Bilateral focused ultrasound medial thalamotomies for trigeminal neuropathic pain: a randomized controlled study

OBJECTIVE

Medial thalamotomy has been shown to benefit patients with neuropathic pain, but widespread adoption of this procedure has been limited by reporting of clinical outcomes in studies without a control group. This study aimed to minimize confounders associated with medial thalamotomy for treating chronic pain by using modern MRI-guided stereotactic lesioning and a rigorous clinical design.

METHODS

This prospective, double-blinded, randomized controlled trial in 10 patients with trigeminal neuropathic pain used sham procedures as controls. Participants underwent assessments by a pain psychologist and pain management clinician, including use of the following measures: the Numeric Pain Rating Scale (NPRS); patient-reported outcome measures; and patient's impression of improvement at baseline, 1 day, 1 week, 1 month, and 3 months postprocedure. Patients in the treated group underwent bilateral focused ultrasound (FUS) medial thalamotomy targeting the central lateral nucleus. Patients in the control group underwent sham procedures with energy output disabled. The primary efficacy outcome measure was between-group differences in pain intensity (using the NPRS) at baseline and at 3 months postprocedure. Adverse events were measured for safety and included MRI analysis. Exploratory measures of connectivity and metabolism were analyzed using diffusion tensor imaging, functional MRI, and PET, respectively.

RESULTS

There were no serious complications from the FUS procedures. MRI confirmed bilateral medial thalamic ablations. There was no significant improvement in pain intensity from baseline to 3 months, either for patients undergoing FUS medial thalamotomy or for sham controls; and the between-group change in NPRS score as the primary efficacy outcome measure was not significantly different. Patient-reported outcome assessments demonstrated improvement (i.e., a decrease) only in pain interference with enjoyment of life at 3 months. There was a perception of benefit at 1 week, but only for patients treated with FUS and not for the sham cohort. Advanced neuroimaging showed that these medial thalamic lesions altered structural connectivity with the postcentral gyrus and demonstrated a trend toward hypometabolism in the insula and amygdala.

CONCLUSIONS

This randomized controlled trial of bilateral FUS medial thalamotomy did not reduce the intensity of trigeminal neuropathic pain, although it should be noted that the ability to estimate the magnitude of treatment effects is limited by the small cohort.

Patient-Specific 3D CT Images Reconstruction from 2D KV Images Via Vision Transformer-Based Deep-Learning

PURPOSE/OBJECTIVE(S)

In some proton therapy facilities, patient alignment relies on two 2D orthogonal kV images, taken at fixed, oblique angles, as no 3D on-the-bed-imaging is available. The visibility of the tumor in kV images is limited since the patient's 3D anatomy is projected onto a 2D plane, especially when the tumor is behind a high-density structure such as bone. This can lead to a large patient setup error. A solution to this problem is to reconstruct the 3D CT image from the kV images obtained in the treatment position.

MATERIALS/METHODS

An asymmetric autoencoder-like network built with vision-transformer blocks was developed. The data was collected from a head and neck patient: 2 orthogonal kV images (1024X1024 voxels), 1 3D CT with padding (512X512X512) acquired from the in-room CT-on-rails before kVs were taken and 2 digitally-reconstructed-radiograph (DRR) images (512X512) based on the CT. We resampled kV images every 8 voxels and DRR and CT every 4 voxels, thus formed a dataset consisting of 262,144 samples, in which the images had a dimension of 128 for each direction. The value of each voxel in CT was normalized to range 0-1 with a uniform shift of 1000 and a denominator of 4000. For kV and DRR, we ranked all voxels value in an ascending order and normalized the values of the first 80% voxels to range 0-0.8 and the rest to range 0.8-1, thus yielding a quasi-Gaussian distribution, which was favorable by the deep neural networks. We further cropped kV and DRR images with a self-supervised bitmap based on the voxels' gradients. In training, both kV and DRR were utilized, and the encoder was encouraged to learn the same feature maps for kV images and its corresponding DRR images with mean-absolute-error (MAE) as the similarity loss. Then the decoder would reconstruct the 3D CT image from the feature maps of the kV images with the CT-on-rails as ground-truth (gCT) and MAE as the reconstruction loss. In testing, only independent kV images were used. The full-size synthetic CT (sCT) was achieved by concatenating the sCTs generated by the model according to their spatial information. The image quality of the sCT was evaluated using MAE and per-voxel-absolute-CT-number-difference volume histogram (CDVH). The proposed network was implemented with PyTorch deep learning library and both distributed data parallel (DDP) and automatic mixed precision (AMP) were applied to saving memory and accelerating the training speed. We used the AdamW optimizer with β1 = 0.9 and β2 = 0.999 and a cosine annealing learning rate scheduler with an initial learning of 1e-7 and 20 warm-up epochs.

RESULTS

The model achieved a MAE of <40HU and the CDVH showed that <5% of the voxels had a per-voxel-absolute-CT-number-difference larger than 185HU. The profile of a typical gCT slice and its corresponding sCT slice exhibited a high agreement, indicating the high similarity between the gCT and sCT.

CONCLUSION

A patient-specific vision-transformer-based network was developed and shown to be accurate and efficient to reconstruct 3D CT images from kV images.

A Free, Open-Source Toolkit to Produce 3D Bolus in the Clinic

PURPOSE/OBJECTIVE(S)

Tissue-equivalent, tissue-approximating and tissue-replacing bolus materials have been in use for decades in radiotherapy. Most frequently these materials are applied to a patient's skin to bring the highest dose region towards the surface of the skin-which is the location of the target. These materials can be applied at the time of simulation and included in a planning CT scan, or can be added during the planning process and first physically applied at the time of treatment. One of the most widely adopted materials for bolus has been sheets of a commercially available proprietary synthetic gel, which is uniform in thickness, and has some ability to match the curvature of the patient's body. Recently investigators have worked to create boluses using 3D printing technology, including several commercially available offerings. We hypothesized that we could create a bespoke, 3D bolus solution, using a series of open-source and free software products.

MATERIALS/METHODS

For an anthropomorphic phantom, a radiation treatment plan representative of skin cancer treatment was designed, this included a superficial target. The DICOM CT and structure set were imported into 3D Slicer, which is a free, open-source software for visualization, processing, segmentation, and registration. Using 3D Slicer, the bolus structure was saved as an STL file. Meshmixer, a free software for working with triangle meshes, was used to complete a mold design, and the mold parts were then printed using a rigid filament on a 3D printer. The mold parts were glued together, and small spring clamps were used secure the walls to the shells to ensure mold integrity. The mold was then filled with a thinned and degassed silicone. After appropriate curing, demolding was completed by removing the clamps and separating the walls. After QA, the bolus was applied to the anthropomorphic phantom and CTs were taken to compare a commercial sheet bolus with the in-house 3D printed product.

RESULTS

The bolus made via the in-house 3D printing process fit even complicated patient geometries well, and had both an obvious visual/goodness of fit advantage over the commercial sheet bolus and a nuanced dosimetric improvement as the air gaps present in the commercial sheet bolus were not desirable nor reproducible. The overall in-house workflow was efficient, and clinically reasonable (an estimated time of 72 hours was presented to the physician team, but in testing less than 24 hours was needed from export to delivery of the finished product).

CONCLUSION

In this work we explored whether motivated groups and departments could produce dosimetrically accurate and clinically reasonable custom boluses for patients undergoing radiotherapy to a superficial area of the body, using a test case on an anthropomorphic phantom. We found that this was absolutely achievable and could be implemented with no funds spent on software or licenses. Provided that a 3D printer, filament and silicone are available, any thoughtful practice can join the bespoke-bolus-club.

Unique T-cell Sub-Population Shifts after SBPT and Nivolumab in Platinum Refractory HNC: Biomarker Correlates from ROR1771

PURPOSE/OBJECTIVE(S)

ROR1771 was a clinical trial investigating the use of stereotactic body proton radiotherapy (SBPT) and nivolumab in recurrent platinum refractory head and neck squamous cell carcinoma (HNSCC). The planned analysis of T-cell subpopulation and biomarker response is herein presented.

MATERIALS/METHODS

Patients with metastatic histologically confirmed HNSCC from any primary site received 2 cycles of nivolumab followed by SBPT to 1-2 selected target lesion(s) (hilar/lung: 8 of 12 patients), followed by maintenance nivolumab. Peripheral blood mononuclear cells were isolated pre-/post-treatment. Flow cytometry identified T-cell subpopulations. Single Cell 5' Gene Expression (GEX) and V(D)J T Cell Receptor libraries were prepared using Single Cell Immune Profiling. Seurat (v4.1.1) was used to identify cell type clusters, and differential expression post-filtration was evaluated using the Wilcoxon Rank Sum test.

RESULTS

A total of 12 patients were eligible for analysis, with one alive at time of analysis, 52 months from start of treatment. Median overall survival here was 12.5 months vs. 7.5-months on CheckMate 141. SBPT ranged from 35-50 Gy. Sequential changes in T-cell populations from baseline were noted with initiation of nivolumab, driving decrease in tumor-reactive (TTR; CD11ahighPD1+CD8+), central memory (TCM; CCR7+CD45RA-), and effector T-cells (TEF; CCR7-CD45RA-). TTR and TCM increased following SBPT, with greatest increase (3.5x TTR and 5.2x TCM) in the surviving patient. An average of 68 genes with significant differential expression between timepoints (p<0.0001) demonstrated RNA gene expression changes across all cell subtypes, including ribosomal (RPL and RPS) genes, ACTB, FTL, MALAT1, and others. This averaged 113 genes across all timepoints in the surviving patient, with peak following nivolumab induction. On T-cell receptor (TCR) analysis of this patient, the predominant clonotype diversity changed substantially following nivolumab. Following SBPT, clonotype diversity again changed to include a milieu seen neither at baseline nor with nivolumab alone. These TCRs persisted for approximately 2 weeks following SBPT before returning to resemble the nivolumab-induced TCR diversity alone, coinciding with disease recurrence.

CONCLUSION

ROR1771 demonstrated overall survival favorably comparable to CheckMate 141. Biomarker analysis of peripheral blood samples demonstrated significant shifts in T-cell subpopulations and underlying gene expression to nivolumab and then to SBPT administration. SBPT to a target lesion changed TCR clonotypes within the peripheral blood beyond those seen with nivolumab administration, with fading of these TCR clonotypes coinciding with recurrence. SBPT in combination with nivolumab may drive systemic immunologic change above that induced by nivolumab alone and warrants further investigation.

Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium

PURPOSE

While the T2-FLAIR mismatch sign is highly specific for isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted astrocytomas among lower-grade gliomas, its utility in WHO grade 4 gliomas is not well-studied. We derived the partial T2-FLAIR mismatch sign as an imaging biomarker for IDH mutation in WHO grade 4 gliomas.

METHODS

Preoperative MRI scans of adult WHO grade 4 glioma patients (n = 2165) from the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium were analyzed. Diagnostic performance of the partial T2-FLAIR mismatch sign was evaluated. Subset analyses were performed to assess associations of imaging markers with overall survival (OS).

RESULTS

One hundred twenty-one (5.6%) of 2165 grade 4 gliomas were IDH-mutant. Partial T2-FLAIR mismatch was present in 40 (1.8%) cases, 32 of which were IDH-mutant, yielding 26.4% sensitivity, 99.6% specificity, 80.0% positive predictive value, and 95.8% negative predictive value. Multivariate logistic regression demonstrated IDH mutation was significantly associated with partial T2-FLAIR mismatch (odds ratio [OR] 5.715, 95% CI [1.896, 17.221], p = 0.002), younger age (OR 0.911 [0.895, 0.927], p < 0.001), tumor centered in frontal lobe (OR 3.842, [2.361, 6.251], p < 0.001), absence of multicentricity (OR 0.173, [0.049, 0.612], p = 0.007), and presence of cystic (OR 6.596, [3.023, 14.391], p < 0.001) or non-enhancing solid components (OR 6.069, [3.371, 10.928], p < 0.001). Multivariate Cox analysis demonstrated cystic components (p = 0.024) and non-enhancing solid components (p = 0.003) were associated with longer OS, while older age (p < 0.001), frontal lobe center (p = 0.008), multifocality (p < 0.001), and multicentricity (p < 0.001) were associated with shorter OS.

CONCLUSION

Partial T2-FLAIR mismatch sign is highly specific for IDH mutation in WHO grade 4 gliomas.

Adult diffuse gliomas: What the neuroradiologist needs to know

Diffuse gliomas are the most common primary malignant brain tumors in adults. Advancements in the molecular profiling of diffuse gliomas in recent years have led to a far better understanding of their biology and clinical outcomes. The fifth edition of the World Health Organization Classification of Central Nervous System Tumors, published in 2021, incorporates this genomic information to a much greater degree than prior editions. It is important for radiologists to understand the new glioma classification system and the characteristic neuroimaging features associated with each entity. This review aims to provide an overview of the diffuse gliomas that can present in adults, with an emphasis on their molecular features and associated imaging findings.

Pediatric-type diffuse low-grade glioma with MYB/MYBL1 alteration: report of 2 cases

2016 World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) has shown how molecular features can impact the classification of brain tumors. The continued combination of molecular features with histopathology has led to distinguish tumors with similar histopathologic features but distinct clinical prognosis. The 2021 revised 5. edition of the WHO classification further includes molecular features for CNS tumor categorization including MYB/MYBL1 altered diffuse astrocytoma which is a newly recognized type of low-grade pediatric-type brain tumor. We discuss imaging features of two pediatric-type low-grade gliomas with MYB/MYBL1-mutation that encountered at our institution.

Best Practice Recommendations for Stroke Vascular Imaging During Iodinated Contrast Shortage

GE Healthcare© announced on April 19, 2022, that their main factory and distributor of iodinated contrast had experienced a temporary shutdown because of COVID-19 outbreak in Shanghai, China. This, along with other supply chain issues, led to a worldwide shortage of iodinated contrast agents, Omnipaque and Visipaque. Our Comprehensive Stroke Center was confronted with the cascading effect of this iodinated contrast material shortage. We took immediate steps to revise our protocols and processes to continue to provide high-quality care to our stroke patients. A multidisciplinary working group comprised of representatives of our stroke center, including vascular neurology, diagnostic neuroradiology, and neurovascular surgery, urgently met to brainstorm how to mitigate the shortage. We established parameters and local guidelines for the use of CT angiography, CT perfusion, and digital subtraction angiography for stroke patients. In this article, we propose "best practice" recommendations from a single Joint Commission approved Comprehensive Stroke Center that can be used as blueprint by other hospital systems when navigating potential future supply chain issues, to provide consistent high-quality stroke care.

Imaging-based stratification of adult gliomas prognosticates survival and correlates with the 2021 WHO classification

BACKGROUND

Because of the lack of global accessibility, delay, and cost-effectiveness of genetic testing, there is a clinical need for an imaging-based stratification of gliomas that can prognosticate survival and correlate with the 2021-WHO classification.

METHODS

In this retrospective study, adult primary glioma patients with pre-surgery/pre-treatment MRI brain images having T2, FLAIR, T1, T1 post-contrast, DWI sequences, and survival information were included in TCIA training-dataset (n = 275) and independent validation-dataset (n = 200). A flowchart for imaging-based stratification of adult gliomas(IBGS) was created in consensus by three authors to encompass all adult glioma types. Diagnostic features used were T2-FLAIR mismatch sign, central necrosis with peripheral enhancement, diffusion restriction, and continuous cortex sign. Roman numerals (I, II, and III) denote IBGS types. Two independent teams of three and two radiologists, blinded to genetic, histology, and survival information, manually read MRI into three types based on the flowchart. Overall survival-analysis was done using age-adjusted Cox-regression analysis, which provided both hazard-ratio (HR) and area-under-curve (AUC) for each stratification system(IBGS and 2021-WHO). The sensitivity and specificity of each IBSG type were analyzed with cross-table to identify the corresponding 2021-WHO genotype.

RESULTS

Imaging-based stratification was statistically significant in predicting survival in both datasets with good inter-observer agreement (age-adjusted Cox-regression, AUC > 0.5, k > 0.6, p < 0.001). IBGS type-I, type-II, and type-III gliomas had good specificity in identifying IDHmut 1p19q-codel oligodendroglioma (training - 97%, validation - 85%); IDHmut 1p19q non-codel astrocytoma (training - 80%, validation - 85.9%); and IDHwt glioblastoma (training - 76.5%, validation- 87.3%) respectively (p-value < 0.01).

CONCLUSIONS

Imaging-based stratification of adult diffuse gliomas predicted patient survival and correlated well with 2021-WHO glioma classification.

The landscape of brain tumor mimics in neuro-oncology practice

BACKGROUND AND OBJECTIVE

Differentiating neoplastic and non-neoplastic brain lesions is essential to make management recommendations and convey prognosis, but the distinction between brain tumors and their mimics in practice may prove challenging. The aim of this study is to provide the incidence of brain tumor mimics in the neuro-oncology setting and describe this patient subset.

METHODS

Retrospective study of adult patients referred to the Division of Neuro-oncology for a presumed diagnosis of brain tumor from January 1, 2005 through December 31, 2017, who later satisfied the diagnosis of a non-neoplastic entity based on neuroimaging, clinical course, and/or histopathology evaluation. We classified tumor mimic entities according to clinical, radiologic, and laboratory characteristics that correlated with the diagnosis.

RESULTS

The incidence of brain tumor mimics was 3.4% (132/3897). The etiologies of the non-neoplastic entities were vascular (35%), inflammatory non-demyelinating (26%), demyelinating (15%), cysts (10%), infectious (9%), and miscellaneous (5%). In our study, 38% of patients underwent biopsy to determine diagnosis, but in 26%, the biopsy was inconclusive.

DISCUSSION

Brain tumor mimics represent a small but important subset of the neuro-oncology referrals. Vascular, inflammatory, and demyelinating etiologies represent two-thirds of cases. Recognizing the clinical, radiologic and laboratory characteristics of such entities may improve resource utilization and prevent unnecessary as well as potentially harmful diagnostic and therapeutic interventions.

Detectable Post-operative Circulating Tumor Human Papillomavirus (HPV) DNA And Association with Recurrence in Patients with HPV-Associated Oropharyngeal Squamous Cell Carcinoma

PURPOSE

  To determine the rate of detectability of ctHPVDNA after surgery but before adjuvant therapy in patients with HPV-associated oropharyngeal squamous cell carcinoma (HPV(+)OPSCC) and to investigate whether detectable ctHPVDNA at this time point may be associated with risk of recurrence.

METHODS AND MATERIALS

 Prospectively collected samples from patients with OPSCC were examined in a blinded fashion using a multi-analyte PCR assay. 45 samples were collected from HPV(+)OPSCC patients pre-op (prior to any treatment), and 159 samples post-op (before or at the start of adjuvant RT). Samples were identified via the radiation oncology biobank or via participation in a clinical trial. RT consisted of 60 Gy +/- cisplatin or de-escalation (30 Gy to 36 Gy in 20 b.i.d. fractions + docetaxel). 32 patients had paired samples available pre and post-op for the primary analysis. Additional exploratory analyses including associations of patient and tumor characteristics with recurrence were assessed using Cox proportional hazards models for all 159 post-op samples.. Detectability of ctHPVDNA was compared across groups utilizing logistic regression. Estimates of recurrence free survival (RFS) were made using Kaplan-Meier (KM).

RESULTS

In a paired analysis of 32 pre and post-op timepoints, 94% of patients had detectable ctHPVDNA pre-op and 41% post-op. RFS at 18 months was 83% (95% CI: 47-95%) for patients with detectable post-op ctHPVDNA compared to 100% for patients with undetectable post-op ctHPVDNA (p=.094).In an exploratory analysis of non-paired post-op samples, ctHPVDNA was detectable in 26% (41 of 159) of patients (median of 22 days post-op). Age (1.06, p=0.025), LVSI (OR 3.17, p=0.011) and ENE (OR=5.67, p=0.001) were associated with detectable ctHPVDNA after surgery. Detectable post-op ctHPVDNA was significantly associated with RFS (p<0.001).

CONCLUSION

Amongst patients with detectable pre-op ctHPVDNA, a significant proportion have detectable post-op ctHPVDNA in paired post-op samples, collected prior to the initiation of adjuvant radiation therapy. Future prospective study is warranted to investigate the association of detectable post-op ctHPVDNA with recurrence, including in comparison to established clinical and pathologic risk factors.

Intracranial meningioma surveillance using volumetrics from T2-weighted MRI

BACKGROUND AND PURPOSE

The gold standard for imaging of meningiomas is MRI with gadolinium-based contrast agent. Due to increased costs, time, and uncertain chronic effects of gadolinium exposure, use of noncontrast T2-weighted imaging (T2WI) in lieu of contrast-enhanced MRI has been an increasing focus of research across various diagnostic scenarios. The purpose of this study was to evaluate the diagnostic accuracy of T2WI in detecting changes in meningioma tumor volume.

METHODS

Imaging and clinical data were reviewed for 82 consecutive patients undergoing MR-surveillance of intracranial meningioma. Using volumetric-T2WI, two neuroradiologists independently calculated tumor volumes. Measurements were compared to a baseline study contrast-enhanced T1 tumor volume. Using contrast-enhanced sequences as the reference standard, statistical analysis was performed to determine the accuracy of T2WI in detecting changes of meningioma volume.

RESULTS

Using only T2WI, readers detected meningioma volume change ≥ 20% in 19/82 patients and volume change <20% in 63/82 patients. Reader accuracy for detecting change in tumor volume on T2WI ≥ 20% was 0.85, sensitivity 0.65, specificity 0.93, positive predictive value (PPV) 0.79, and negative predictive value (NPV) 0.87. For meningiomas >1 ml, reader accuracy for detecting change in tumor volume on T2WI ≥20% was 0.90, sensitivity 0.78, specificity 0.95, PPV 0.88, and NPV 0.91. Change in tumor volume on T2WI ≥20% was detected with 100% accuracy for posterior fossa meningiomas. Inter-reader agreement for all meningiomas was moderate (κ = 0.45) improving to substantial agreement (κ = 0.77) with tumor volumes >1 ml.

CONCLUSION

Volumetric-T2WI detects changes in meningioma volume with comparable accuracy to gold standard T1 postcontrast imaging, particularly with higher tumor volumes and posterior fossa locations.

Encephalopathy at admission predicts adverse outcomes in patients with SARS-CoV-2 infection

Aims

To determine if neurologic symptoms at admission can predict adverse outcomes in patients with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2).

Methods

Electronic medical records of 1053 consecutively hospitalized patients with laboratory‐confirmed infection of SARS‐CoV‐2 from one large medical center in the USA were retrospectively analyzed. Univariable and multivariable Cox regression analyses were performed with the calculation of areas under the curve (AUC) and concordance index (C‐index). Patients were stratified into subgroups based on the presence of encephalopathy and its severity using survival statistics. In sensitivity analyses, patients with mild/moderate and severe encephalopathy (defined as coma) were separately considered.

Results

Of 1053 patients (mean age 52.4 years, 48.0% men [n = 505]), 35.1% (n = 370) had neurologic manifestations at admission, including 10.3% (n = 108) with encephalopathy. Encephalopathy was an independent predictor for death (hazard ratio [HR] 2.617, 95% confidence interval [CI] 1.481–4.625) in multivariable Cox regression. The addition of encephalopathy to multivariable models comprising other predictors for adverse outcomes increased AUCs (mortality: 0.84–0.86, ventilation/ intensive care unit [ICU]: 0.76–0.78) and C‐index (mortality: 0.78 to 0.81, ventilation/ICU: 0.85–0.86). In sensitivity analyses, risk stratification survival curves for mortality and ventilation/ICU based on severe encephalopathy (n = 15) versus mild/moderate encephalopathy (n = 93) versus no encephalopathy (n = 945) at admission were discriminative (p < 0.001).

Conclusions

Encephalopathy at admission predicts later progression to death in SARS‐CoV‐2 infection, which may have important implications for risk stratification in clinical practice.

Evaluation of RAPNO criteria in medulloblastoma and other leptomeningeal seeding tumors using MRI and clinical data

BACKGROUND

Although the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working group has made recommendations for response assessment in patients with medulloblastoma (MBL) and leptomeningeal seeding tumors, these criteria have yet to be evaluated.

METHODS

We examined MR imaging and clinical data in a multicenter retrospective cohort of 269 patients with MBL diagnoses, high grade glioma, embryonal tumor, germ cell tumor, or choroid plexus papilloma. Interobserver agreement, objective response (OR) rates, and progression-free survival (PFS) were calculated. Landmark analyses were performed for OR and progression status at 0.5, 1.0, and 1.5 years after treatment initiation. Cox proportional hazards models were used to determine the associations between OR and progression with overall survival (OS). Subgroup analyses based on tumor subgroup and treatment modality were performed.

RESULTS

The median follow-up time was 4.0 years. In all patients, the OR rate was .0.565 (95% CI: 0.505-0.625) by RAPNO. The interobserver agreement of OR determination between 2 raters (a neuroradiologist and a neuro-oncologist) for the RAPNO criteria in all patients was 83.8% (k statistic = 0.815; P < 0.001). At 0.5-, 1.0-, and 1.5-year landmarks, both OR status and PFS determined by RAPNO were predictive of OS (hazard ratios [HRs] for 1-year landmark: OR HR = 0.079, P < 0.001; PFS HR = 10.192, P < 0.001). In subgroup analysis, OR status and PFS were predictive of OS for all tumor subtypes and treatment modalities.

CONCLUSION

RAPNO criteria showed excellent consistency in the treatment response evaluation of MBL and other leptomeningeal seeding tumors. OR and PFS determined by RAPNO criteria correlated with OS.

"Real world" use of a highly reliable imaging sign: "T2-FLAIR mismatch" for identification of IDH mutant astrocytomas

AbstractThe T2-FLAIR (fluid attenuated inversion recovery) mismatch sign is an easily detectable imaging sign on routine clinical MRI studies that suggests diagnosis of isocitrate dehydrogenase (IDH)-mutant 1p/19q non-codeleted gliomas. Multiple independent studies show that the T2-FLAIR mismatch sign has near-perfect specificity, but low sensitivity for diagnosing IDH-mutant astrocytomas. Thus, the T2-FLAIR mismatch sign represents a non-invasive radiogenomic diagnostic finding with potential clinical impact. Recently, false positive cases have been reported, many related to variable application of the sign's imaging criteria and differences in image acquisition, as well as to differences in the included patient populations. Here we summarize the imaging criteria for the T2-FLAIR mismatch sign, review similarities and differences between the multiple validation studies, outline strategies to optimize its clinical use, and discuss potential opportunities to refine imaging criteria in order to maximize its impact in glioma diagnostics.

Imaging Mimics of Brain Tumors

Nonneoplastic entities may closely resemble the imaging findings of primary or metastatic intracranial neoplasia, posing diagnostic challenges for the referring provider and radiologist. Prospective identification of brain tumor mimics is an opportunity for the radiologist to add value to patient care by decreasing time to diagnosis and avoiding unnecessary surgical procedures and medical therapies, but requires familiarity with mimic entities and a high degree of suspicion on the part of the interpreting radiologist. This article provides a framework for the radiologist to identify "brain tumor mimics," highlighting imaging and laboratory pearls and pitfalls, and illustrating unique and frequently encountered lesions.

Fluid attenuation in non-contrast-enhancing tumor (nCET): an MRI Marker for Isocitrate Dehydrogenase (IDH) mutation in Glioblastoma

PURPOSE

The WHO 2016 update classifies glioblastomas (WHO grade IV) according to isocitrate dehydrogenase (IDH) gene mutation status. We aimed to determine MRI-based metrics for predicting IDH mutation in glioblastoma.

METHODS

This retrospective study included glioblastoma cases (n = 199) with known IDH mutation status and pre-operative MRI (T1WI, T2WI, FLAIR, contrast-enhanced T1W1 at minimum). Two neuroradiologists determined the following MRI metrics: (1) primary lobe of involvement (frontal or non-frontal); (2) presence/absence of contrast-enhancement; (3) presence/absence of necrosis; (4) presence/absence of fluid attenuation in the non-contrast-enhancing tumor (nCET); (5) maximum width of peritumoral edema (cm); (6) presence/absence of multifocal disease. Inter-reader agreement was determined. After resolving discordant measurements, multivariate association between consensus MRI metrics/patient age and IDH mutation status was determined.

RESULTS

Among 199 glioblastomas, 16 were IDH-mutant. Inter-reader agreement was calculated for contrast-enhancement (ĸ = 0.49 [- 0.11-1.00]), necrosis (ĸ = 0.55 [0.34-0.76]), fluid attenuation in nCET (ĸ = 0.83 [0.68-0.99]), multifocal disease (ĸ = 0.55 [0.39-0.70]), and primary lobe (ĸ = 0.85 [0.80-0.91]). Mean difference for peritumoral edema width between readers was 0.3 cm [0.2-0.5], p < 0.001. Multivariate analysis uncovered significant associations between IDH-mutation and fluid attenuation in nCET (OR 82.9 [19.22, ∞], p < 0.001), younger age (OR 0.93 [0.86, 0.98], p = 0.009), frontal lobe location (OR 11.08 [1.14, 352.97], p = 0.037), and less peritumoral edema (OR 0.15 [0, 0.65], p = 0.044).

CONCLUSIONS

Conventional MRI metrics and patient age predict IDH-mutation status in glioblastoma. Among MRI markers, fluid attenuation in nCET represents a novel marker with high inter-reader agreement that is strongly associated with Glioblastoma, IDH-mutant.

3D fast low-angle shot (FLASH) technique for 3T contrast-enhanced brain MRI in the inpatient and emergency setting: comparison with 3D magnetization-prepared rapid gradient echo (MPRAGE) technique

PURPOSE

To retrospectively evaluate the diagnostic performance of a 1-min contrast-enhanced 3D-FLASH pulse sequence for detecting intracranial enhancing lesions compared to standard contrast-enhanced 3D-MPRAGE pulse sequence.

METHODS

Contrast-enhanced 3D-FLASH (acquisition time 49 s) and contrast-enhanced 3D-MPRAGE (4 min 35 s) pulse sequences were performed consecutively in 110 inpatient/emergency department 3T MRI brain examinations and analyzed by two independent neuroradiologist readers. For each sequence, the readers recorded (1) number of enhancing intracranial lesions; (2) intracranial susceptibility artifact (presence or absence; mm depth of intracranial signal loss); and (3) motion artifact (none, mild, moderate, severe). Inter and intra-reader agreement and reader accuracy relative to a reference standard were determined, and sequence comparison with respect to susceptibility and motion artifacts was performed.

RESULTS

There was substantial intra-reader, inter-sequence agreement [reader 1, κ = 0.70 (95% CI: [0.60, 0.81]); reader 2, κ = 0.70 (95% CI: [0.59, 0.82])] and substantial intra-sequence, inter-reader agreement [3D-MPRAGE assessment, κ = 0.76 (95% CI: [0.66, 0.86]); 3D-FLASH assessment, κ = 0.86 (95% CI: [0.77, 0.94]) for detection of intracranial enhancing lesions. For both readers, the diagnostic accuracy of 3D-FLASH and 3D-MPRAGE was similar (3D-MPRAGE: 86.4 and 88.1%; 3D-FLASH: 88.2 and 84.5%), with no inter-sequence diagnostic accuracy discordancy between the sequences for either reader. 3D-FLASH was associated with less susceptibility artifact (p < 0.001 both readers) and less motion artifact (p < 0.001 both readers).

CONCLUSION

On 3T brain MRI in the inpatient and emergency department setting, 1-min 3D-FLASH pulse sequence achieved comparable diagnostic performance to 4.5 min 3D-MPRAGE pulse sequence for detecting enhancing intracranial lesions, with reduced susceptibility and motion artifacts.

Extracting diffusion tensor fractional anisotropy and mean diffusivity from 3-direction DWI scans using deep learning

PURPOSE

To develop and evaluate machine-learning methods that reconstruct fractional anisotropy (FA) values and mean diffusivities (MD) from 3-direction diffusion MRI (dMRI) acquisitions.

METHODS

Two machine-learning models were implemented to map undersampled dMRI signals with high-quality FA and MD maps that were reconstructed from fully sampled DTI scans. The first model was a previously described multilayer perceptron (MLP), which maps signals and FA/MD values from a single voxel. The second was a convolutional neural network U-Net model, which maps dMRI slices to full FA/MD maps. Each method was trained on dMRI brain scans (N = 46), and reconstruction accuracies were compared with conventional linear-least-squares (LLS) reconstructions.

RESULTS

In an independent testing cohort (N = 20), 3-direction U-Net reconstructions had significantly lower absolute FA error than both 3-direction MLP (U-Net_3-dir : 0.06 ± 0.01 vs. MLP_3-dir : 0.08 ± 0.01, P < 1 × 10^-5 ) and 6-direction LLS (LLS_6-dir : 0.09 ± 0.03, P = 1 × 10^-5 ). The MD errors were not significantly different among 3-direction MLP (0.06 ± 0.01 × 10^-3 mm² /s), 3-direction U-Net (0.06 ± 0.01 × 10^-3 mm² /s), and 6-direction LLS (0.07 ± 0.02 × 10^-3 mm² /s, P > .1).

CONCLUSION

The proposed U-Net model reconstructed FA from 3-direction dMRI scans with improved accuracy compared with both a previously described MLP approach and LLS fitting from 6-direction scans. The MD reconstruction accuracies did not differ significantly between reconstructions.

Prognostic Value of Preoperative MRI Metrics for Diffuse Lower-Grade Glioma Molecular Subtypes

BACKGROUND AND PURPOSE

Despite the improved prognostic relevance of the 2016 WHO molecular-based classification of lower-grade gliomas, variability in clinical outcome persists within existing molecular subtypes. Our aim was to determine prognostically significant metrics on preoperative MR imaging for lower-grade gliomas within currently defined molecular categories.

MATERIALS AND METHODS

We undertook a retrospective analysis of 306 patients with lower-grade gliomas accrued from an institutional data base and The Cancer Genome Atlas. Two neuroradiologists in consensus analyzed preoperative MRIs of each lower-grade glioma to determine the following: tumor size, tumor location, number of involved lobes, corpus callosum involvement, hydrocephalus, midline shift, eloquent cortex involvement, ependymal extension, margins, contrast enhancement, and necrosis. Adjusted hazard ratios determined the association between MR imaging metrics and overall survival per molecular subtype, after adjustment for patient age, patient sex, World Health Organization grade, and surgical resection status.

RESULTS

For isocitrate dehydrogenase (IDH) wild-type lower-grade gliomas, tumor size (hazard ratio, 3.82; 95% CI, 1.94-7.75; P < .001), number of involved lobes (hazard ratio, 1.70; 95% CI, 1.28-2.27; P < .001), hydrocephalus (hazard ratio, 4.43; 95% CI, 1.12-17.54; P = .034), midline shift (hazard ratio, 1.16; 95% CI, 1.03-1.30; P = .013), margins (P = .031), and contrast enhancement (hazard ratio, 0.34; 95% CI, 0.13-0.90; P = .030) were associated with overall survival. For IDH-mutant 1p/19q-codeleted lower-grade gliomas, tumor size (hazard ratio, 2.85; 95% CI, 1.06-7.70; P = .039) and ependymal extension (hazard ratio, 6.34; 95% CI, 1.07-37.59; P = .042) were associated with overall survival.

CONCLUSIONS

MR imaging metrics offers prognostic information for patients with lower-grade gliomas within molecularly defined classes, with the greatest prognostic value for IDH wild-type lower-grade gliomas.

Brain Tumor Segmentation Using an Ensemble of 3D U-Nets and Overall Survival Prediction Using Radiomic Features

Accurate segmentation of different sub-regions of gliomas such as peritumoral edema, necrotic core, enhancing, and non-enhancing tumor core from multimodal MRI scans has important clinical relevance in diagnosis, prognosis and treatment of brain tumors. However, due to the highly heterogeneous appearance and shape of these tumors, segmentation of the sub-regions is challenging. Recent developments using deep learning models has proved its effectiveness in various semantic and medical image segmentation tasks, many of which are based on the U-Net network structure with symmetric encoding and decoding paths for end-to-end segmentation due to its high efficiency and good performance. In brain tumor segmentation, the 3D nature of multimodal MRI poses challenges such as memory and computation limitations and class imbalance when directly adopting the U-Net structure. In this study we aim to develop a deep learning model using a 3D U-Net with adaptations in the training and testing strategies, network structures, and model parameters for brain tumor segmentation. Furthermore, instead of picking one best model, an ensemble of multiple models trained with different hyper-parameters are used to reduce random errors from each model and yield improved performance. Preliminary results demonstrate the effectiveness of this method and achieved the 9th place in the very competitive 2018 Multimodal Brain Tumor Segmentation (BraTS) challenge. In addition, to emphasize the clinical value of the developed segmentation method, a linear model based on the radiomics features extracted from segmentation and other clinical features are developed to predict patient overall survival. Evaluation of these innovations shows high prediction accuracy in both low-grade glioma and glioblastoma patients, which achieved the 1st place in the 2018 BraTS challenge.

Anatomic and Thermometric Analysis of Cranial Nerve Palsy after Laser Amygdalohippocampotomy for Mesial Temporal Lobe Epilepsy

BACKGROUND

Laser interstitial thermal therapy (LITT) is a minimally invasive therapy for treating medication-resistant mesial temporal lobe epilepsy. Cranial nerve (CN) palsy has been reported as a procedural complication, but the mechanism of this complication is not understood.

OBJECTIVE

To identify the cause of postoperative CN palsy after LITT.

METHODS

Four medial temporal lobe epilepsy patients with CN palsy after LITT were identified for comparison with 22 consecutive patients with no palsy. We evaluated individual variation in the distance between CN III and the uncus, and CN IV and the parahippocampal gyrus using preoperative T1- and T2-weighted magnetic resonance (MR) images. Intraoperative MR thermometry was used to estimate temperature changes.

RESULTS

CN III (n = 2) and CN IV palsies (n = 2) were reported. On preoperative imaging, the majority of identified CN III (54%) and CN IV (43%) were located within 1 to 2 mm of the uncus and parahippocampal gyrus tissue border, respectively. Affected CN III and CN IV were more likely to be found &lt; 1 mm of the tissue border (PCNIII = .03, PCNIV &lt; .01; chi-squared test). Retrospective assessment of thermal profile during ablation showed higher temperature rise along the mesial temporal lobe tissue border in affected CNs than unaffected CNs after controlling for distance (12.9°C vs 5.8°C; P = .03; 2-sample t-test).

CONCLUSION

CN palsy after LITT likely results from direct heating of the respective CN running at extreme proximity to the mesial temporal lobe. Low-temperature thresholds set at the border of the mesial temporal lobe in patients whose CNs are at close proximity may reduce this risk.

Molecular Subtype Classification in Lower-Grade Glioma with Accelerated DTI

BACKGROUND AND PURPOSE

Image-based classification of lower-grade glioma molecular subtypes has substantial prognostic value. Diffusion tensor imaging has shown promise in lower-grade glioma subtyping but currently requires lengthy, nonstandard acquisitions. Our goal was to investigate lower-grade glioma classification using a machine learning technique that estimates fractional anisotropy from accelerated diffusion MR imaging scans containing only 3 diffusion-encoding directions.

MATERIALS AND METHODS

Patients with lower-grade gliomas (n = 41) (World Health Organization grades II and III) with known isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status were imaged preoperatively with DTI. Whole-tumor volumes were autodelineated using conventional anatomic MR imaging sequences. In addition to conventional ADC and fractional anisotropy reconstructions, fractional anisotropy estimates were computed from 3-direction DTI subsets using DiffNet, a neural network that directly computes fractional anisotropy from raw DTI data. Differences in whole-tumor ADC, fractional anisotropy, and estimated fractional anisotropy were assessed between IDH-wild-type and IDH-mutant lower-grade gliomas with and without 1p/19q codeletion. Multivariate classification models were developed using whole-tumor histogram and texture features from ADC, ADC + fractional anisotropy, and ADC + estimated fractional anisotropy to identify the added value provided by fractional anisotropy and estimated fractional anisotropy.

RESULTS

ADC (P = .008), fractional anisotropy (P < .001), and estimated fractional anisotropy (P < .001) significantly differed between IDH-wild-type and IDH-mutant lower-grade gliomas. ADC (P < .001) significantly differed between IDH-mutant gliomas with and without codeletion. ADC-only multivariate classification predicted IDH mutation status with an area under the curve of 0.81 and codeletion status with an area under the curve of 0.83. Performance improved to area under the curve = 0.90/0.94 for the ADC + fractional anisotropy classification and to area under the curve = 0.89/0.89 for the ADC + estimated fractional anisotropy classification.

CONCLUSIONS

Fractional anisotropy estimates made from accelerated 3-direction DTI scans add value in classifying lower-grade glioma molecular status.

Tumor pharmacokinetics and pharmacodynamics of the CDK4/6 inhibitor ribociclib in patients with recurrent glioblastoma

INTRODUCTION

We conducted a phase Ib study (NCT02345824) to determine whether ribociclib, an inhibitor of cyclin-dependent kinases 4 and 6 (CDK4/6), penetrates tumor tissue and modulates downstream signaling pathways including retinoblastoma protein (Rb) in patients with recurrent glioblastoma (GBM).

METHODS

Study participants received ribociclib (600 mg QD) for 8-21 days before surgical resection of their recurrent GBM. Total and unbound concentrations of ribociclib were measured in samples of tumor tissue, plasma, and cerebrospinal fluid (CSF). We analyzed tumor specimens obtained from the first (initial/pre-study) and second (recurrent/on-study) surgery by immunohistochemistry for Rb status and downstream signaling of CDK4/6 inhibition. Participants with Rb-positive recurrent tumors continued ribociclib treatment on a 21-day-on, 7-day-off schedule after surgery, and were monitored for toxicity and disease progression.

RESULTS

Three participants with recurrent Rb-positive GBM participated in this study. Mean unbound (pharmacologically active) ribociclib concentrations in plasma, CSF, MRI-enhancing, MRI-non-enhancing, and tumor core regions were 0.337 μM, 0.632 μM, 1.242 nmol/g, 0.484 nmol/g, and 1.526 nmol/g, respectively, which exceeded the in vitro IC₅₀ (0.04 μM) for inhibition of CDK4/6 in cell-free assay. Modulation of pharmacodynamic markers of ribociclib CDK 4/6 inhibition in tumor tissues were inconsistent between study participants. No participants experienced serious adverse events, but all experienced early disease progression.

CONCLUSIONS

This study suggests that ribociclib penetrated recurrent GBM tissue at concentrations predicted to be therapeutically beneficial. Our study was unable to demonstrate tumor pharmacodynamic correlates of drug activity. Although well tolerated, ribociclib monotherapy seemed ineffective for the treatment of recurrent GBM.

Risk Factors for Perceptual-versus-Interpretative Errors in Diagnostic Neuroradiology

BACKGROUND AND PURPOSE

Diagnostic errors in radiology are classified as perception or interpretation errors. This study determined whether specific conditions differed when perception or interpretation errors occurred during neuroradiology image interpretation.

MATERIALS AND METHODS

In a sample of 254 clinical error cases in diagnostic neuroradiology, we classified errors as perception or interpretation errors, then characterized imaging technique, interpreting radiologist's experience, anatomic location of the abnormality, disease etiology, time of day, and day of the week. Interpretation and perception errors were compared with hours worked per shift, cases read per shift, average cases read per shift hour, and the order of case during the shift when the error occurred.

RESULTS

Perception and interpretation errors were 74.8% (n = 190) and 25.2% (n = 64) of errors, respectively. Logistic regression analyses showed that the odds of an interpretation error were 2 times greater (OR, 2.09; 95% CI, 1.05-4.15; P = .04) for neuroradiology attending physicians with ≤5 years of experience. Interpretation errors were more likely with MR imaging compared with CT (OR, 2.10; 95% CI, 1.09-4.01; P = .03). Infectious/inflammatory/autoimmune diseases were more frequently associated with interpretation errors (P = .04). Perception errors were associated with faster reading rates (6.01 versus 5.03 cases read per hour; P = .004) and occurred later during the shift (24th-versus-18th case; P = .04).

CONCLUSIONS

Among diagnostic neuroradiology error cases, interpretation-versus-perception errors are affected by the neuroradiologist's experience, technique, and the volume and rate of cases read. Recognition of these risk factors may help guide programs for error reduction in clinical neuroradiology services.

Extent of Surgical Resection in Lower-Grade Gliomas: Differential Impact Based on Molecular Subtype

BACKGROUND AND PURPOSE

Diffuse lower-grade gliomas are classified into prognostically meaningful molecular subtypes. We aimed to determine the impact of surgical resection on overall survival in lower-grade glioma molecular subtypes.

MATERIALS AND METHODS

For 172 patients with lower-grade gliomas (World Health Organization grade II or III), pre- and postsurgical glioma volumes were determined using a semiautomated segmentation software based on FLAIR or T2-weighted MR imaging sequences. The association of pre- and postsurgical glioma volume and the percentage of glioma resection with overall survival was determined for the entire cohort and separately for lower-grade glioma molecular subtypes based on isocitrate dehydrogenase (IDH) and 1p/19q status, after adjustment for age, sex, World Health Organization grade, chemotherapy administration, and radiation therapy administration.

RESULTS

For the entire cohort, postsurgical glioma volume (hazard ratio, 1.80; 95% CI, 1.18-2.75; P = .006) and the percentage of resection (hazard ratio, 3.22; 95% CI, 1.79-5.82; P < .001) were associated with overall survival. For IDH-mutant 1p/19q-codeleted oligodendrogliomas, the percentage of resection (hazard ratio, 6.69; 95% CI, 1.57-28.46; P = .01) was associated with overall survival. For IDH-mutant 1p/19q-noncodeleted astrocytomas, presurgical glioma volume (hazard ratio, 3.20; 95% CI, 1.22-8.39; P = .018), postsurgical glioma volume (hazard ratio, 2.33; 95% CI, 1.32-4.12; P = .004), and percentage of resection (hazard ratio, 4.34; 95% CI, 1.74-10.81; P = .002) were associated with overall survival. For IDH-wild-type lower-grade gliomas, pre-/postsurgical glioma volume and percentage of resection were not associated with overall survival.

CONCLUSIONS

The extent of surgical resection has a differential survival impact in patients with lower-grade gliomas based on their molecular subtype. IDH-mutant lower-grade gliomas benefit from a greater extent of surgical resection, with the strongest impact observed for IDH-mutant 1p/19q-noncodeleted astrocytomas.

Dynamic Contrast-Enhanced MRI to Differentiate Parotid Neoplasms Using Golden-Angle Radial Sparse Parallel Imaging

BACKGROUND AND PURPOSE

Conventional imaging frequently shows overlapping features between benign and malignant parotid neoplasms. We investigated dynamic contrast-enhanced MR imaging using golden-angle radial sparse parallel imaging in differentiating parotid neoplasms.

MATERIALS AND METHODS

For this retrospective study, 41 consecutive parotid neoplasms were imaged with dynamic contrast-enhanced MR imaging with golden-angle radial sparse parallel imaging using 1-mm in-plane resolution. The temporal resolution was 3.4 seconds for 78.2 seconds and 8.8 seconds for the remaining acquisition. Three readers retrospectively and independently created and classified time-intensity curves as follows: 1) continuous wash-in; 2) rapid wash-in, subsequent plateau; and 3) rapid wash-in with washout. Additionally, time-intensity curve-derived semiquantitative metrics normalized to the ipsilateral common carotid artery were recorded. Diagnostic performance for the prediction of neoplasm type and malignancy was assessed. Subset multivariate analysis (n = 32) combined semiquantitative time-intensity curve metrics with ADC values.

RESULTS

Independent time-intensity curve classification of the 41 neoplasms produced moderate-to-substantial interreader agreement (κ = 0.50-0.79). The time-intensity curve classification threshold of ≥2 predicted malignancy with a positive predictive value of 56.0%-66.7%, and a negative predictive value of 92.0%-100%. The time-intensity curve classification threshold of <2 predicted pleomorphic adenoma with a positive predictive value of 87.0%-95.0% and a negative predictive value of 76.0%-95.0%. For all readers, type 2 and 3 curves were associated with malignant neoplasms (P < .001), and type 1 curves, with pleomorphic adenomas (P < .001). Semiquantitative analysis for malignancy prediction yielded an area under the receiver operating characteristic curve of 0.85 (95% CI, 0.73-0.99). Combining time-to-maximum and ADC predicts pleomorphic adenoma better than either metric alone (P < .001).

CONCLUSIONS

Golden-angle radial sparse parallel MR imaging allows high spatial and temporal resolution permeability characterization of parotid neoplasms, with a high negative predictive value for malignancy prediction. Combining time-to-maximum and ADC improves pleomorphic adenoma prediction compared with either metric alone.

Are patients with oligodendroglioma at higher risk for radiation neurotoxicity?

2061

Background: Symptomatic radiation neurotoxicity (RN), manifesting on MRI as focal necrosis and/or T2 signal abnormality, is a dreaded complication of radiation therapy (RT). While RT is standard of care for anaplastic gliomas, the long-term benefit vs risk profile in low-grade gliomas is not well defined. Patients with oligodendroglioma carry a better overall survival than those with astrocytoma. Anecdotally, they are more prone to experience RN than astrocytomas, as suggested by Acharya et al in 2017. We hypothesized that, independent of grade, oligodendrogliomas have a higher incidence of RN as compared to astrocytomas. Methods: We reviewed the records of 628 patients with WHO grade II and III gliomas from our institution. Study population comprised 326 patients with: standard fractionated RT, pathology confirmation by a neuropathologist, and follow up of at least 2 years after diagnosis. RN was defined as either histologically confirmed by pathology or requiring intervention for clinically presumed RN (bevacizumab or high-dose steroids.) A separate category included patients with dramatic cognitive decline with increased T2 signal abnormality, in the absence or tumor progression. Results: There were 131 patients with oligodendroglioma, based upon 1p/19q co-deletion (105 cases) or histology in the absence of molecular testing (26 cases). The remaining 195 patients had astrocytoma with intact 1p/19q, isocitrate dehydrogenase (IDH) wild-type, or diagnosed histologically absent molecular testing. The incidence of RN were 18.3% and 8.2% for oligodendroglioma and astrocytoma, respectively (p = 0.0063). An additional four patients with oligodendroglioma and two with astrocytoma had significant cognitive deterioration with increased T2 signal abnormality, without tumor progression. Conclusions: The greater than two-fold increase in RN incidence for oligodendrogliomas is significant and suggests patients with oligodendrogliomas may be more at risk to develop RN. Therefore, in patients with oligodendroglioma, the consideration of fractionated RT needs to be weighed against the increased potential for RN. Analysis of baseline imaging and patient characteristics variables that correlate with development of RN are ongoing and will be presented at the meeting.

Neuroimaging-Based Classification Algorithm for Predicting 1p/19q-Codeletion Status in IDH-Mutant Lower Grade Gliomas

BACKGROUND AND PURPOSE

Isocitrate dehydrogenase (IDH)-mutant lower grade gliomas are classified as oligodendrogliomas or diffuse astrocytomas based on 1p/19q-codeletion status. We aimed to test and validate neuroradiologists' performances in predicting the codeletion status of IDH-mutant lower grade gliomas based on simple neuroimaging metrics.

MATERIALS AND METHODS

One hundred two IDH-mutant lower grade gliomas with preoperative MR imaging and known 1p/19q status from The Cancer Genome Atlas composed a training dataset. Two neuroradiologists in consensus analyzed the training dataset for various imaging features: tumor texture, margins, cortical infiltration, T2-FLAIR mismatch, tumor cyst, T2* susceptibility, hydrocephalus, midline shift, maximum dimension, primary lobe, necrosis, enhancement, edema, and gliomatosis. Statistical analysis of the training data produced a multivariate classification model for codeletion prediction based on a subset of MR imaging features and patient age. To validate the classification model, 2 different independent neuroradiologists analyzed a separate cohort of 106 institutional IDH-mutant lower grade gliomas.

RESULTS

Training dataset analysis produced a 2-step classification algorithm with 86.3% codeletion prediction accuracy, based on the following: 1) the presence of the T2-FLAIR mismatch sign, which was 100% predictive of noncodeleted lower grade gliomas, (n = 21); and 2) a logistic regression model based on texture, patient age, T2* susceptibility, primary lobe, and hydrocephalus. Independent validation of the classification algorithm rendered codeletion prediction accuracies of 81.1% and 79.2% in 2 independent readers. The metrics used in the algorithm were associated with moderate-substantial interreader agreement (κ = 0.56-0.79).

CONCLUSIONS

We have validated a classification algorithm based on simple, reproducible neuroimaging metrics and patient age that demonstrates a moderate prediction accuracy of 1p/19q-codeletion status among IDH-mutant lower grade gliomas.

Features of diffuse gliomas that are misdiagnosed on initial neuroimaging: a case control study

PURPOSE

The neuroimaging diagnosis of diffuse gliomas can be challenging owing to their variable clinical and radiologic presentation. The purpose of this study was to identify factors that are associated with imaging errors in the diagnosis of diffuse gliomas.

METHODS

A retrospective case-control analysis was undertaken. 18 misdiagnosed diffuse gliomas on initial neuroimaging (cases) and 108 accurately diagnosed diffuse gliomas on initial neuroimaging (controls) were collected. Clinical, pathological, and imaging metrics were tabulated for each patient. The tabulated metrics were compared between cases and controls to determine factors associated with misdiagnosis.

RESULTS

Cases of misdiagnosed diffuse glioma (vs controls) were more likely to undergo initial triage as a stroke workup [OR 14.429 (95% CI 4.345, 47.915), p < 0.0001], were less likely to enhance [OR 0.283 (95% CI 0.098, 0.812), p = 0.02], were smaller (mean diameter 4.4 vs 6.0 cm, p = 0.0008), produced less midline shift (median midline shift 0.0 vs 2.0 mm, p = 0.003), were less likely to demonstrate necrosis [OR 0.156 (95% CI 0.034-0.713), p = 0.008], and were less likely to have IV contrast administered on the initial MRI [OR 0.100 (95% CI 0.020, 0.494), p = 0.008].

CONCLUSION

Several clinical and radiologic metrics are associated with diffuse gliomas that are missed or misdiagnosed on the initial neuroimaging study. Knowledge of these associations may aid in avoiding misinterpretation and accurately diagnosing such cases in clinical practice.

Head and Neck MRI Findings in CHARGE Syndrome

Coloboma of the eye, Heart defects, Atresia of the choanae, Retardation of growth and/or development, Genital and/or urinary abnormalities, and Ear abnormalities and deafness (CHARGE) syndrome is a disorder with multiple congenital anomalies seen on imaging. A retrospective review of 10 patients with CHARGE syndrome who underwent MR imaging of the brain as part of a preoperative evaluation for cochlear implantation was conducted. Structural abnormalities of the entire MR imaging of the head were evaluated, including the auditory system, olfactory system, face, skull base, and central nervous system. The most frequent MR imaging findings included dysplasias of the semicircular canals and hypoplasia of the frontal lobe olfactory sulci. Less frequent findings included cleft lip/palate and coloboma. Our study uncovered new findings of a J-shaped sella, dorsal angulation of the clivus, and absent/atrophic parotid glands, not previously described in patients with CHARGE. Our results emphasize the utility of MR imaging in the diagnosis and management of patients with CHARGE syndrome.

T2-FLAIR Mismatch, an Imaging Biomarker for IDH and 1p/19q Status in Lower-grade Gliomas: A TCGA/TCIA Project

Purpose: Lower-grade gliomas (WHO grade II/III) have been classified into clinically relevant molecular subtypes based on IDH and 1p/19q mutation status. The purpose was to investigate whether T2/FLAIR MRI features could distinguish between lower-grade glioma molecular subtypes.Experimental Design: MRI scans from the TCGA/TCIA lower grade glioma database (n = 125) were evaluated by two independent neuroradiologists to assess (i) presence/absence of homogenous signal on T2WI; (ii) presence/absence of "T2-FLAIR mismatch" sign; (iii) sharp or indistinct lesion margins; and (iv) presence/absence of peritumoral edema. Metrics with moderate-substantial agreement underwent consensus review and were correlated with glioma molecular subtypes. Somatic mutation, DNA copy number, DNA methylation, gene expression, and protein array data from the TCGA lower-grade glioma database were analyzed for molecular-radiographic associations. A separate institutional cohort (n = 82) was analyzed to validate the T2-FLAIR mismatch sign.Results: Among TCGA/TCIA cases, interreader agreement was calculated for lesion homogeneity [κ = 0.234 (0.111-0.358)], T2-FLAIR mismatch sign [κ = 0.728 (0.538-0.918)], lesion margins [κ = 0.292 (0.135-0.449)], and peritumoral edema [κ = 0.173 (0.096-0.250)]. All 15 cases that were positive for the T2-FLAIR mismatch sign were IDH-mutant, 1p/19q non-codeleted tumors (P < 0.0001; PPV = 100%, NPV = 54%). Analysis of the validation cohort demonstrated substantial interreader agreement for the T2-FLAIR mismatch sign [κ = 0.747 (0.536-0.958)]; all 10 cases positive for the T2-FLAIR mismatch sign were IDH-mutant, 1p/19q non-codeleted tumors (P < 0.00001; PPV = 100%, NPV = 76%).Conclusions: Among lower-grade gliomas, T2-FLAIR mismatch sign represents a highly specific imaging biomarker for the IDH-mutant, 1p/19q non-codeleted molecular subtype. Clin Cancer Res; 23(20); 6078-85. ©2017 AACR.

Influence of clinical history on MRI interpretation of optic neuropathy

Background and purpose

Clinical history is known to influence interpretation of a wide range of radiologic examinations. We sought to evaluate the influence of the clinical history on MRI interpretation of optic neuropathy.

Materials and methods

107 consecutive orbital MRI scans were retrospectively reviewed by three neuroradiologists. The readers independently evaluated the coronal STIR sequence for optic nerve hyperintensity and/or atrophy (yes/no) and the coronal post-contrast T1WI for optic nerve enhancement (yes/no). Readers initially evaluated the cases blinded to the clinical history. Following a two week washout period, readers again evaluated the cases with the clinical history provided. Inter-reader and reader-clinical radiologist agreement was assessed using Cohen's simple kappa coefficient.

Results

Intra-reader agreement, without and with provision of clinical history, was 0.564–0.716 on STIR and 0.270–0.495 on post-contrast T1WI. Inter-reader agreement was overall fair-moderate. On post-contrast T1WI, inter-reader agreement was significantly higher when the clinical history was provided (p = 0.001). Reader-clinical radiologist agreement improved with provision of the clinical history to the readers on both the STIR and post-contrast T1WI sequences.

Conclusions

In the MRI assessment of optic neuropathy, only modest levels of inter-reader agreement were achieved, even after provision of clinical history. Provision of clinical history improved inter-reader agreement, especially when assessing for optic nerve enhancement. These findings confirm the subjective nature of orbital MRI interpretation in cases of optic neuropathy, and point to the importance of an accurate clinical history. Of note, the accuracy of orbital MRI in the context of optic neuropathy was not assessed, and would require further investigation.

Imaging appearance of the lateral rectus-superior rectus band in 100 consecutive patients without strabismus

BACKGROUND AND PURPOSE

The lateral rectus-superior rectus band is an orbital connective tissue structure that has been implicated in a form of strabismus termed sagging eye syndrome. Our purpose was to define the normal MR imaging and CT appearance of this band in patients without strabismus.

MATERIALS AND METHODS

Orbital MR imaging and CT examinations in 100 consecutive patients without strabismus were evaluated. Readers graded the visibility of the lateral rectus-superior rectus band on coronal T1WI, coronal STIR, and coronal CT images. Readers determined whether the band demonstrated superotemporal bowing or any discontinuities and whether a distinct lateral levator aponeurosis was seen. Reader agreement was assessed by κ coefficients. Association between imaging metrics and patient age/sex was calculated by using the Fisher exact test.

RESULTS

The lateral rectus-superior rectus band was visible in 95% of coronal T1WI, 68% of coronal STIR sequences, and 70% of coronal CT scans. Ninety-five percent of these bands were seen as a continuous, arc-like structure extending from the superior rectus/levator palpebrae muscle complex to the lateral rectus muscle; 24% demonstrated superotemporal bowing; and in 82% of orbits, a distinct lateral levator aponeurosis was visible. Increasing patient age was negatively associated with lateral rectus-superior rectus band visibility (P=.03), positively associated with lateral rectus-superior rectus band superotemporal bowing (P=.03), and positively associated with lateral levator aponeurosis visibility (P=.01).

CONCLUSIONS

The lateral rectus-superior rectus band is visible in most patients without strabismus on coronal T1WI. The age effect with respect to its visibility and superotemporal bowing could represent age-related connective tissue degeneration.