRI-based radiomic features extracted from multiple MRI sequences provide a non-invasive diagnosis of low- and high-grade gliomas and can be implemented in clinical settings for diagnosing the glioma grades.

Cohort study on the relationship between morphologic parameters of paravertebral muscles, BMI and lumbar lordosis on the severity of lumbar stenosis.

There is a growing body of literature separately linking lumbar spinal stenosis (LSS) with various factors such as paravertebral muscle (PVM) impaired function/morphology, lordosis or BMI. However, their interplay is yet to be known. The present study aims to investigate the relationship between PVM morphology, BMI and lumbar lordosis in a population with a surgical indication for LSS. A cross-sectional retrospective study was conducted on a group of 122 patients diagnosed with LSS in a hospital setting and scheduled for spine surgery. Epidemiological data and body mass index (BMI) were gathered. The cross-sectional area of the psoas muscle (rCSA) at the L4-L5 disc level on preoperative axial T2 MRI was measured. Fat infiltration of the anterior (APVM) and posterior paravertebral muscles (PPVM) was evaluated according to Goutallier classification while the severity of lumbar stenosis was staged according to Schizas criteria. Lumbar lordosis was measured on sagittal MRI using Cobb's angle method. The presence of the "rising psoas" sign was also noted. Statistical analysis of the data was performed using Pearson and Spearman correlations. Statistical analysis revealed a moderate correlation between the severity of LSS and BMI (p = 0.001), and fatty infiltration of paravertebral muscles (p = 0.000, p = 0.000). Adjusting for age, gender, and BMI resulted in a low correlation (p = 0.003, p = 0.045), rCSA correlated negatively with age, gender, and lordosis. BMI had a low positive correlation with lumbar lordosis (p = 0.006), severity (p = 0.001), number of levels (p = 0.005) and PPVM (p = 0.031). This study highlighted the relationship between PVM morphology and the severity of radiological signs in patients with LSS undergoing spine surgery and found a correlation independent of age, gender, and BMI. BMI was also shown to correlate with the severity after controlling for age and gender. rCSA has limited use in evaluating the severity of LSS.

Symptoms: Purple Ear Drum and Hearing Loss

Symptoms: Purple Ear Drum and Hearing Loss

Symptoms: Sudden Hearing Loss and Aural Fullness

Symptoms: Sudden Hearing Loss and Aural Fullness

ROLE OF MAGNETIC RESONANCE IMAGING IN EVALUATION OF PAINFUL HIP JOINT

This study aims to evaluate the diagnostic value of MRI in the assessment of painful hip joint. Background: Radiographic evaluation is an initial and crucial role in patients with painful hip joint. Hip pain has different aetiologies in adults and children. MRI is the investigation choice for characterizing the various disorders and assessing the full extent of bone, cartilage and soft tissue abnormality of the hip joint. Methods: This prospective study included 50 patients with painful hip joint. The following MR sequences were performed to all patients: Coronal T1, T2 &amp; STIR WIs, axial T1&amp;T2WIs, and sagittal T1WI. Patient's history, local examination of the diseased hip and laboratory investigations were performed. Results: Male patients ages ranged from 1 to 60 years with a mean age of 35 years. Conclusion: MRI of the hip joint is informative, diagnostic, and accurate for the assessment of hip pain and sufficient imaging modality for delineation of different hip joint pathology.

NIMG-66. CANNY EDGE DETECTION ALGORITHM FOR QUANTITATIVE DIFFERENTIATION BETWEEN DIFFUSE AND CIRCUMSCRIPT GLIOMA GROWTH PATTERNS ON MRI

Abstract BACKGROUND Lower grade gliomas show heterogenous appearance on T2-weighted MRI. Some tumors grow diffusely along axonal structures whereas others distort adjacent brain tissue through local mass effect. The diagnostic, therapeutic and prognostic implication of differential growth patterns on MRI remain unknown and are difficult to assess quantitatively. METHODS A web-based application allowing for image preprocessing and providing a comprehensive edge detection tool by means of quantifying tumor border delineation on T2-weighted images based on the canny edge detection algorithm was developed. A sigma value between 1 and 100 determined the threshold where tumor borders where not detected anymore, with 1 equating to the lowest threshold and thus detection of all edges contained in the image. Two experienced faculty members assigned sigma values to axial T2 images of a random sample of 20 WHO grade 2 astrocytomas, IDH-mutant and 1p/19q-non-codeleted. The sigma values were then compared with a binary, subjective rating by the same faculty staff according to the perceived predominant growth pattern (diffuse versus circumscript) of each glioma. RESULTS When subjectively categorizing tumors binarily (diffuse versus circumscript), there was moderate interrater variability between observers (cohen’s kappa=0.6). Raters agreed in 16 of 20 cases, terming 7 gliomas unanimously diffuse and 9 gliomas circumscript. In 4 cases, the raters opinions diverged. The sigma values differed significantly between diffuse and circumscript tumors in both raters (rater 1, p=0.002; rater 2, p=0.018). For rater 1, the mean sigma difference between diffuse and circumscript tumors was 10.7 and 9.3 for rater 2. The mean overall sigma value was 13.3 for rater 1 and 18.7 for rater 2 (p=0.005). CONCLUSION Edge detection algorithms can be efficiently applied on MRI scans and are highly accurate in differentiating diffuse from circumscript gliomas. Objectification demands defining imaging criteria for diffuse and circumscript appearance of lower grade gliomas on MRI.

Dysphagia and Tongue Deviation: An Unexpected Cause.

Dysphagia and Tongue Deviation: An Unexpected Cause.

PO17: Assessment of a Prototype Gynecologic US/MR/CT Phantom for Utilization in Interstitial Brachytherapy Training

<h3>Purpose</h3> Simulation-based education has been previously demonstrated to be efficacious for teaching intracavitary (IC) brachytherapy. In principle, the success of this "hands-on" approach could be extended to interstitial (IS) and/or hybrid IC/IS brachytherapy. Yet, this education technique has not been adopted and one reason may be the shortcomings of current simulation models. Highly-desirable features which were not available in current simulation models included: non-stylized realistic anatomical representation, compatibility with image-guidance (ultrasound, CT, and/or MRI), practical material for needle placement, and commercial availability. Our work presents results from our evaluation of the physical, radiographic, and imaging characteristics of a new commercial prototype phantom designed for simulation-based education. <h3>Materials and Methods</h3> The SIM (Simulated Inanimate Models, Pittsford, NY) gynecological trainer prototype phantom was constructed based on a representative female pelvis CT imageset to provide physically realistic anatomy within a block of tissue-like material. The original CT imageset was truncated to a region of interest with dimensions of 160 × 160 × 220 mm. To provide a planning imageset, the phantom was imaged using CT with 1 mm slice reconstruction and using an axial T2 MRI sequence with 1.5 mm slice reconstruction. We assessed the anatomic dimensions of the model, physical compatibility with different hybrid applicators, and the quality of the radiographic model on imaging. After the implant was approved, a planning CT was taken, an HR-CTV was drawn, and the plan quality was evaluated. After clinical assessment, feedback was provided to the manufacturer for consideration in future designs. <h3>Results</h3> The phantom consisted of a 15 mm introitus which preceded a cylindrical air cavity with length of 75 mm and average diameter of 20 mm with irregular ridges intended to represent a vaginal canal which was capped by a pliable opening of 3 mm intended to represent an intact cervical os. Near the cervical region, the cylindrical air cavity widened from 20 to 28 mm. Proximal to the cervical os, there was a conical air cavity 80 mm in length which represented an intrauterine canal. In addition to the air cavities and tissue, the phantom was composed of three other distinct materials designed to represent bones, bladder, and rectum - each of which was distinguishable on US-, CT- and MR-based imaging. Within the phantom, an experienced physician was able to place a tandem-and-ovoid (TO) applicator with a 30 degree curved tandem, but was restricted to ovoid sizes ≤ 20 mm. To supplement the TO, the physician was able to place three IS needles to produce a realistic hybrid IC/IS implant intended to cover a hypothetical 35 × 35 × 40 mm³ HR-CTV. Coronal and sagittal views of the phantom post-implant planning CT imageset with <i>in situ</i> hybrid IC/IS equipment are shown in Figure 1. Figure 1 also contains the final plan with HR-CTV D_90% = 102% with the purple HR-CTV contour and red 100% isodose line. The primary clinical feedback provided to the manufacturer on this prototype phantom included: enlarging the vaginal canal dimensions to physically accommodate larger IC applicators; adding a visual/palpable cervical tumor to provide a target and recreate the needle-placement decision-making process. <h3>Conclusions</h3> We report the basic characteristics of a novel gynecologic phantom prototype which intended for simulation-based training. This phantom provided an anatomically-realistic "hand-on" tool composed of various materials which were each distinguishable on three modalities: US, CT, MR. Clinical feedback was provided to the manufacturer for consideration in the next generation of this phantom.

Symptom: Runny Nose Six Years After Acoustic Neuroma Surgery

Symptom: Runny Nose Six Years After Acoustic Neuroma Surgery

Clinical and Radiomics-Based Deep Learning Predictive Model for Early Treatment Failure after Neoadjuvant Radiochemotherapy for Rectal Cancer

<h3>Purpose/Objective(s)</h3> As shown in RAPIDO and PRODIGE-23 trials, total neoadjuvant therapy for rectal cancer increases the complete response rate, however, the overall survival benefit remains uncertain. Although postponing surgery assures more time for tumor downstaging, it also increases surgical complications and can worsen prognosis in non-responding tumors. We aimed to develop a clinical and radiomics-based model for early treatment failure (ETF) prediction after neoadjuvant radiochemotherapy (RCHTx) for rectal cancer. <h3>Materials/Methods</h3> We conducted a prospective cohort analysis of 92 consecutive and eligible patients with rectal adenocarcinoma treated with neoadjuvant radiochemotherapy in the years 2018-2020, and followed until February 2022. We defined ETF as postoperative poor pathological response and no MRI-confirmed downstaging; or unresectability after neoadjuvant treatment; or cancer-related or treatment-related death within 18 months since treatment initiation. Collected clinical data included physical examination, grading, staging (before and after RCHTx), biomarker levels, RCHTx prescription details, and pre-operative MRI tumor and nodal characteristics. Radiomic features were extracted from GTV delineated on axial MRI T2 TSE sequences. To develop a predictive model, we followed OmicSelector-based (https://biostat.umed.pl/OmicSelector) feature selection, logistic regression (LR), and artificial deep neural network model development procedure. After splitting into training (60%), testing (20%), and validation (20%) datasets, the final feature set was selected based on the highest average logistic regression accuracy on all sets, while all patients with MRI performed outside our institution were included in the testing set (compensating possible batch effect). <h3>Results</h3> ETF was experienced by 24% of patients and was associated with significantly shorter overall survival (median 12.1 months [95%CI:8.5-16.5] vs. not reached, p<0.0001). None of the clinical factors was significantly associated with ETF (adjusted p value>0.05; AUC ROC range 0.39-0.64). LR model based on clinical factors presented overfitting (accuracy 82% on the training set, 56.2% on testing and 68.8% on validation set). The best feature set included 14 selected radiomic features, patient's weight, T-stage, grading, mesorectal fascia and nodal involvement. LR model based on those features achieved perfect accuracy on training and testing sets and 81.3% accuracy on the validation set. Deep neural network model utilizing selected clinical and radiomic features achieved 87.5% accuracy (80% sensitivity, 91% specificity) on testing and 93.8% accuracy (100% sensitivity, 91% specificity) on validation set. <h3>Conclusion</h3> Combined clinical and radiomics-based deep learning model could predict ETF after RCHTx for rectal cancer with at least 80% sensitivity and 90% specificity. Prediction of ETF after RCHTx could select high-risk patients who may require non-standard treatment.

Assessment of Interfraction Change in Gross Tumor Volume of Anal Carcinoma Patients Undergoing Curative Chemoradiotherapy

<h3>Purpose/Objective(s)</h3> Radiation with concurrent chemotherapy (CRT) represents standard definitive therapy for anal cancer. CRT protocols result in excellent local control but are associated with significant acute and late morbidity. Adaptive planning techniques may allow for decrease in treatment volume and reduce toxicity. In this study, we used serial MRI scans to assess changes in gross tumor volume (GTV) during curative CRT. <h3>Materials/Methods</h3> Since 2019, we have instituted a REB-approved prospective registry study of de-escalated radiotherapy for patients undergoing CRT for anal cancer. Patients received a total dose of 45-63 Gy in 25-35 fractions with concurrent Capecitabine and a single dose of Mitomycin-C on day 1. In addition to pre-treatment (pre-tx) CT and MR simulation, patients also underwent MR simulation at fraction 11 (fx11) and fraction 21 (fx21). The GTV was contoured separately on individual axial T2 sequences. Median (inter-quartile-range) was used for descriptive statistics and the Mann-Whitney-Wilcoxon was used between groups of interfractional contours to determine statistically significant differences in tumor size between fractions. The Kruskal-Wallace test was used to determine significance between all 3 GTV volumes. P-values of <0.05 were considered statistically significant. <h3>Results</h3> A total of 24 patients were accrued. All patient completed RT without interruptions. All 24 had pre-tx MRI. During CRT course, 22 had a second MRI scan (fx11), and 19 had a third (fx21) scan. Table 1 shows the median (IQR) pre-tx GTV and the absolute and percent reduction in the GTV at fx11 and fx21 compared to pre-treatment GTV. Median (IQR) reduction in GTV between pre-tx and fx11 and fx21 MRI was 6.1cc (3.8-12.1) and 7.8cc (5.7-14.6), respectively. Median reduction in GTV between fx11 and fx21 was 2.9cc (1.3-6.6). After normalizing volumes as the percentage of pre-tx GTV, median (IQR) volume was 62.5% (51.6-69.7) (p<0.001) at fx11 and 43.6% (34.2-55.6) (p<0.001) at fx21. Based on Kruskal-Wallace test, overall change between GTVs at all 3 time points was found to be significant, p=0.042. <h3>Conclusion</h3> For patients undergoing CRT for anal cancer, there appears to be an early and significant reduction in the tumor volume over time. This study helps define planning adaptation parameters using serial MRI during CRT and will inform strategies to reduce normal tissue exposure

The unique features of middle cranial fossa and Sylvian fissure arachnoid cysts in children: MRI evaluation.

The purpose of the study is to evaluate MRI findings of middle fossa arachnoid cysts in children according to Galassi classification and determine the differences between types and to assess the morphological changes in cysts during follow-up imaging. MR images of 266 middle fossa arachnoid cysts of 255 pediatric patients were evaluated by two experienced radiologists retrospectively. MRI features including the sidedness of the cyst, Galassi type, parenchymal compression findings (cortical flattening and white matter compression), bone remodeling, and midline shift were evaluated on axial T2- and T1-weighted images. Follow-up MRI and available CSF flow MR imaging data were evaluated for change in cyst size and cisternal connections, respectively. The most common type was type 1 according to Galassi classification. The accompanying bone remodeling and white matter compression had a higher incidence in Galassi type 2 and 3 groups than Galassi type 1. Mean age of patients with bone remodeling and white matter compression was significantly higher in patients with Galassi type 1. All patients with cyst enlargement were younger than 2years of age, and all of them were Galassi type 1. Cisternal connection was demonstrated in 7 patients. While parenchymal compression and bone remodeling are expected findings in Galassi type 2 and 3 cysts, these features can also be seen in smaller Galassi type 1 cysts, regardless of size. Most of the middle fossa arachnoid cysts remain stable on follow-up imaging, and the increase in size is not an expected finding, especially in older children.

Preoperative Extrapancreatic Extension Prediction in Patients with Pancreatic Cancer Using Multiparameter MRI and Machine Learning-Based Radiomics Model

Pancreatic cancer is a common malignant tumor with a dismal prognosis. Preoperative differentiation of extrapancreatic extension (EPE) based on radiomics will facilitate treatment decision-making. This research retrospectively recruited 156 patients from two medical centers. 122 patients from the center A were randomly divided into the training set and the internal test set in a 4:1 ratio. Additionally, 34 patients from the center B served as the external test set. Radiomics features were extracted from multiparametric MRI (MP-MRI), containing axial T2 weighted imaging (T2WI), diffusion weighted imaging (DWI), and dynamic contrast enhancement (DCE) sequences. The three-step method was used for feature extraction: SelecteKBest, least absolute shrinkage and selection operator (LASSO) algorithm, and recursive feature elimination based on random forest (RFE-RF). The model was constructed using six classifiers based on machine learning, and the classifier with the best performance was chosen. Finally, clinical factors associated with EPE were incorporated into the combined model. The classifier with the best performance was XGBoost, which obtained area under curve (AUC) values of 0.853 and 0.848 in the internal and external test sets, respectively. Through SelectKBest, the most relevant clinical factor for EPE was determined to be platelet, which was then added to the combined model, yielding AUC values of 0.880 and 0.848 in the internal and external test sets, respectively. Radiomics models had the potential to noninvasively and accurately predict EPE before surgery. Additionally, it would add value to personalized precision treatment.

S2429 A Rare Case of Esophageal Adenocarcinoma Presenting as an Isolated Brain Lesion 6 Years After Treatment

Introduction: Esophageal adenocarcinomas account for ∼1% of all cancers in the U.S. The prevalence of central nervous system (CNS) metastases associated with these cancers is around 1.8%. Response rates to standard of care are poor and prognosis is dismal. Often CNS involvement is associated with widely metastatic disease, herein, we present a case of a solitary brain lesion from esophageal adenocarcinoma at first recurrence. Case Description/Methods: A 72-year-old-male with a 40 pack-year smoking presented with progressive dysphagia in March 2015. Contrast enhanced CT of the chest, abdomen and pelvis revealed a constricting mass at the esophagogastric junction that led to endoscopy guided biopsy revealing esophageal adenocarcinoma. He underwent neoadjuvant chemotherapy (cisplatin/5-fluorouracil) and radiation therapy followed by esophagogastrectomy in July of 2015 where diagnosis of stage IIIBT3N2cM0 esophageal adenocarcinoma was confirmed. Clinical and imaging surveillance for 6 years had not shown any progression of cancer. However, in June of 2021, he presented with altered mental status that led to contrast enhanced brain MRI showing a T2 hyperintense left parietal lobe mass with an 8 mm midline shift and surrounding vasogenic edema (Figure). FDG PET-CT head to toes did not show extracranial recurrence. He underwent left posterior temporal craniotomy for resection of tumor confirming the diagnosis of metastatic esophageal adenocarcinoma. IHC showed positivity of cytokeratin7, CDX2 and SATB2. Whole exome sequencing revealed mutations in ARID1A, FH, and TP53 with variants of unknown significance of ATM and CDH. Tumor displayed proficient mismatch repair protein, a combined positive score of 15 for PD-L1, and negative Her2/Neu. Further sequencing showed tumor mutational burden of 4, no genomic loss of heterozygosity, and stable microsatellite repeats. He received gamma-knife radiation to the solitary left temporal lobe lesion. Patient continues to maintain his quality of life with no evidence of clinical and radiographic recurrence. Discussion: Isolated brain metastasis from esophageal adenocarcinoma is a very rare phenomenon. Limited data suggests that the survival of patients with isolated CNS lesions is < 1 year, however, achieving pathologic complete response after neoadjuvant chemo-radiation therapy has shown to improve survival. These esophageal cancers with isolated CNS metastases may share a unique genomic profile and more research is required to understand their alterations.Figure 1.: MRI of the brain. 1A- Pre-op axial OLEA of L. temporal lobe tumor (06/2021), 1B- Pre-op axial coronal T1 (06/2021), 1C- Follow-up T2 MRI.

Ultrafast cervcial spine MRI protocol using deep learning-based reconstruction: Diagnostic equivalence to a conventional protocol

PurposeA major drawback of magnetic resonance imaging (MRI) is its limited imaging speed. This study proposed an ultrafast cervical spine MRI protocol (2 min 57 s) using deep learning-based reconstruction (DLR) and compared the diagnostic results to those of conventional MRI protocols (12 min 54 s). MethodsFifty patients who underwent cervical spine MRI using both conventional and ultrafast protocols, including sagittal T1-weighted, T2-weighted, short-TI inversion recovery, and axial T2*-weighted imaging were included in this study. The ultrafast protocol shortened the acquisition time to approximately-one-fourth of that of the conventional protocol by reducing the phase matrix, oversampling rate, and number of excitations, and by applying compressed sensing. To compensate for the decreased signal-to-noise ratio caused by acceleration, noise reduction using DLR was performed. For image interpretation, three neuroradiologists graded or classified degenerative changes, including central canal stenosis, foraminal stenosis, endplate degeneration, disc degeneration, and disc hernia. The presence of other pathologies was also recorded. Given the absence of a reference standard, we tested the interchangeability of the two protocols by calculating the 95% confidence interval (CI) of the individual equivalence index. We also assessed the inter-protocol intra-reader agreement using kappa statistics. ResultsExcept for endplate degeneration, the 95 % CI of the individual equivalence index for all variables did not exceed 5 %, indicating interchangeability between the two protocols. The kappa values ranged from 0.600 to 0.977, indicating substantial to almost perfect agreement. ConclusionsThe proposed ultrafast MRI protocol yielded almost equivalent diagnostic results compared as the conventional protocol.

Predictive Value of 18 F-FDG PET/MRI for Pleural Invasion in Solid and Subsolid Lung Adenocarcinomas Smaller Than 3cm.

Positron emission tomography (PET)/MRI combines the characteristics of metabolism imaging and high soft tissue resolution, and could provide high diagnostic efficacy for assessment of pleural invasion (PI) of lung cancer. To investigate the application of 18 F-fluorodeoxyglucose (FDG) PET/MRI for predicting PI of lung cancer with the maximum diameter ≤3cm. Prospective. A total of 44 patients with non-small cell lung cancer (NSCLC), age from 39 to 79 years old, including 19 (56.82%) females. A 3-T, hybrid PET/MRI including axial fast spin echo respiratory-triggered T2 fat-suppressed imaging (T2FS) and echo planar imaging diffusion-weighted imaging (DWI). The maximum standardized uptake value (SUVmax) of all lesions was measured on PET images. Localized effusion outside the contact between the nodules and the pleura on T2FS and signal at the contact between the nodules and the pleura on DWI were evaluated by experienced physicians through visual assessment of the MRI sequences. Three models (models 1-3) were developed, incorporating CT, CT and PET, PET and MRI features, and Lasso regression was used in feature selection. The receiver operating characteristic (ROC) curve for PI diagnosis was visualized for each model, and the area under the curve (AUC) was calculated. The DeLong test was used to compare the different AUCs. A P value < 0.05 was considered statistically significant. The AUC of models 1-3 was 0.762, 0.829, and 0.915, respectively. The DeLong test showed a statistically significant difference between the AUCs of model 1 vs. model 3, while the differences between the AUCs of model 1 vs. model 2 (P=0.253) and model 2 vs. model 3 (P=0.075) were not statistically significant. 18 F-FDG PET/MRI might show high predictive value for lung adenocarcinoma smaller than 3cm with PI. 1 TECHNICAL EFFICACY: Stage 2.

P15.09.A Canny edge detection algorithm for quantitative differentiation between diffuse and circumscript glioma growth patterns on MRI

Abstract Background Lower grade gliomas show heterogenous appearance on T2-weighted MRI. Some tumors grow diffusely along axonal structures whereas others distort adjacent brain tissue through local mass effect. The diagnostic, therapeutic and prognostic implication of differential growth patterns on MRI remain unknown and are difficult to assess quantitatively. Material and Methods A web-based application allowing for image preprocessing and providing a comprehensive edge detection tool by means of quantifying tumor border delineation on T2-weighted images based on the canny edge detection algorithm was developed. A sigma value between 1 and 100 determined the threshold where tumor borders where not detected by the algorithm anymore, with 1 equating to the lowest threshold and thus detection of all edges contained in the image. Two experienced faculty members assigned sigma values to axial T2 images of a random sample of 20 WHO grade 2 astrocytomas, IDH-mutant and 1p/19q-non-codeleted. The sigma values were then compared with a binary, subjective rating by the same faculty staff according to the perceived predominant growth pattern (diffuse versus circumscript) of each glioma. Results When subjectively categorizing tumors binarily (diffuse versus circumscript), there was moderate interrater variability between observers (cohen’s kappa=0.6). Raters agreed in 16 of 20 cases, terming 7 gliomas unanimously diffuse and 9 gliomas circumscript. In 4 cases, the raters opinions diverged. The sigma values differed significantly between diffuse and circumscript tumors in both raters (rater 1, p=0.002; rater 2, p=0.018). For rater 1, the mean sigma difference between diffuse and circumscript tumors was 10.7 and 9.3 for rater 2. Conclusion Edge detection algorithms can be efficiently applied on MRI scans and are highly accurate in differentiating diffuse from circumscript gliomas. Objectification demands defining imaging criteria for diffuse and circumscript appearance of lower grade gliomas on MRI.