Detection of small metastatic brain tumors: comparison of 3D contrast-enhanced whole-brain black-blood imaging and MP-RAGE imaging

Comparison between postcontrast thin-slice T1-weighted 2D spin echo and 3D T1-weighted SPACE sequences in the detection of brain metastases at 1.5 and 3 T

OBJECTIVES

Accurate detection of metastatic brain lesions (MBL) is critical due to advances in radiosurgery. We compared the results of three readers in detecting MBL using T1-weighted 2D spin echo (SE) and sampling perfection with application-optimized contrasts using different flip angle evolution (SPACE) sequences with whole-brain coverage at both 1.5 T and 3 T.

METHODS

Fifty-six patients evaluated for MBL were included and underwent a standard protocol (1.5 T, n = 37; 3 T, n = 19), including postcontrast T1-weighted SE and SPACE. The rating was performed by three raters in two sessions > six weeks apart. The true number of MBL was determined using all available imaging including follow-up. Intraclass correlations for intra-rater and inter-rater agreement were calculated. Signal intensity ratios (SIR; enhancing lesion, white matter) were determined on a subset of 46 MBL > 4 mm. A paired t-test was used to evaluate postcontrast sequence order and SIR. Reader accuracy was evaluated by the coefficient of determination.

RESULTS

A total of 135 MBL were identified (mean/subject 2.41, SD 6.4). The intra-rater agreement was excellent for all 3 raters (ICC = 0.97-0.992), as was the inter-rater agreement (ICC = 0.995 SE, 0.99 SPACE). Subjective qualitative ratings were lower for SE images; however, signal intensity ratios were higher in SE sequences. Accuracy was high in all readers for both SE (R2 0.95-0.96) and SPACE (R2 0.91-0.96) sequences.

CONCLUSIONS

Although SE sequences are superior to gradient echo sequences in the detection of small MBL, they have long acquisition times and frequent artifacts. We show that T1-weighted SPACE is not inferior to standard thin-slice SE sequences in the detection of MBL at both imaging fields.

CRITICAL RELEVANCE STATEMENT

Our results show the suitability of 3D T1-weighted turbo spin echo (TSE) sequences (SPACE, CUBE, VISTA) in the detection of brain metastases at both 1.5 T and 3 T.

KEY POINTS

• Accurate detection of brain metastases is critical due to advances in radiosurgery. • T1-weighted SE sequences are superior to gradient echo in detecting small metastases. • T1-weighted 3D-TSE sequences may achieve high resolution and relative insensitivity to artifacts. • T1-weighted 3D-TSE sequences have been recommended in imaging brain metastases at 3 T. • We found T1-weighted 3D-TSE equivalent to thin-slice SE at 1.5 T and 3 T.

Development of RLK-Unet: a clinically favorable deep learning algorithm for brain metastasis detection and treatment response assessment

Purpose/objectives

Previous deep learning (DL) algorithms for brain metastasis (BM) detection and segmentation have not been commonly used in clinics because they produce false-positive findings, require multiple sequences, and do not reflect physiological properties such as necrosis. The aim of this study was to develop a more clinically favorable DL algorithm (RLK-Unet) using a single sequence reflecting necrosis and apply it to automated treatment response assessment.

Methods and materials

A total of 128 patients with 1339 BMs, who underwent BM magnetic resonance imaging using the contrast-enhanced 3D T1 weighted (T1WI) turbo spin-echo black blood sequence, were included in the development of the DL algorithm. Fifty-eight patients with 629 BMs were assessed for treatment response. The detection sensitivity, precision, Dice similarity coefficient (DSC), and agreement of treatment response assessments between neuroradiologists and RLK-Unet were assessed.

Results

RLK-Unet demonstrated a sensitivity of 86.9% and a precision of 79.6% for BMs and had a DSC of 0.663. Segmentation performance was better in the subgroup with larger BMs (DSC, 0.843). The agreement in the response assessment for BMs between the radiologists and RLK-Unet was excellent (intraclass correlation, 0.84).

Conclusion

RLK-Unet yielded accurate detection and segmentation of BM and could assist clinicians in treatment response assessment.

Improved Brain Tumor Conspicuity at 3 T Using Dark Blood, Fat-Suppressed, Dixon Unbalanced T1 Relaxation-Enhanced Steady-State MRI

OBJECTIVES

Contrast-enhanced magnetic resonance imaging (MRI) is the cornerstone for brain tumor diagnosis and treatment planning. We have developed a novel dual-echo volumetric dark blood pulse sequence called Dixon unbalanced T1 relaxation-enhanced steady-state (uT 1 RESS) that improves the visibility of contrast-enhancing lesions while suppressing the tissue signals from blood vessels and fat. The purpose of this study was to test the hypothesis that Dixon uT 1 RESS would significantly improve the conspicuity of brain tumors compared with magnetization-prepared rapid gradient echo (MPRAGE), as well as to determine potential limitations of the technique.

MATERIALS AND METHODS

This retrospective study was approved by the hospital institutional review board. Forty-seven adult patients undergoing an MRI scan for a brain tumor indication were included. Contrast-enhanced MRI of the brain was performed at 3 T using both MPRAGE and Dixon uT 1 RESS. To control for any impact of contrast agent washout during the scan procedure, Dixon uT 1 RESS was acquired in approximately half the subjects immediately after MPRAGE, and in the other half immediately before MPRAGE. Image quality, artifacts, and lesion detection were scored by 3 readers, whereas lesion apparent signal-to-noise ratio and lesion-to-background Weber contrast were calculated from region-of-interest measurements.

RESULTS

Image quality was not rated significantly different between MPRAGE and Dixon uT 1 RESS, whereas motion artifacts were slightly worse with Dixon uT 1 RESS. Comparing Dixon uT 1 RESS with MPRAGE, the respective values for mean lesion apparent signal-to-noise ratio were not significantly different (199.31 ± 99.05 vs 203.81 ± 110.23). Compared with MPRAGE, Dixon uT 1 RESS significantly increased the tumor-to-brain contrast (1.60 ± 1.18 vs 0.61 ± 0.47 when Dixon uT1RESS was acquired before MPRAGE and 1.94 ± 0.97 vs 0.82 ± 0.55 when Dixon uT 1 RESS was acquired after MPRAGE). In patients with metastatic disease, Dixon uT 1 RESS detected at least 1 enhancing brain lesion that was missed by MPRAGE on average in 24.7% of patients, whereas Dixon uT 1 RESS did not miss any lesions that were demonstrated by MPRAGE. Dixon uT 1 RESS better detected vascular and dural invasion in a small number of patients.

CONCLUSIONS

In conclusion, brain tumors were significantly more conspicuous at 3 T using Dixon uT 1 RESS compared with MPRAGE, with an approximately 2.5-fold improvement in lesion-to-background contrast irrespective of sequence order. It outperformed MPRAGE for the detection of brain metastases, dural or vascular involvement. These results suggest that Dixon uT 1 RESS could prove to be a useful adjunct or alternative to existing neuroimaging techniques for the postcontrast evaluation of intracranial tumors.

Atypical clinical and novel radiological findings in Susac syndrome: Experience from a large monocentric cohort

Susac syndrome (SuS) is a rare immune-mediated endotheliopathy that affects the brain, retina and inner ear and is characterised by the variable clinical triad of encephalopathy, visual and vestibulocochlear dysfunction. Here, we present clinical and paraclinical data of 19 SuS patients followed at Ghent University Hospital and highlight some atypical clinical and novel radiological findings. Our findings suggest that spinal involvement expands the clinical phenotype of SuS. We further introduce dark blood sequences as a more sensitive technique to detect radiological disease activity in SuS. Our data add to the current understanding of the diagnosis, monitoring and treatment of SuS.

ISRS Technical Guidelines for Stereotactic Radiosurgery: Treatment of Small Brain Metastases (≤1 cm in Diameter)

PURPOSE

The objective of this literature review was to develop International Stereotactic Radiosurgery Society (ISRS) consensus technical guidelines for the treatment of small, ≤1 cm in maximal diameter, intracranial metastases with stereotactic radiosurgery. Although different stereotactic radiosurgery technologies are available, most of them have similar treatment workflows and common technical challenges that are described.

METHODS AND MATERIALS

A systematic review of the literature published between 2009 and 2020 was performed in Pubmed using the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) methodology. The search terms were limited to those related to radiosurgery of brain metastases and to publications in the English language.

RESULTS

From 484 collected abstract 37 articles were included into the detailed review and bibliographic analysis. An additional 44 papers were identified as relevant from a search of the references. The 81 papers, including additional 7 international guidelines, were deemed relevant to at least one of five areas that were considered paramount for this report. These areas of technical focus have been employed to structure these guidelines: imaging specifications, target volume delineation and localization practices, use of margins, treatment planning techniques, and patient positioning.

CONCLUSION

This systematic review has demonstrated that Stereotactic Radiosurgery (SRS) for small (1 cm) brain metastases can be safely performed on both Gamma Knife (GK) and CyberKnife (CK) as well as on modern LINACs, specifically tailored for radiosurgical procedures, However, considerable expertise and resources are required for a program based on the latest evidence for best practice.

Deep-Learning-Based Automatic Detection and Segmentation of Brain Metastases with Small Volume for Stereotactic Ablative Radiotherapy

Simple Summary

With advances in radiotherapy (RT) technique and more frequent use of stereotactic ablative radiotherapy (SABR), precise segmentation of all brain metastases (BM) including a small volume of BM is essential to choose an appropriate treatment modality. However, the process of detecting and manually delineating BM with small volumes often results in missing delineation and requires a great amount of labor. To address this issue, we present a useful deep learning (DL) model for the detection and segmentation of BMwith contrast-enhanced magnetic resonance images. Specifically, we applied effective training techniques to detect and segment a BM of less than 0.04 cc, which is relatively small compared to previous studies. The results of our DL model demonstrated that the proposed methods provide considerable benefit for BM, even small-volume BM, detection, and segmentation for SABR.

Abstract

Recently, several efforts have been made to develop the deep learning (DL) algorithms for automatic detection and segmentation of brain metastases (BM). In this study, we developed an advanced DL model to BM detection and segmentation, especially for small-volume BM. From the institutional cancer registry, contrast-enhanced magnetic resonance images of 65 patients and 603 BM were collected to train and evaluate our DL model. Of the 65 patients, 12 patients with 58 BM were assigned to test-set for performance evaluation. Ground-truth for BM was assigned to one radiation oncologist to manually delineate BM and another one to cross-check. Unlike other previous studies, our study dealt with relatively small BM, so the area occupied by the BM in the high-resolution images were small. Our study applied training techniques such as the overlapping patch technique and 2.5-dimensional (2.5D) training to the well-known U-Net architecture to learn better in smaller BM. As a DL architecture, 2D U-Net was utilized by 2.5D training. For better efficacy and accuracy of a two-dimensional U-Net, we applied effective preprocessing include 2.5D overlapping patch technique. The sensitivity and average false positive rate were measured as detection performance, and their values were 97% and 1.25 per patient, respectively. The dice coefficient with dilation and 95% Hausdorff distance were measured as segmentation performance, and their values were 75% and 2.057 mm, respectively. Our DL model can detect and segment BM with small volume with good performance. Our model provides considerable benefit for clinicians with automatic detection and segmentation of BM for stereotactic ablative radiotherapy.

From Dose Reduction to Contrast Maximization: Can Deep Learning Amplify the Impact of Contrast Media on Brain Magnetic Resonance Image Quality? A Reader Study

OBJECTIVES

The aim of this study was to evaluate a deep learning method designed to increase the contrast-to-noise ratio in contrast-enhanced gradient echo T1-weighted brain magnetic resonance imaging (MRI) acquisitions. The processed images are quantitatively evaluated in terms of lesion detection performance.

MATERIALS AND METHODS

A total of 250 multiparametric brain MRIs, acquired between November 2019 and March 2021 at Gustave Roussy Cancer Campus (Villejuif, France), were considered for inclusion in this retrospective monocentric study. Independent training (107 cases; age, 55 ± 14 years; 58 women) and test (79 cases; age, 59 ± 14 years; 41 women) samples were defined. Patients had glioma, brain metastasis, meningioma, or no enhancing lesion. Gradient echo and turbo spin echo with variable flip angles postcontrast T1 sequences were acquired in all cases. For the cases that formed the training sample, "low-dose" postcontrast gradient echo T1 images using 0.025 mmol/kg injections of contrast agent were also acquired. A deep neural network was trained to synthetically enhance the low-dose T1 acquisitions, taking standard-dose T1 MRI as reference. Once trained, the contrast enhancement network was used to process the test gradient echo T1 images. A read was then performed by 2 experienced neuroradiologists to evaluate the original and processed T1 MRI sequences in terms of contrast enhancement and lesion detection performance, taking the turbo spin echo sequences as reference.

RESULTS

The processed images were superior to the original gradient echo and reference turbo spin echo T1 sequences in terms of contrast-to-noise ratio (44.5 vs 9.1 and 16.8; P < 0.001), lesion-to-brain ratio (1.66 vs 1.31 and 1.44; P < 0.001), and contrast enhancement percentage (112.4% vs 85.6% and 92.2%; P < 0.001) for cases with enhancing lesions. The overall image quality of processed T1 was preferred by both readers (graded 3.4/4 on average vs 2.7/4; P < 0.001). Finally, the proposed processing improved the average sensitivity of gradient echo T1 MRI from 88% to 96% for lesions larger than 10 mm (P = 0.008), whereas no difference was found in terms of the false detection rate (0.02 per case in both cases; P > 0.99). The same effect was observed when considering all lesions larger than 5 mm: sensitivity increased from 70% to 85% (P < 0.001), whereas false detection rates remained similar (0.04 vs 0.06 per case; P = 0.48). With all lesions included regardless of their size, sensitivities were 59% and 75% for original and processed T1 images, respectively (P < 0.001), and the corresponding false detection rates were 0.05 and 0.14 per case, respectively (P = 0.06).

CONCLUSION

The proposed deep learning method successfully amplified the beneficial effects of contrast agent injection on gradient echo T1 image quality, contrast level, and lesion detection performance. In particular, the sensitivity of the MRI sequence was improved by up to 16%, whereas the false detection rate remained similar.

Comparison of contrast-enhanced T1-weighted imaging using DANTE-SPACE, PETRA, and MPRAGE: a clinical evaluation of brain tumors at 3 Tesla

Background

We aimed to compare the performance of three contrast-enhanced T1-weighted three-dimensional (3D) magnetic resonance (MR) sequences to detect brain tumors at 3 Tesla. The three sequences were: (I) delay alternating with nutation for tailored excitation sampling perfection with application-optimized contrasts using different flip angle evolution (DANTE-SPACE), (II) pointwise encoding time reduction with radial acquisition (PETRA), and (III) magnetization-prepared rapid acquisition with gradient echo (MPRAGE).

Methods

This study involved 77 consecutive patients, including 34 patients with known primary brain tumors and 43 patients suspected of intracranial metastases. All patients underwent each of the three sequences with comparable spatial resolution and acquisition time post-injection. Signal-to-noise ratios (SNRs) for gray matter (GM) and white matter (WM), contrast-to-noise ratios (CNRs) for lesion/GM, lesion/WM, and GM/WM were quantitatively compared. Two radiologists determined the total number of enhancing lesions by consensus. Intraclass correlation coefficients (ICCs) between the two radiologists for metastases presence, qualitative ratings for image quality, and acoustic noise level of each sequence were assessed.

Results

Among the three sequences, SNRs and CNRs between lesions and surrounding parenchyma were highest using DANTE-SPACE, but CNR_WM/GM was the lowest with DANTE-SPACE. SNRs for PETRA images were significantly higher than those for MPRAGE (P<0.001). CNRs between lesions and surrounding parenchyma were similar for PETRA and MPRAGE (P>0.05). Significantly more brain metastases were detected with DANTE-SPACE (n=94) compared with MPRAGE (n=71) and PETRA (n=72). The ICCs were 0.964 for MPRAGE, 0.975 for PETRA, and 0.973 for DANTE-SPACE. Qualitative scores for lesion imaging using DANTE-SPACE were significantly higher than those obtained with PETRA and MPRAGE (P=0.002 and P=0.004, respectively). The acoustic noise level for PETRA (64.45 dB) was significantly lower than that for MPRAGE (78.27 dB, P<0.01) and DANTE-SPACE (80.18 dB, P<0.01).

Conclusions

PETRA achieves comparable detection of brain tumors with MPRAGE and is preferred for depicting osseous metastases and meningeal enhancement. DANTE-SPACE with blood vessel suppression showed improved detection of cerebral metastases compared with MPRAGE and PETRA, which could be helpful for the differential diagnosis of tumors.

Brain metastases: An update on the multi-disciplinary approach of clinical management

IMPORTANCE

Brain metastasis (BM) is the most common malignant intracranial neoplasm in adults with over 100,000 new cases annually in the United States and outnumbering primary brain tumors 10:1.

OBSERVATIONS

The incidence of BM in adult cancer patients ranges from 10-40%, and is increasing with improved surveillance, effective systemic therapy, and an aging population. The overall prognosis of cancer patients is largely dependent on the presence or absence of brain metastasis, and therefore, a timely and accurate diagnosis is crucial for improving long-term outcomes, especially in the current era of significantly improved systemic therapy for many common cancers. BM should be suspected in any cancer patient who develops new neurological deficits or behavioral abnormalities. Gadolinium enhanced MRI is the preferred imaging technique and BM must be distinguished from other pathologies. Large, symptomatic lesion(s) in patients with good functional status are best treated with surgery and stereotactic radiosurgery (SRS). Due to neurocognitive side effects and improved overall survival of cancer patients, whole brain radiotherapy (WBRT) is reserved as salvage therapy for patients with multiple lesions or as palliation. Newer approaches including multi-lesion stereotactic surgery, targeted therapy, and immunotherapy are also being investigated to improve outcomes while preserving quality of life.

CONCLUSION

With the significant advancements in the systemic treatment for cancer patients, addressing BM effectively is critical for overall survival. In addition to patient's performance status, therapeutic approach should be based on the type of primary tumor and associated molecular profile as well as the size, number, and location of metastatic lesion(s).

Consensus recommendations for a standardized brain tumor imaging protocol for clinical trials in brain metastases

A recent meeting was held on March 22, 2019, among the FDA, clinical scientists, pharmaceutical and biotech companies, clinical trials cooperative groups, and patient advocacy groups to discuss challenges and potential solutions for increasing development of therapeutics for central nervous system metastases. A key issue identified at this meeting was the need for consistent tumor measurement for reliable tumor response assessment, including the first step of standardized image acquisition with an MRI protocol that could be implemented in multicenter studies aimed at testing new therapeutics. This document builds upon previous consensus recommendations for a standardized brain tumor imaging protocol (BTIP) in high-grade gliomas and defines a protocol for brain metastases (BTIP-BM) that addresses unique challenges associated with assessment of CNS metastases. The "minimum standard" recommended pulse sequences include: (i) parameter matched pre- and post-contrast inversion recovery (IR)-prepared, isotropic 3D T1-weighted gradient echo (IR-GRE); (ii) axial 2D T2-weighted turbo spin echo acquired after injection of gadolinium-based contrast agent and before post-contrast 3D T1-weighted images; (iii) axial 2D or 3D T2-weighted fluid attenuated inversion recovery; (iv) axial 2D, 3-directional diffusion-weighted images; and (v) post-contrast 2D T1-weighted spin echo images for increased lesion conspicuity. Recommended sequence parameters are provided for both 1.5T and 3T MR systems. An "ideal" protocol is also provided, which replaces IR-GRE with 3D TSE T1-weighted imaging pre- and post-gadolinium, and is best performed at 3T, for which dynamic susceptibility contrast perfusion is included. Recommended perfusion parameters are given.

Improvement of the Diagnostic Performance of Facial Neuritis Using Contrast-Enhanced 3D T1 Black-Blood Imaging: Comparison with Contrast-Enhanced 3D T1-Spoiled Gradient-Echo Imaging

This study aims to investigate the diagnostic ability of the contrast-enhanced 3D T1 black-blood fast spin-echo (T1 BB-FSE) sequence compared with the contrast-enhanced 3D T1-spoiled gradient-echo (CE-GRE) sequence in patients with facial neuritis. Forty-five patients with facial neuritis who underwent temporal bone MR imaging, including T1 BB-FSE and CE-GRE imaging, were examined. Two reviewers independently assessed the T1 BB-FSE and CE-GRE images in terms of diagnostic performance, and qualitative (diagnostic confidence and visual asymmetric enhancement) and quantitative analysis (contrast-enhancing lesion extent of the canalicular segment of the affected facial nerve (LEC) and the affected side-to-normal signal intensity ratio (rSI)). The AUCs of each reviewer, and the sensitivity and accuracy of T1 BB-FSE were significantly superior to those of CE-GRE (p < 0.05). Regarding diagnostic confidence and visual asymmetric enhancement, T1 BB-FSE tended to be rated greater than CE-GRE (p < 0.05). Additionally, in quantitative analysis, LEC and rSI of the canalicular segment on T1 BB-FSE were larger than those on CE-GRE (p < 0.05). The T1 BB-FSE sequence was significantly superior to the CE-GRE sequence, with more conspicuous lesion visualization in terms of both qualitative and quantitative aspects in patients with facial neuritis.

Robust performance of deep learning for automatic detection and segmentation of brain metastases using three-dimensional black-blood and three-dimensional gradient echo imaging

OBJECTIVES

To evaluate whether a deep learning (DL) model using both three-dimensional (3D) black-blood (BB) imaging and 3D gradient echo (GRE) imaging may improve the detection and segmentation performance of brain metastases compared to that using only 3D GRE imaging.

METHODS

A total of 188 patients with brain metastases (917 lesions) who underwent a brain metastasis MRI protocol including contrast-enhanced 3D BB and 3D GRE were included in the training set. DL models based on 3D U-net were constructed. The models were validated in the test set consisting of 45 patients with brain metastases (203 lesions) and 49 patients without brain metastases.

RESULTS

The combined 3D BB and 3D GRE model yielded better performance than the 3D GRE model (sensitivities of 93.1% vs 76.8%, p < 0.001), and this effect was significantly stronger in subgroups with small metastases (p interaction < 0.001). For metastases < 3 mm, ≥ 3 mm and < 10 mm, and ≥ 10 mm, the sensitivities were 82.4%, 93.2%, and 100%, respectively. The combined 3D BB and 3D GRE model showed a false-positive per case of 0.59 in the test set. The combined 3D BB and 3D GRE model showed a Dice coefficient of 0.822, while 3D GRE model showed a lower Dice coefficient of 0.756.

CONCLUSIONS

The combined 3D BB and 3D GRE DL model may improve the detection and segmentation performance of brain metastases, especially in detecting small metastases.

KEY POINTS

• The combined 3D BB and 3D GRE model yielded better performance for the detection of brain metastases than the 3D GRE model (p < 0.001), with sensitivities of 93.1% and 76.8%, respectively. • The combined 3D BB and 3D GRE model showed a false-positive rate per case of 0.59 in the test set. • The combined 3D BB and 3D GRE model showed a Dice coefficient of 0.822, while the 3D GRE model showed a lower Dice coefficient of 0.756.

Utility of Contrast-Enhanced T2 FLAIR for Imaging Brain Metastases Using a Half-dose High-Relaxivity Contrast Agent

BACKGROUND AND PURPOSE

Efficient detection of metastases is important for patient' treatment. This prospective study was to explore the clinical value of contrast-enhanced T2 FLAIR in imaging brain metastases using half-dose gadobenate dimeglumine.

MATERIALS AND METHODS

In vitro signal intensity of various gadolinium concentrations was explored by spin-echo T1-weighted imaging and T2 FLAIR. Then, 46 patients with lung cancer underwent nonenhanced T2 FLAIR before administration of half-dose gadobenate dimeglumine and 3 consecutive contrast-enhanced T2 FLAIR sequences followed by 1 spin-echo T1WI after administration of half-dose gadobenate dimeglumine. After an additional dose of 0.05 mmol/kg, 3D brain volume imaging was performed. All brain metastases were classified as follows: solid-enhancing, ≥ 5 mm (group A); ring-enhancing, ≥ 5 mm (group B); and lesion diameter of <5 mm (group C). The contrast ratio of the lesions on 3 consecutive phases of contrast-enhanced T2 FLAIR was measured, and the percentage increase of contrast-enhanced T2 FLAIR among the 3 groups was compared.

RESULTS

In vitro, the maximal signal intensity was achieved in T2 FLAIR at one-eighth to one-half of the contrast concentration needed for maximal signal intensity in T1WI. In vivo, the mean contrast ratio values of metastases on contrast-enhanced T2 FLAIR for the 3 consecutive phases ranged from 63.64% to 83.05%. The percentage increase (PI) values of contrast-enhanced T2 FLAIR were as follows: PI_A < PI_B (P = .001) and PI_A < PI_C (P < .001). The degree of enhancement of brain metastases on contrast-enhanced T2 FLAIR was lower than on 3D brain volume imaging (P < .001) in group A, and higher than on 3D brain volume imaging (P < .001) in group C.

CONCLUSIONS

Small or ring-enhancing metastases can be better visualized on delayed contrast-enhanced T2 FLAIR using a half-dose high-relaxivity contrast agent.

Gadolinium-Enhanced 3D T1-Weighted Black-Blood MR Imaging for the Detection of Acute Optic Neuritis

BACKGROUND AND PURPOSE

A 3D T1-weighted black-blood sequence was recently shown to improve the detection of contrast-enhancing lesions in the brain in patients with MS compared with a 3D T1-weighted MPRAGE sequence. We compared a contrast-enhanced 3D T1-weighted black-blood sequence with a dedicated orbital contrast-enhanced T1-weighted Dixon sequence in patients with acute optic neuritis.

MATERIALS AND METHODS

MR imaging data (3T) of 51 patients showing symptoms of acute optic neuritis were analyzed retrospectively, including whole-brain contrast-enhanced 3D T1-weighted black-blood and dedicated orbital coronal 2D or 3D contrast-enhanced T1-weighted Dixon sequences. Two neuroradiologists assessed the images for overall image quality, artifacts, diagnostic confidence, and visual contrast enhancement. Furthermore, the standardized contrast-to-noise ratio was calculated. The final diagnosis of acute optic neuritis was established on the basis of clinical presentation, visually evoked potentials, and optical coherence tomography.

RESULTS

Thirty of 51 patients were diagnosed with acute optic neuritis. Of those, 21 showed contrast-enhancing lesions in the optic nerves, similarly detectable on contrast-enhanced T1-weighted Dixon and contrast-enhanced T1-weighted black-blood images. Thus, the accuracy for each sequence was identical, with a resulting sensitivity of 70% and specificity of 90% or 100% (depending on the reader). Overall image quality, diagnostic confidence, visual contrast enhancement, and artifacts were rated similarly in contrast-enhanced 3D T1-weighted black-blood and dedicated orbital contrast-enhanced T1-weighted Dixon sequences. There was no significant difference (P = .27) in the mean standardized contrast-to-noise ratio between contrast-enhanced T1-weighted black-blood (1.76 ± 1.07) and contrast-enhanced T1-weighted Dixon (2.29 ± 2.49) sequences.

CONCLUSIONS

Contrast-enhanced 3D T1-weighted black-blood imaging is comparable in accuracy and qualitative/quantitative features with dedicated orbital contrast-enhanced T1-weighted Dixon imaging for the detection of acute optic neuritis. Therefore, when used, it has the potential to considerably shorten total patient imaging time.

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.

Twofold improved tumor-to-brain contrast using a novel T1 relaxation-enhanced steady-state (T1RESS) MRI technique

A technique that provides more accurate cancer detection would be of great value. Toward this end, we developed T1 relaxation-enhanced steady-state (T₁RESS), a novel magnetic resonance imaging (MRI) pulse sequence that enables the flexible modulation of T1 weighting and provides the unique feature that intravascular signals can be toggled on and off in contrast-enhanced scans. T₁RESS makes it possible to effectively use an MRI technique with improved signal-to-noise ratio efficiency for cancer imaging. In a proof-of-concept study, "dark blood" unbalanced T₁RESS provided a twofold improvement in tumor-to-brain contrast compared with standard techniques, whereas balanced T₁RESS greatly enhanced vascular detail. In conclusion, T₁RESS represents a new MRI technique with substantial potential value for cancer imaging, along with a broad range of other clinical applications.

Labyrinthine enhancement on 3D black blood MR images of the brain as an imaging biomarker for cisplatin ototoxicity in (lung) cancer patients

PURPOSE

Cancer patients treated with platinum-based chemotherapy can present with ototoxicity symptoms. The purpose of this work is to report the imaging features related to cisplatin ototoxicity.

METHODS

Between December 2015 and March 2019, a cohort of 96 consecutive patients with lung cancer was selected. Only patients who received cisplatin chemotherapy and underwent an imaging protocol consisting of a Gd-enhanced 3D-BB and 3D-T1W sequence, as well as T2W sequence to exclude metastases, were included. Labyrinthine enhancement was assessed, and all findings regarding the auditory and vestibular function were retrieved from the clinical files.

RESULTS

Twenty-one patients met the inclusion criteria. The Gd-enhanced 3D-BB images were used to divide them into the labyrinth enhancement group (LEG) and the labyrinth non-enhancement group (LNEG). None of these patients demonstrated enhancing regions on the 3D-T1W images. The labyrinthine fluid remained high on the T2 images in all patients, excluding metastases. The LEG consisted of 6 patients. The cochlea and semicircular canals were the most frequently affected regions. All the LEG patients that presented with hearing loss (4/6) had cochlear enhancement. Patients with normal hearing had no cochlear enhancement. Five patients (5/6) showed vestibular enhancement. Four of these patients had vestibular symptoms.

CONCLUSION

Labyrinthine enhancement as an imaging feature related to cisplatin ototoxicity is unreported. This study demonstrates a correlation between hearing loss and cochlear enhancement and also between vestibular impairment and vestibular/semicircular enhancement on 3D-BB images, which remained invisible on the 3D-T1W images. The labyrinthine enhancement on 3D-BB images in the presence of normal signal intensity of the intralabyrinthine fluid can be used as an imaging biomarker for cisplatin toxicity in daily clinical practice and should not be mistaken for intralabyrinthine metastases.

Deep-Learning Detection of Cancer Metastases to the Brain on MRI

BACKGROUND

Approximately one-fourth of all cancer metastases are found in the brain. MRI is the primary technique for detection of brain metastasis, planning of radiotherapy, and the monitoring of treatment response. Progress in tumor treatment now requires detection of new or growing metastases at the small subcentimeter size, when these therapies are most effective.

PURPOSE

To develop a deep-learning-based approach for finding brain metastasis on MRI.

STUDY TYPE

Retrospective.

SEQUENCE

Axial postcontrast 3D T₁ -weighted imaging.

FIELD STRENGTH

1.5T and 3T.

POPULATION

A total of 361 scans of 121 patients were used to train and test the Faster region-based convolutional neural network (Faster R-CNN): 1565 lesions in 270 scans of 73 patients for training; 488 lesions in 91 scans of 48 patients for testing. From the 48 outputs of Faster R-CNN, 212 lesions in 46 scans of 18 patients were used for training the RUSBoost algorithm (MatLab) and 276 lesions in 45 scans of 30 patients for testing.

ASSESSMENT

Two radiologists diagnosed and supervised annotation of metastases on brain MRI as ground truth. This data were used to produce a 2-step pipeline consisting of a Faster R-CNN for detecting abnormal hyperintensity that may represent brain metastasis and a RUSBoost classifier to reduce the number of false-positive foci detected.

STATISTICAL TESTS

The performance of the algorithm was evaluated by using sensitivity, false-positive rate, and receiver's operating characteristic (ROC) curves. The detection performance was assessed both per-metastases and per-slice.

RESULTS

Testing on held-out brain MRI data demonstrated 96% sensitivity and 20 false-positive metastases per scan. The results showed an 87.1% sensitivity and 0.24 false-positive metastases per slice. The area under the ROC curve was 0.79.

CONCLUSION

Our results showed that deep-learning-based computer-aided detection (CAD) had the potential of detecting brain metastases with high sensitivity and reasonable specificity.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:1227-1236.

Usefulness of the Delay Alternating with Nutation for Tailored Excitation Pulse with T1-Weighted Sampling Perfection with Application-Optimized Contrasts Using Different Flip Angle Evolution in the Detection of Cerebral Metastases: Comparison with MPRAGE Imaging

BACKGROUND AND PURPOSE

Contrast-enhanced T1-weighted sampling perfection with application-optimized contrasts by using different flip angle evolution (SPACE) with the delay alternating with nutation for tailored excitation (DANTE) pulse could suppress the blood flow signal and provide a higher contrast-to-noise ratio of enhancing lesion-to-brain parenchyma than the MPRAGE sequence. The purpose of our study was to evaluate the usefulness of SPACE with DANTE compared with MPRAGE for detecting brain metastases.

MATERIALS AND METHODS

Seventy-one patients who underwent contrast-enhanced SPACE with DANTE and MPRAGE sequences and who were suspected of having metastatic lesions were included. Two neuroradiologists determined the number of enhancing lesions, and diagnostic performance was evaluated using figure of merit, sensitivity, positive predictive value, interobserver agreement, and reading time. Contrast-to-noise ratio_{lesion/parenchyma} and contrast-to-noise ratio_{white matter/gray matter} were also assessed.

RESULTS

SPACE with DANTE (observer one, 328; observer two, 324) revealed significantly more small (<5 mm) enhancing lesions than MPRAGE (observer one, 175; observer two, 150) (P < 0.001 for observer 1, P ≤ .0001 for observer 2). Furthermore, SPACE with DANTE showed significantly higher figure of merit and sensitivity and shorter reading time than MPRAGE for both observers. The mean contrast-to-noise ratio_{lesion/parenchyma} of SPACE with DANTE (52.3 ± 43.1) was significantly higher than that of MPRAGE (17.5 ± 19.3) (P ≤ .0001), but the mean contrast-to-noise ratio_{white matter/gray matter} of SPACE with DANTE (-0.65 ± 1.39) was significantly lower than that of MPRAGE (3.08 ± 1.39) (P ≤ .0001).

CONCLUSIONS

Compared with MPRAGE, SPACE with DANTE significantly improves the detection of brain metastases.

Diagnostic Clinical Trials in Breast Cancer Brain Metastases: Barriers and Innovations

Optimal treatment of breast cancer brain metastases (BCBM) is often hampered by limitations in diagnostic abilities. Developing innovative tools for BCBM diagnosis is vital for early detection and effective treatment. In this study we explored the advances in trial for the diagnosis of BCBM, with review of the literature. On May 8, 2019, we searched ClinicalTrials.gov for interventional and diagnostic clinical trials involving BCBM, without limiting for date or location. Information on trial characteristics, experimental interventions, results, and publications were collected and analyzed. In addition, a systematic review of the literature was conducted to explore published studies related to BCBM diagnosis. Only 9 diagnostic trials explored BCBM. Of these, 1 trial was withdrawn because of low accrual numbers. Three trials were completed; however, none had published results. Modalities in trial for BCBM diagnosis entailed magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), PET-CT, nanobodies, and circulating tumor cells (CTCs), along with a collection of novel tracers and imaging biomarkers. MRI continues to be the diagnostic modality of choice, whereas CT is best suited for acute settings. Advances in PET and PET-CT allow the collection of metabolic and functional information related to BCBM. CTC characterization can help reflect on the molecular foundations of BCBM, whereas cell-free DNA offers new genetic material for further exploration in trials. The integration of machine learning in BCBM diagnosis seems inevitable as we continue to aim for rapid and accurate detection and better patient outcomes.

Evaluation of Thick-Slab Overlapping MIP Images of Contrast-Enhanced 3D T1-Weighted CUBE for Detection of Intracranial Metastases: A Pilot Study for Comparison of Lesion Detection, Interpretation Time, and Sensitivity with Nonoverlapping CUBE MIP, CUBE, and Inversion-Recovery-Prepared Fast-Spoiled Gradient Recalled Brain Volume

BACKGROUND AND PURPOSE

Early and accurate identification of cerebral metastases is important for prognostication and treatment planning although this process is often time consuming and labor intensive, especially with the hundreds of images associated with 3D volumetric imaging. This study aimed to evaluate the benefits of thick-slab overlapping MIPs constructed from contrast-enhanced T1-weighted CUBE (overlapping CUBE MIP) for the detection of brain metastases in comparison with traditional CUBE and inversion-recovery prepared fast-spoiled gradient recalled brain volume (IR-FSPGR-BRAVO) and nonoverlapping CUBE MIP.

MATERIALS AND METHODS

A retrospective review of 48 patients with cerebral metastases was performed at our institution from June 2016 to October 2017. Brain MRIs, which were acquired on multiple 3T scanners, included gadolinium-enhanced T1-weighted IR-FSPGR-BRAVO and CUBE, with subsequent generation of nonoverlapping CUBE MIP and overlapping CUBE MIP. Two blinded radiologists identified the total number and location of metastases on each image type. The Cohen κ was used to determine interrater agreement. Sensitivity, interpretation time, and lesion contrast-to-noise ratio were assessed.

RESULTS

Interrater agreement for identification of metastases was fair-to-moderate for all image types (κ = 0.222-0.598). The total number of metastases identified was not significantly different across the image types. Interpretation time for CUBE MIPs was significantly shorter than for CUBE and IR-FSPGR-BRAVO, saving at least 50 seconds per case on average (P < .001). The mean lesion contrast-to-noise ratio for both CUBE MIPs was higher than for IR-FSPGR-BRAVO. The mean contrast-to-noise ratio for small lesions (<4 mm) was lower for nonoverlapping CUBE MIP (1.55) than for overlapping CUBE MIP (2.35). For both readers, the sensitivity for lesion detection was high for all image types but highest for overlapping CUBE MIP and CUBE (0.93-0.97).

CONCLUSIONS

This study suggests that the use of overlapping CUBE MIP or nonoverlapping CUBE MIP for the detection of brain metastases can reduce interpretation time without sacrificing sensitivity, though the contrast-to-noise ratio of lesions is highest for overlapping CUBE MIP.

Deep-learned 3D black-blood imaging using automatic labelling technique and 3D convolutional neural networks for detecting metastatic brain tumors

Black-blood (BB) imaging is used to complement contrast-enhanced 3D gradient-echo (CE 3D-GRE) imaging for detecting brain metastases, requiring additional scan time. In this study, we proposed deep-learned 3D BB imaging with an auto-labelling technique and 3D convolutional neural networks for brain metastases detection without additional BB scan. Patients were randomly selected for training (29 sets) and testing (36 sets). Two neuroradiologists independently evaluated deep-learned and original BB images, assessing the degree of blood vessel suppression and lesion conspicuity. Vessel signals were effectively suppressed in all patients. The figure of merits, which indicate the diagnostic performance of radiologists, were 0.9708 with deep-learned BB and 0.9437 with original BB imaging, suggesting that the deep-learned BB imaging is highly comparable to the original BB imaging (difference was not significant; p = 0.2142). In per patient analysis, sensitivities were 100% for both deep-learned and original BB imaging; however, the original BB imaging indicated false positive results for two patients. In per lesion analysis, sensitivities were 90.3% for deep-learned and 100% for original BB images. There were eight false positive lesions on the original BB imaging but only one on the deep-learned BB imaging. Deep-learned 3D BB imaging can be effective for brain metastases detection.

Multiple Sclerosis: Improved Detection of Active Cerebral Lesions With 3-Dimensional T1 Black-Blood Magnetic Resonance Imaging Compared With Conventional 3-Dimensional T1 GRE Imaging

OBJECTIVES

The aim of this study was to assess the diagnostic accuracy of a modified high-resolution whole-brain three-dimensional T1-weighted black-blood sequence (T1-weighted modified volumetric isotropic turbo spin echo acquisition [T1-mVISTA]) in comparison to a standard three-dimensional T1-weighted magnetization-prepared rapid gradient echo (MP-RAGE) sequence for detection of contrast-enhancing cerebral lesions in patients with relapsing-remitting multiple sclerosis (MS).

MATERIALS AND METHODS

After institutional review board approval and informed consent, 22 patients (8 men; aged 31.0 ± 9.2 years) with relapsing-remitting MS were included in this monocentric prospective cohort study.Contrast-enhanced T1-mVISTA and MP-RAGE, both with 0.8 mm resolution, were performed in all patients. In a substudy of 12 patients, T1-mVISTA was compared with a T1-mVISTA with 1.0 mm resolution (T1-mVISTA_1.0). Reference lesions were defined by an experienced neuroradiologist using all available sequences and served as the criterion standard. T1-mVISTA, T1-mVISTA_1.0, and MP-RAGE sequences were read in random order 4 weeks apart. Image quality, visual contrast enhancement, contrast-to-noise-ratio (CNR), diagnostic confidence, and lesion size were assessed and compared by Wilcoxon and Mann-Whitney U tests.

RESULTS

Eleven of 22 patients displayed contrast-enhancing lesions. Visual contrast enhancement, CNR, and diagnostic confidence of contrast-enhancing MS lesions were significantly increased in T1-mVISTA compared with MP-RAGE (P < 0.001). Significantly more contrast-enhancing lesions were detected with T1-mVISTA than with MP-RAGE (71 vs 39, respectively; P < 0.001). With MP-RAGE, 25.6% of lesions were missed in the initial reading, whereas only 4.2% of lesions were missed with T1-mVISTA. Increase of the voxel volume from 0.8 mm to 1.0 mm isotropic in T1-mVISTA_1.0 did not affect the detectability of lesions, whereas scan time was decreased from 4:43 to 1:55 minutes.

CONCLUSIONS

Three-dimensional T1-mVISTA improves the detection rates of contrast-enhancing cerebral MS lesions compared with conventional 3D MP-RAGE sequences by increasing CNR of lesions and might, therefore, be useful in patient management.

Detection of Volume-Changing Metastatic Brain Tumors on Longitudinal MRI Using a Semiautomated Algorithm Based on the Jacobian Operator Field

BACKGROUND AND PURPOSE

Accurate follow-up of metastatic brain tumors has important implications for patient prognosis and management. The aim of this study was to develop and evaluate the accuracy of a semiautomated algorithm in detecting growing or shrinking metastatic brain tumors on longitudinal brain MRIs.

MATERIALS AND METHODS

We used 50 pairs of successive MR imaging datasets, 30 on 1.5T and 20 on 3T, containing contrast-enhanced 3D T1-weighted sequences. These yielded 150 growing or shrinking metastatic brain tumors. To detect them, we completed 2 major steps: 1) spatial normalization and calculation of the Jacobian operator field to quantify changes between scans, and 2) metastatic brain tumor candidate segmentation and detection of volume-changing metastatic brain tumors with the Jacobian operator field. Receiver operating characteristic analysis was used to assess the detection accuracy of the algorithm, and it was verified with jackknife resampling. The reference standard was based on detections by a neuroradiologist.

RESULTS

The areas under the receiver operating characteristic curves were 0.925 for 1.5T and 0.965 for 3T. Furthermore, at its optimal performance, the algorithm achieved a sensitivity of 85.1% and 92.1% and specificity of 86.7% and 91.3% for 1.5T and 3T, respectively. Vessels were responsible for most false-positives. Newly developed or resolved metastatic brain tumors were a major source of false-negatives.

CONCLUSIONS

The proposed algorithm could detect volume-changing metastatic brain tumors on longitudinal brain MRIs with statistically high accuracy, demonstrating its potential as a computer-aided change-detection tool for complementing the performance of radiologists, decreasing inter- and intraobserver variability, and improving efficacy.

Efficacy of Maximum Intensity Projection of Contrast-Enhanced 3D Turbo-Spin Echo Imaging with Improved Motion-Sensitized Driven-Equilibrium Preparation in the Detection of Brain Metastases

Objective

To evaluate the diagnostic benefits of 5-mm maximum intensity projection of improved motion-sensitized driven-equilibrium prepared contrast-enhanced 3D T1-weighted turbo-spin echo imaging (MIP iMSDE-TSE) in the detection of brain metastases. The imaging technique was compared with 1-mm images of iMSDE-TSE (non-MIP iMSDE-TSE), 1-mm contrast-enhanced 3D T1-weighted gradient-echo imaging (non-MIP 3D-GRE), and 5-mm MIP 3D-GRE.

Materials and Methods

From October 2014 to July 2015, 30 patients with 460 enhancing brain metastases (size > 3 mm, n = 150; size ≤ 3 mm, n = 310) were scanned with non-MIP iMSDE-TSE and non-MIP 3D-GRE. We then performed 5-mm MIP reconstruction of these images. Two independent neuroradiologists reviewed these four sequences. Their diagnostic performance was compared using the following parameters: sensitivity, reading time, and figure of merit (FOM) derived by jackknife alternative free-response receiver operating characteristic analysis. Interobserver agreement was also tested.

Results

The mean FOM (all lesions, 0.984; lesions ≤ 3 mm, 0.980) and sensitivity ([reader 1: all lesions, 97.3%; lesions ≤ 3 mm, 96.2%], [reader 2: all lesions, 97.0%; lesions ≤ 3 mm, 95.8%]) of MIP iMSDE-TSE was comparable to the mean FOM (0.985, 0.977) and sensitivity ([reader 1: 96.7, 99.0%], [reader 2: 97, 95.3%]) of non-MIP iMSDE-TSE, but they were superior to those of non-MIP and MIP 3D-GREs (all, p < 0.001). The reading time of MIP iMSDE-TSE (reader 1: 47.7 ± 35.9 seconds; reader 2: 44.7 ± 23.6 seconds) was significantly shorter than that of non-MIP iMSDE-TSE (reader 1: 78.8 ± 43.7 seconds, p = 0.01; reader 2: 82.9 ± 39.9 seconds, p < 0.001). Interobserver agreement was excellent (κ > 0.75) for all lesions in both sequences.

Conclusion

MIP iMSDE-TSE showed high detectability of brain metastases. Its detectability was comparable to that of non-MIP iMSDE-TSE, but it was superior to the detectability of non-MIP/MIP 3D-GREs. With a shorter reading time, the false-positive results of MIP iMSDE-TSE were greater. We suggest that MIP iMSDE-TSE can provide high diagnostic performance and low false-positive rates when combined with 1-mm sequences.

The detectability of brain metastases using contrast-enhanced spin-echo or gradient-echo images: a systematic review and meta-analysis

This study aimed to compare the detectability of brain metastases using contrast-enhanced spin-echo (SE) and gradient-echo (GRE) T1-weighted images. The Ovid-MEDLINE and EMBASE databases were searched for studies on the detectability of brain metastases using contrast-enhanced SE or GRE images. The pooled proportions for the detectability of brain metastases were assessed using random-effects modeling. Heterogeneity among studies was determined using χ (2) statistics for the pooled estimates and the inconsistency index, I (2) . To overcome heterogeneity, subgroup analyses according to slice thickness and lesion size were performed. A total of eight eligible studies, which included a sample size of 252 patients and 1413 brain metastases, were included. The detectability of brain metastases using SE images (89.2 %) was higher than using GRE images (81.6 %; adjusted 84.0 %), but this difference was not statistically significant (p = 0.2385). In subgroup analysis of studies with 1-mm-thick slices and small metastases (<5 mm in diameter), 3-dimensional (3D) SE images demonstrated a higher detectability in comparison to 3D GRE images (93.7 % vs 73.1 % in 1-mm-thick slices; 89.5 % vs 59.4 % for small metastases) (p < 0.0001). Although both SE or GRE images are acceptable for detecting brain metastases, contrast-enhanced 3D SE images using 1-mm-thick slices are preferred for detecting brain metastases, especially small lesions (<5 mm in diameter).

Comparison of contrast-enhanced modified T1-weighted 3D TSE black-blood and 3D MP-RAGE sequences for the detection of cerebral metastases and brain tumours

OBJECTIVES

To compare a modified T1-weighted 3D TSE black-blood sequence with sub-millimetre resolution (T1-mVISTA) with a magnetization-prepared rapid gradient echo (MP-RAGE) sequence for the diagnosis of cerebral malignomas.

METHODS

Forty-six patients with known or suspected intracranial tumours and 15 control patients were included in this retrospective study. All patients underwent T1-mVISTA (0.75-mm isotropic resolution, 4:43 min) and MP-RAGE (0.8-mm isotropic resolution, 4:46 minutes) at 3-Tesla in random order after application of contrast agent. Two experienced radiologists determined the number of lesions. Maximum diameter, diagnostic confidence (DC), visual assessment of contrast enhancement (VCE) and CNRlesion/parenchyma were assessed for each lesion.

RESULTS

Significantly more lesions were detected with T1-mVISTA compared to the MP-RAGE (61 vs. 36; p < 0.05). Further, DC and VCE was rated significantly higher in the T1-mVISTA (p < 0.05 and p < 0.001). Mean CNRlesion/parenchyma was twofold higher for T1-mVISTA (24.2 ± 17.5 vs. 12.7 ± 11.5, p < 0.001). The 25 lesions detected only in T1-mVISTA were significantly smaller than those detected in both sequences (4.3 ± 3.7 mm vs. 11.3 ± 10.7 mm; p < 0.01).

CONCLUSIONS

T1-mVISTA increases the contrast of lesions significantly compared to MP-RAGE and might therefore improve detection rates of small lesions in early stages of disease.

KEY POINTS

• T1-mVISTA leads to significantly higher contrast-to-noise ratios of cerebral malignomas. • T1-mVISTA detects significantly more metastatic lesions compared to 3D-MPRAGE. • Lesions detected only by T1-mVISTA are smaller than those detected in both sequences. • Diagnostic confidence is significantly higher for lesions detected by T1-mVISTA. • Application of T1-mVISTA might be of high relevance in early stages of disease.

Is stereotactic radiosurgery a rational treatment option for brain metastases from small cell lung cancer? A retrospective analysis of 70 consecutive patients

Background

Because of the high likelihood of multiple brain metastases (BM) from small cell lung cancer (SCLC), the role of focal treatment using stereotactic radiosurgery (SRS) has yet to be determined. We aimed to evaluate the efficacy and limitations of upfront and salvage SRS for patients with BM from SCLC.

Methods

This was a retrospective and observational study analyzing 70 consecutive patients with BM from SCLC who received SRS. The median age was 68 years, and the median Karnofsky performance status (KPS) was 90. Forty-six (66%) and 24 (34%) patients underwent SRS as the upfront and salvage treatment after prophylactic or therapeutic whole brain radiotherapy (WBRT), respectively. Overall survival (OS), neurological death-free survival, remote and local tumor recurrence rates were analyzed.

Results

None of our patients were lost to follow-up and the median follow-up was 7.8 months. One-and 2-year OS rates were 43% and 15%, respectively. The median OS time was 7.8 months. One-and 2-year neurological death-free survival rates were 94% and 84%, respectively. In total, 219/292 tumors (75%) in 60 patients (86 %) with sufficient radiological follow-up data were evaluated. Six-and 12-month rates of remote BM relapse were 25% and 47%, respectively. Six-and 12-month rates of local control failure were 4% and 23%, respectively. Repeat SRS, salvage WBRT and microsurgery were subsequently required in 30, 8 and one patient, respectively. Symptomatic radiation injury, treated conservatively, developed in 3 patients.

Conclusions

The present study suggested SRS to be a potentially effective and minimally invasive treatment option for BM from SCLC either alone or after failed WBRT. Although repeat salvage treatment was needed in nearly half of patients to achieve control of distant BM, such continuation of radiotherapeutic management might contribute to reducing the rate of neurological death.

Detection of small brain metastases at 3 T: comparing the diagnostic performances of contrast-enhanced T1-weighted SPACE, MPRAGE, and 2D FLASH imaging

The aim of this study was to compare the diagnostic performance of contrast-enhanced T1-weighted sampling perfection with application-optimized contrasts using different flip angle evolutions (SPACE), magnetization-prepared rapid gradient-echo (MPRAGE), and two-dimensional (2D) fast low angle shot (FLASH) for the detection of small brain metastases. Twelve patients who had brain metastases less than 10 mm in diameter were enrolled. The diagnostic performance was evaluated using alternative free-response receiver operating characteristic analysis. Sensitivity and positive predictive value were also calculated. The mean Az and sensitivities of SPACE for all observers were significantly higher than those of MPRAGE and 2D FLASH.

Clinical image quality assessment of accelerated magnetic resonance neuroimaging using compressed sensing

PURPOSE

The aim of this study was to determine to what degree current compressed sensing methods are capable of accelerating clinical magnetic resonance neuroimaging sequences.

METHODS

Two 2-dimensional clinical sequences were chosen for this study because of their long scan times. A pilot study was used to establish the sampling scheme and regularization parameter needed in compressed sensing reconstruction. These findings were used in a subsequent blinded study in which images reconstructed using compressed sensing were evaluated by 2 board-certified neuroradiologists. Image quality was evaluated at up to 10 anatomical features.

RESULTS

The findings indicate that compressed sensing may provide 2-fold acceleration of certain clinical magnetic resonance neuroimaging sequences. A global ringing artifact and image blurring were identified as the 2 primary artifacts that would hinder the ability to confidently discern abnormality.

CONCLUSION

Compressed sensing is able to moderately accelerate certain neuroimaging sequences without severe loss of clinically relevant information. For those sequences with coarser spatial resolution and/or at a higher acceleration factor, artifacts degrade the quality of the reconstructed image to a point where they are of little to no clinical value.

A historical overview of magnetic resonance imaging, focusing on technological innovations

Magnetic resonance imaging (MRI) has now been used clinically for more than 30 years. Today, MRI serves as the primary diagnostic modality for many clinical problems. In this article, historical developments in the field of MRI will be discussed with a focus on technological innovations. Topics include the initial discoveries in nuclear magnetic resonance that allowed for the advent of MRI as well as the development of whole-body, high field strength, and open MRI systems. Dedicated imaging coils, basic pulse sequences, contrast-enhanced, and functional imaging techniques will also be discussed in a historical context. This article describes important technological innovations in the field of MRI, together with their clinical applicability today, providing critical insights into future developments.

Contrast-enhanced MR imaging in neuroimaging

MR imaging without and with gadolinium-based contrast agents (GBCAs) is an important imaging tool for defining normal anatomy and characteristics of lesions. GBCAs have been used in contrast-enhanced MR imaging in defining and characterizing lesions of the central nervous system for more than 20 years. The combination of unenhanced and GBCA-enhanced MR imaging is the clinical gold standard for the noninvasive detection and delineation of most intracranial and spinal lesions. MR imaging has a high predictive value that rules out neoplasm and most inflammatory and demyelinating processes of the central nervous system.