Bitemporal hemianopia typically results from compression of the optic chiasm by sellar, suprasellar, or chiasmal lesions. Most of the cases of bitemporal hemianopia are secondary to pituitary masses. Defects in the temporal half of the visual field that mimic those that are caused by such pituitary or chiasmal lesions are known as bitemporal “pseudohemianopia” and involve orbital pathology. Tilted disc syndrome is an eye anomaly that may result in bitemporal visual field deficits similar to those that are caused by extrinsic or intrinsic mass effect on the optic chiasm. We report an incidentally found tilted disc syndrome in a patient with a history of surgically treated high myopia and the symptoms of  bilateral, gradual vision loss.

Background

Spinal arachnoid webs are uncommon and difficult to diagnose, especially because causative intradural transverse bands of arachnoid tissue are radiographically occult. Left untreated, arachnoid webs may cause progressive, debilitating, and permanent neurological dysfunction. Conversely, more than 90% of patients may experience rapid neurological recovery after resection, even with a prolonged duration of presenting symptoms. Indirect imaging signs such as spinal cord indentation and compression with cerebrospinal fluid (CSF) flow alteration provide crucial diagnostic clues that are critical in guiding appropriate management of such patients.

Observations

The authors reported a patient with no significant medical history who presented with back pain, progressive lower extremity weakness, gait ataxia, and bowel and bladder incontinence. They discussed multimodality imaging for determining the presence of arachnoid webs, including magnetic resonance imaging, phase-contrast CSF flow study, computed tomography myelography, and intraoperative ultrasound. They also discussed the detailed anatomy of the spinal subarachnoid space and a plausible pathophysiological mechanism for dorsal arachnoid webs.

Lessons

The authors report on a patient who underwent comprehensive imaging evaluation detailing the arachnoid web and whose subsequent anatomical localization and surgical treatment resulted in a full neurological recovery.

BACKGROUND: Accurate detection and grading of atheromatous stenotic lesions within the cardiac, renal, and intracranial vasculature is imperative for early recognition of disease and guiding treatment strategies. PURPOSE: In this work, a stenotic lesion phantom was used to compare high resolution and normal resolution modes on the same CT scanner in terms of detection and size discrimination performance. MATERIALS AND METHODS: The phantom is comprised of three acrylic cylinders (each 15.0 cm in diameter and 1.3 cm thick) with a matching array of holes in each module. The outer two modules contain holes that are slightly larger than the corresponding hole in the central module to simulate stenotic narrowing in vasculature. The stack of modules was submerged in an iodine solution simulating contrast-enhanced stenotic lesions with a range of lumen diameters (1.32-10.08 mm) and stenosis severity (0%, 50%, 60%, 70%, and 80%). The phantom was imaged on the Canon Aquilion Precision high-resolution CT scanner in high-resolution (HR) mode (0.25 mm × 0.50 mm detector element size) and normal-resolution (NR) mode (0.50 mm × 0.50 mm) using 120 kV and two dose levels (14 and 21 mGy SSDE) with 30 repeat scans acquired for each combination. Filtered back-projection (FBP) and a hybrid-iterative reconstruction (AIDR) were used with the FC18 kernel, as well as a deep learning algorithm (AiCE) which is only available for HR. A non-prewhitening model observer with an eye filter was implemented to quantify performance for detection and size discrimination tasks in the axial plane. RESULTS: Detection performance improved with increasing diameter, dose, and for AIDR in comparison to FBP for a fixed resolution mode. Performance in the HR mode was generally higher than NR for the smaller lumen diameters (1-5 mm) with decreasing differences as the diameter increased. Performance in NR mode surpassed HR mode for lumen diameters greater than ∼4 mm and ∼5 mm for 14 mGy and 21 mGy, respectively. AiCE provided consistently higher detection performance compared with AIDR-FC18 (48% higher for a 6 mm lumen diameter). Discrimination performance increased with increasing nominal diameter, dose, and for larger differences in stenosis severity. When comparing discrimination performance in HR to NR modes, the largest relative differences occur at the smallest nominal diameters and smallest differences in stenosis severity. The AiCE reconstruction algorithm produced the highest overall discrimination performance values, and these were significantly higher than AIDR-FC18 for nominal diameters of 7.14 and 10.08 mm. CONCLUSIONS: HR mode outperforms NR for detection up to a specific diameter and the results improve with AiCE and for higher dose levels. For the task of size discrimination, HR mode consistently outperforms NR if AIDR-FC18 is used for dose levels of at least 21 mGy, and the results improve with AiCE and for the smallest differences in stenosis severity investigated (50% vs. 60%). High-resolution CT appears to be beneficial for detecting smaller simulated lumen diameters (<5 mm) and is generally advantageous for discrimination tasks related to stenotic lesions, which inherently contain information at higher frequencies, given the right reconstruction algorithm and dose level.

Objective  Super-high and ultra-high spatial resolution computed tomography (CT) imaging can be advantageous for detecting temporal bone pathology and guiding treatment strategies. Methods  Six temporal bone cadaveric specimens were used to evaluate the temporal bone microanatomic structures utilizing the following CT reconstruction modes: normal resolution (NR, 0.5-mm slice thickness, 512 ² matrix), high resolution (HR, 0.5-mm slice thickness, 1,024 ² matrix), super-high resolution (SHR, 0.25-mm slice thickness, 1,024 ² matrix), and ultra-high resolution (UHR, 0.25-mm slice thickness, 2,048 ² matrix). Noise and signal-to-noise ratio (SNR) for bone and air were measured at each reconstruction mode. Two observers assessed visualization of seven small anatomic structures using a 4-point scale at each reconstruction mode. Results  Noise was significantly higher and SNR significantly lower with increases in spatial resolution (NR, HR, and SHR). There was no statistical difference between SHR and UHR imaging with regard to noise and SNR. There was significantly improved visibility of all temporal bone osseous structures of interest with SHR and UHR imaging relative to NR imaging ( p  < 0.001) and most of the temporal bone osseous structures relative to HR imaging. There was no statistical difference in the subjective image quality between SHR and UHR imaging of the temporal bone ( p  ≥ 0.085). Conclusion  Super-high-resolution and ultra-high-resolution CT imaging results in significant improvement in image quality compared with normal-resolution and high-resolution CT imaging of the temporal bone. This preliminary study also demonstrates equivalency between super-high and ultra-high spatial resolution temporal bone CT imaging protocols for clinical use.

Purpose

The T2-FLAIR mismatch sign has shown promise in determining IDH mutant 1p/19q non-co-deleted gliomas with a high specificity and modest sensitivity. To develop a multi-parametric radiomic model using MRI to predict 1p/19q co-deletion status in patients with newly diagnosed IDH1 mutant glioma and to perform a comparative analysis to T2-FLAIR mismatch sign+.

Methods

In this retrospective study, patients with diagnosis of IDH1 mutant gliomas with known 1p/19q status who had preoperative MRI were included. T2-FLAIR mismatch was evaluated independently by two board-certified neuroradiologists. Texture features were extracted from glioma segmentation of FLAIR images. eXtremeGradient Boosting (XGboost) classifiers were used for model development. Leave-one-out-cross-validation (LOOCV) and external validation performances were reported for both the training and external validation sets.

Results

A total of 103 patients were included for model development and 18 patients for external testing validation. The diagnostic performance (sensitivity/specificity/accuracy) in the determination of the 1p/19q co-deletion status was 59%/83%/67% (training) and 62.5%/70.0%/66.3% (testing) for the T2-FLAIR mismatch sign. This was significantly improved (p = 0.04) using the radiomics model to 77.9%/82.8%/80.3% (training) and 87.5%/89.9%/88.8% (testing), respectively. The addition of radiomics as a computer-assisted tool resulted in significant (p = 0.02) improvement in the performance of the neuroradiologist with 13 additional corrected cases in comparison to just using the T2-FLAIR mismatch sign.

Conclusion

The proposed radiomic model provides much needed sensitivity to the highly specific T2-FLAIR mismatch sign in the determination of the 1p/19q non-co-deletion status and improves the overall diagnostic performance of neuroradiologists when used as an assistive tool.