Fat-saturated Sequences Research Articles

Magnetic Resonance Imaging Diagnosis of Spinal Longitudinal Epidural Collections in a Spontaneous Spinal Dural Breach and Successful Surgical Treatment

Spontaneous intracranial hypotension is generally secondary to cerebrospinal fluid leaks. Spinal magnetic resonance imaging is an important part of the diagnostic workup, especially to display spinal longitudinal epidural collections. Other causes of leaks include nerve root sleeve tear and cerebrospinal fluid-venous fistula. We propose a standard magnetic resonance imaging protocol including sagittal T1, T2-weighted, and T2 fat-saturated sequences, with addition of high-resolution three-dimensional T2 images to improve detection of spinal longitudinal epidural collections and help locate the dural breach level. Spine computed tomography may prove useful in detecting a bony spur that may cause the dural breach. Treatment of identified dural breaches includes targeted epidural blood patch or neurosurgery in case of blood patch inefficacy. Few cases of successful surgical treatments of dural breaches have been reported with complete regression of spinal longitudinal epidural collections; thus more studies will be valuable to help establish guidelines in this pathology.

Increased Postoperative Deltoid Signal seen after Suprapectoral Biceps Tenodesis: Potential Risk to the Anterior Branch of the Axillary Nerve

BackgroundArthroscopic suprapectoral biceps tenodesis is a common procedure for lesions of the long head of the biceps in the setting of anterior shoulder pain. However, the distal portal poses a theoretical risk to the terminal branches of the axillary nerve as the nerve travels from posterior to anterior to innervate the anterior deltoid. The purpose of this retrospective cohort study was to assess for axillary nerve branch injury, identified by deltoid signal change in postoperative magnetic resonance imaging (MRI) in patients who underwent an arthroscopic suprapectoral biceps tenodesis. MethodsPatients who underwent rotator cuff repair with a concomitant arthroscopic suprapectoral biceps tenodesis, had a postoperative MRI, and at least 1 year of follow-up were included. The incidence of increased deltoid signal consistent with injury to an anterior branch of the axillary nerve on proton density fat saturated sequences was collected. Age, sex, body mass index (BMI), and patient reported outcome measures (PROMs) including the American Shoulder and Elbow Surgeons Shoulder Score (ASES) score, Patient-Reported Outcomes Measurement Information System (PROMIS) pain, physical function (PF), and upper extremity (UE) scores, and Single Assessment Numeric Evaluation (SANE) score were compared in patients with and without increased deltoid signal on postoperative MRI. P<0.05 was used for significance. ResultsTwenty-four patients were eligible for inclusion (9 female, average age 59.0±10.1, BMI 27.6±6.7). Edema-like signal within the anterior deltoid musculature was observed in 9 patients on postoperative MRI. Two patients had a second follow-up MRI performed which demonstrated resolution of signal, and one patient required a second surgery for release of adhesions. Patients with increased deltoid signal had higher BMI (p=0.03). There was no difference in any other demographic or postoperative PROM between patients with increased signal and those without at any follow-up time point. No patient demonstrated persistent weakness or numbness in the axillary nerve distribution at final follow-up. DiscussionOver one third of patients in our cohort had MRI evidence of axillary nerve branch injury as seen on proton density fat saturated MRI sequences postoperatively. The distal arthroscopic portal for a suprapectoral biceps tenodesis may place anterior terminal branches of the axillary nerve at risk for injury. Additional investigation and strategies for avoidance of nerve injury in this area should be pursued.

The role of sacro-iliac joint magnetic resonance imaging in the diagnosis of axial spondyloarthritis: focus on differential diagnosis in women.

To review the role of sacro-iliac magnetic resonance imaging (MRI) in the diagnosis of axial spondyloarthritis (AxSpA), with a focus on gender differences. The experience of the authors and the results of an informal literature review are reported. Inflammatory changes of the sacro-iliac joint are the hallmark of AxSpA. Early, non-radiographic sacroiliitis may be diagnosed with MRI through the assessment of bone marrow edema (BMO) as well as concomitant structural damage. The MRI protocol should include three necessary sequences, i.e., fat-saturated T2-weighted sequences on two orthogonal planes, T1-weighted semi-coronal sequence, and fat-suppressed T1-weighted semi-coronal sequence. Inflammatory changes comprise required signs (BMO and/or osteitis) and additional signs, including synovitis (better defined as joint space enhancement), enthesitis, and capsulitis. Structural changes consist of erosions, sclerosis, fat metaplasia, and ankylosis. Due to mechanical axial strain, inflammatory changes in the sacro-iliac joint can be found in healthy individuals, runners, and patients with nonspecific low back pain. The prevalence of BMO is higher in women during pregnancy and postpartum, even 12 months after childbirth, but the extent and distribution of MRI findings may help in the differential diagnosis. Other challenges in the MRI diagnosis of sacroiliitis are subchondral T2 hyperintensity during developmental age, periarticular sclerosis in healthy subjects, or osteitis condensans ilii, and several pathological conditions that may mimic AxSpA, some of which are more frequently found in women. The described diagnostic challenges impose a multidisciplinary approach combining imaging findings with clinical and laboratory data.

A multimodal neural network with gradient blending improves predictions of survival and metastasis in sarcoma

The objective of this study is to develop a multimodal neural network (MMNN) model that analyzes clinical variables and MRI images of a soft tissue sarcoma (STS) patient, to predict overall survival and risk of distant metastases. We compare the performance of this MMNN to models based on clinical variables alone, radiomics models, and an unimodal neural network. We include patients aged 18 or older with biopsy-proven STS who underwent primary resection between January 1st, 2005, and December 31st, 2020 with complete outcome data and a pre-treatment MRI with both a T1 post-contrast sequence and a T2 fat-sat sequence available. A total of 9380 MRI slices containing sarcomas from 287 patients are available. Our MMNN accepts the entire 3D sarcoma volume from T1 and T2 MRIs and clinical variables. Gradient blending allows the clinical and image sub-networks to optimally converge without overfitting. Heat maps were generated to visualize the salient image features. Our MMNN outperformed all other models in predicting overall survival and the risk of distant metastases. The C-Index of our MMNN for overall survival is 0.77 and the C-Index for risk of distant metastases is 0.70. The provided heat maps demonstrate areas of sarcomas deemed most salient for predictions. Our multimodal neural network with gradient blending improves predictions of overall survival and risk of distant metastases in patients with soft tissue sarcoma. Future work enabling accurate subtype-specific predictions will likely utilize similar end-to-end multimodal neural network architecture and require prospective curation of high-quality data, the inclusion of genomic data, and the involvement of multiple centers through federated learning.

Aneurysmal Wall Enhancement of Non-Ruptured Intracranial Aneurysms after Endovascular Treatment Correlates with Higher Aneurysm Reperfusion Rates, but Only in Large Aneurysms.

Aneurysmal wall enhancement (AWE) of non-ruptured sacular intracranial aneurysms (IA) after endovascular treatment (ET) is a frequently observed imaging finding using AWE-sequences in brain magnetic resonance imaging (MRI). So far, its value remains unclear. We aimed to investigate the effect of AWE on aneurysm reperfusion rates in a longitudinal cohort. This is a retrospective MRI study over the timespan of up to 5 years, assessing the correlation of increased AWE of non-ruptured IAs and events of aneurysm reperfusion and retreatment, PHASES Score and grade of AWE. T1 SPACE fat saturation (FS) and T1 SE FS blood suppression sequences after contrast administration were used for visual interpretation of increased AWE. The IAs' sizes were assessed via the biggest diameter. The grade of enhancement was defined in a grading system from grade 1 to grade 3. 127 consecutive non ruptured IA-patients (58.9 ± 9.0 years, 94 female, 33 male) who underwent elective aneurysm occlusion were included. AWE was observed in 40.2% of patients (51/127) after ET, 6 patients already showed AWE before treatment. In large IAs (which were defined as a single maximum diameter of over 7.5 mm), AWE was significantly associated with aneurysm reperfusion in contrast to large aneurysm without AWE). All grades of AWE were significantly associated with reperfusion. Our data suggests that in patients with initially large IAs, AWE is correlated with aneurysm reperfusion.

Evaluation of deep-learning TSE images in clinical musculoskeletal imaging.

In this study, we compared the fat-saturated (FS) and non-FS turbo spin echo (TSE) magnetic resonance imaging knee sequences reconstructed conventionally (conventional-TSE) against a deep learning-based reconstruction of accelerated TSE (DL-TSE) scans. A total of 232 conventional-TSE and DL-TSE image pairs were acquired for comparison. For each consenting patient, one of the clinically acquired conventional-TSE proton density-weighted sequences in the sagittal or coronal planes (FS and non-FS), or in the axial plane (non-FS), was repeated using a research DL-TSE sequence. The DL-TSE reconstruction resulted in an image resolution that increased by at least 45% and scan times that were up to 52% faster compared to the conventional TSE. All images were acquired on a MAGNETOM Vida 3T scanner (Siemens Healthineers AG, Erlangen, Germany). The reporting radiologists, blinded to the acquisition time, were requested to qualitatively compare the DL-TSE against the conventional-TSE reconstructions. Despite having a faster acquisition time, the DL-TSE was rated to depict smaller structures better for 139/232 (60%) cases, equivalent for 72/232 (31%) cases and worse for 21/232 (9%) cases compared to the conventional-TSE. Overall, the radiologists preferred the DL-TSE reconstruction in 124/232 (53%) cases and stated no preference, implying equivalence, for 65/232 (28%) cases. DL-TSE reconstructions enabled faster acquisition times while enhancing spatial resolution and preserving the image contrast. From these results, the DL-TSE provided added or comparable clinical value and utility in less time. DL-TSE offers the opportunity to further reduce the overall examination time and improve patient comfort with no loss in diagnostic accuracy.

Reconstruction of 3D knee MRI using deep learning and compressed sensing: a validation study on healthy volunteers.

To investigate the potential of combining compressed sensing (CS) and artificial intelligence (AI), in particular deep learning (DL), for accelerating three-dimensional (3D) magnetic resonance imaging (MRI) sequences of the knee. Twenty healthy volunteers were examined using a 3-T scanner with a fat-saturated 3D proton density sequence with four different acceleration levels (10, 13, 15, and 17). All sequences were accelerated with CS and reconstructed using the conventional and a new DL-based algorithm (CS-AI). Subjective image quality was evaluated by two blinded readers using seven criteria on a 5-point-Likert-scale (overall impression, artifacts, delineation of the anterior cruciate ligament, posterior cruciate ligament, menisci, cartilage, and bone). Using mixed models, all CS-AI sequences were compared to the clinical standard (sense sequence with an acceleration factor of 2) and CS sequences with the same acceleration factor. 3D sequences reconstructed with CS-AI achieved significantly better values for subjective image quality compared to sequences reconstructed with CS with the same acceleration factor (p ≤ 0.001). The images reconstructed with CS-AI showed that tenfold acceleration may be feasible without significant loss of quality when compared to the reference sequence (p ≥ 0.999). For 3-T 3D-MRI of the knee, a DL-based algorithm allowed for additional acceleration of acquisition times compared to the conventional approach. This study, however, is limited by its small sample size and inclusion of only healthy volunteers, indicating the need for further research with a more diverse and larger sample. DRKS00024156. Using a DL-based algorithm, 54% faster image acquisition (178s versus 384s) for 3D-sequences may be possible for 3-T MRI of the knee. • Combination of compressed sensing and DL improved image quality and allows for significant acceleration of 3D knee MRI. •DL-based algorithm achieved better subjective image quality than conventional compressed sensing. •For 3D knee MRI at 3 T, 54% faster image acquisition may be possible.

Inflammatory Knee Synovitis: Evaluation of an Accelerated FLAIR Sequence Compared With Standard Contrast-Enhanced Imaging.

The aim of this study was to assess the diagnostic value and accuracy of a deep learning (DL)-accelerated fluid attenuated inversion recovery (FLAIR) sequence with fat saturation (FS) in patients with inflammatory synovitis of the knee. Patients with suspected knee synovitis were retrospectively included between January and September 2023. All patients underwent a 3 T knee magnetic resonance imaging including a DL-accelerated noncontrast FLAIR FS sequence (acquisition time: 1 minute 38 seconds) and a contrast-enhanced (CE) T1-weighted FS sequence (acquisition time: 4 minutes 50 seconds), which served as reference standard. All knees were scored by 2 radiologists using the semiquantitative modified knee synovitis score, effusion synovitis score, and Hoffa inflammation score. Diagnostic confidence, image quality, and image artifacts were rated on separate Likert scales. Wilcoxon signed rank test was used to compare the semiquantitative scores. Interreader and intrareader reproducibility were calculated using Cohen κ. Fifty-five patients (mean age, 52 ± 17 years; 28 females) were included in the study. Twenty-seven patients (49%) had mild to moderate synovitis (synovitis score 6-13), and 17 patients (31%) had severe synovitis (synovitis score >14). No signs of synovitis were detected in 11 patients (20%) (synovitis score <5). Semiquantitative assessment of the whole knee synovitis score showed no significant difference between the DL-accelerated FLAIR sequence and the CE T1-weighted sequence (mean FLAIR score: 10.69 ± 8.83, T1 turbo spin-echo FS: 10.74 ± 10.32; P = 0.521). Both interreader and intrareader reproducibility were excellent (range Cohen κ [0.82-0.96]). Assessment of inflammatory knee synovitis using a DL-accelerated noncontrast FLAIR FS sequence was feasible and equivalent to CE T1-weighted FS imaging.

Abstract B038: A preliminary study on predicting pathological complete response to neoadjuvant chemotherapy in triple-negative breast cancer

Abstract Purpose In this preliminary study, we are aiming to develop a deep learning model to predict pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) for triple-negative breast cancer (TNBC) patient based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Background Neoadjuvant chemotherapy (NAC) has become a grown treatment method for patients with triple-negative breast cancer (TNBC). However, not every patient can achieve pathological complete response (pCR) to NAC. NAC also has side effects such as nausea, hair loss, appetite loss, mouth sores, and nerve damage. Additionally, delaying surgery to remove the tumor can allow it to spread, making treatment more difficult. Therefore, it is necessary to predict pCR to NAC reliably in a non-invasive way. Deep learning methods, especially convolutional neural network (CNN), have been shown great success in image-based treatment response prediction. Methods In this preliminary study, totally 78 TNBC patients on DCE-MRI collected from public dataset (Duke University) were used, among which are 23 patients with pCR and 55 patients without pCR. For each patient, the median slice from the tumor area of the fat-saturated gradient echo T1-weighted pre-contrast sequence MRI was extracted. A convolutional neural network model was built to predict whether the patients receive pCR or not after NAC. In the constructed prediction model, three convolutional layers were used to capture the features from DCE-MRI. Each convolutional layer was followed by a max-pooling layer to reduce the dimensions of the feature maps. Two fully connected layers were added into the model so that the model has a binary outcome which provides the prediction of pCR. Additionally, “ReLU” was used as the activation function in all the layers except for the output layer which used “softmax” instead. By using augmentation technique, we solved the problems of small sample size and unbalance data. Results In this study, 75% dataset were used for training and the remaining 25% were used for testing. The model we developed has a 75% accuracy, with a sensitivity of 0.67 and a specificity of 0.79. These results indicate that the model performs well in predicting patients who do not achieve pathological complete response (pCR). Additionally, the area under the receiver operating characteristic (AUC) curve is calculated as 0.74, indicating the outstanding performance. Citation Format: Xi Chen, Zhiguo Zhou. A preliminary study on predicting pathological complete response to neoadjuvant chemotherapy in triple-negative breast cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B038.

Tendinous Signal Alterations on MRI in the Asymptomatic Elbow: A Retrospective Cross-Sectional Study.

It is clinically relevant to prevent overtreatment of tendinopathy diagnosed solely on imaging. Therefore, the prevalence of presumable asymptomatic signal changes in the common flexor origin, biceps insertion, brachialis insertion, and triceps insertion were assessed. Two hundred and five magnetic resonance imaging (MRI) exams of the elbow with coronal and axial fat-saturated fluid-sensitive sequences between January 1, 2018 and July 31, 2022 were retrospectively identified in our center.Two radiology residents reviewed the exams independently. The elbow tendons were given a score from 0 to 4. Score 0: no signal abnormality; score 1: increased T2-weighted signal around the tendon; score 2: increased T2-weighted signal compared to muscle within the tendon; score 3: partial tear; and score 4: complete tear. The common flexor tendon showed signal alterations in 8% of patients; nine patients had an increased signal around the tendon, and eight patients had an increased signal within the tendon. Three patients (1.5%) had an altered signal intensity in the biceps tendon. All triceps tendons showed a linear hyperintense signal, suggesting that it is physiological. There were no partial or complete tears. No signal abnormalities were noted in the brachialis tendon among all patients. The prevalence of presumable asymptomatic signal alterations seen in the common flexor origin on MRI is not negligible; therefore, clinical correlation is advised to prevent overtreatment of tendinopathy in these cases. No partial or complete tears were seen.

High contrast cartilaginous endplate imaging in spine using three dimensional dual-inversion recovery prepared ultrashort echo time (3D DIR-UTE) sequence

PurposeTo investigate the feasibility and application of a novel imaging technique, a three-dimensional dual adiabatic inversion recovery prepared ultrashort echo time (3D DIR-UTE) sequence, for high contrast assessment of cartilaginous endplate (CEP) imaging with head-to-head comparisons between other UTE imaging techniques.MethodThe DIR-UTE sequence employs two narrow-band adiabatic full passage (AFP) pulses to suppress signals from long T2 water (e.g., nucleus pulposus (NP)) and bone marrow fat (BMF) independently, followed by multispoke UTE acquisition to detect signals from the CEP with short T2 relaxation times. The DIR-UTE sequence, in addition to three other UTE sequences namely, an IR-prepared and fat-saturated UTE (IR-FS-UTE), a T1-weighted and fat-saturated UTE sequence (T1w-FS-UTE), and a fat-saturated UTE (FS-UTE) was used for MR imaging on a 3 T scanner to image six asymptomatic volunteers, six patients with low back pain, as well as a human cadaveric specimen. The contrast-to-noise ratio of the CEP relative to the adjacent structures—specifically the NP and BMF—was then compared from the acquired images across the different UTE sequences.ResultsFor asymptomatic volunteers, the DIR-UTE sequence showed significantly higher contrast-to-noise ratio values between the CEP and BMF (CNRCEP-BMF) (19.9 ± 3.0) and between the CEP and NP (CNRCEP-NP) (23.1 ± 1.7) compared to IR-FS-UTE (CNRCEP-BMF: 17.3 ± 1.2 and CNRCEP-NP: 19.1 ± 1.8), T1w-FS-UTE (CNRCEP-BMF: 9.0 ± 2.7 and CNRCEP-NP: 10.4 ± 3.5), and FS-UTE (CNRCEP-BMF: 7.7 ± 2.2 and CNRCEP-NP: 5.8 ± 2.4) for asymptomatic volunteers (all P-values < 0.001). For the spine sample and patients with low back pain, the DIR-UTE technique detected abnormalities such as irregularities and focal defects in the CEP regions.ConclusionThe 3D DIR-UTE sequence is able to provide high-contrast volumetric CEP imaging for human spines on a clinical 3 T scanner.

Haemorrhagic pituitary adenoma

Intra tumoral haemorrhage occurs frequently in pituitary macro adenomas. It can either manifest as pituitary apoplexy [1], a life threatening condition with sudden onset of headaches, nausea and vomiting; or as a silent recent or old haemorrhage. In the latter, like in our case, MR imaging is best to delineate these haemorrhagic changes. In fact, typical features are T1 and T2 hyperintensity (Figure 1A &amp; 1B), persisting in fat saturated sequences (Figure 1C) with peripheral enhancement (Figure 1D). Usually a subsequent cystic change occurs, responsible for a fluid-fluid level (Figure 1E). Among the differential diagnosis of supra sellar masses, cystic craniopharyngiomas typically have calcifications although better appreciated on CT and a vividly enhancing solid component. Arachnoid cysts are very thin walled cystic supra sellar lesions with no solid or enhancing component, usually extending superiorly to the third ventricle and can be causing obstructive hydrocephalus. Rathke cleft cyst remains the most challenging differential, recent efforts were made to help make the correct diagnosis [2]. In that matter the classic appearance of a midline sellar and supra sellar lesion with fluid-fluid level, haemorrhagic changes and a T2 hypointense rim (Figure 1E) clinches the diagnosis of a haemorrhagic pituitary macroadenoma.

Clinical outcomes of 3T magnetic resonance imaging-guided lumbar and sacral foraminal injections

PurposeThis article evaluates the feasibility, safety, and efficacy of MRI-guided lumbar or sacral nerve root infiltration for chronic back pain. We compared the outcomes of our MRI-guided infiltrations with data from CT-guided infiltrations reported in the literature and explored the potential advantages of MRI guidance.MethodForty-eight MRI-guided nerve root infiltrations were performed using a 3 T MRI machine. The optimal needle path was determined using breathhold T2-weighted sequences, and the needle was advanced under interleaved guidance based on breathhold PD-weighted images. Pain levels were assessed using a numeric rating scale (NRS) before the procedure and up to 5 months after, during follow-up. Procedure success was evaluated by comparing patients’ pain levels before and after the infiltration.ResultsThe MRI-guided infiltrations yielded pain reduction 1 week after the infiltration in 92% of cases, with an average NRS substantial change of 3.9 points. Pain reduction persisted after 5 months for 51% of procedures. No procedure-related complications occurred. The use of a 22G needle and reconstructed subtraction images from T2 FatSat sequences improved the workflow.ConclusionOur study showed that MRI-guided nerve root infiltration is a feasible, safe, and effective treatment option for chronic back pain. Precise positioning of the needle tip and accurate distribution of the injected solution contributed to the effectiveness of MRI-guided infiltration, which appeared to be as accurate as CT-guided procedures. Further research is needed to explore the potential benefits of metal artifact reduction sequences to optimize chronic back pain management.

“Bone marrow edema” in the differential diagnosis of traumatic injuries of the knee

Bone marrow edema is MR images is defined by the presence of hypointense infiltration on T1-weighted images and clear high signal intensity on fat-saturated T2-weighted sequences (T2 FSE FAT SATURATED, T2-weighted short-tau inversion recovery (T2w-STIR)).Aim: To demonstrate the features of manifestation of “bone marrow edema” at different severity and character of traumatic injury of the knee.Materials and Methods. A series of clinical cases with subchondral bone involvement in the form of “bone marrow edema” resulting from trauma is presented using the example of the knee joint as the most common area of MRI for differential diagnosis.Results. The features of “marrow edema” of the femoral and tibial condyles were analyzed using clinical examples. It was shown that the severity and nature of injury can be judged by the nature of the edema, presence of linear hypointensities, articular surface deforms and the bone defects.Conclusion. Evaluation of “bone marrow edema” revealed on MRI examination in case of pain syndrome after a knee joint injury allows timely clarification of the diagnosis and adequate treatment.

Penggunaan T2 STIR dan Fat Saturation pada Pemeriksaan MRI Lumbal Kasus Hernia Nucleus Pulposus (HNP)

Background: Signal to noise ratio (SNR) is defined as the ratio of the amplitude of the signal received by the coil to the amplitude of the noise. Methods: This research was quantitative alongside an observational approach conducted at the Radiology Installation of Satya Negara Hospital, North Jakarta. Alongside a research population of Lumbar MRI patients with HNP clinical indication from October to November 2022. The research sample was ten patients aged around 25-50 years with a diagnosis of HNP. Furthermore, an MRI examination was carried out using T2 STIR and T2 Fat Saturation sequences. Hence, the results of the Lumbar MRI image were ROI performed on common areas alongside the Corpus, Discus, CSF, Spinal Cord, and HNP area. Results: This research showed there was a significant difference in SNR values in the T2 STIR and T2 Fat Saturation sequences in common areas with a p-value of 0.05. There was no significant difference in SNR values in the HNP-experienced area with a p-value of 0.05. Conclusions: After a statistical test using the Paired Sample T Test, the test results obtained were p value 0.05, namely 0.692 for the SNR value on the results of the MRI Lumbar sagittal section of the sequence T2 STIR and T2 Fat saturation in the Lumbar area experiencing HNP, which means that Ho was accepted, which means that there was no significant difference in SNR values between the T2 STIR and T2 Fat saturation sequences in the lumbar tissue that experienced HNP. 2. The SNR value of MRI images of the lumbar sagittal section of the sequence T2 STIR and T2 Fat saturation in normal lumbar tissue including Corpus, Discus, CSF, the test results obtained are p-value 0.05. This means that Ho was rejected, which means there was a significant difference in SNR values between the T2 STIR and T2 Fat saturation sequences. In the spinal cord area, the test results obtained were p value 0.05. This meant that Ho was accepted, which meant there was no significant difference in SNR values between the T2 STIR and T2 Fat saturation sequences.

Diagnosis and monitoring denosumab therapy of giant cell tumors of bone: radiologic-pathologic correlation.

To determine the value of CT and dynamic contrast-enhanced (DCE-)MRI for monitoring denosumab therapy of giant cell tumors of bone (GCTB) by correlating it to histopathology. Patients with GCTB under denosumab treatment and monitored with CT and (DCE-)MRI (2012-2021) were retrospectively included. Imaging and (semi-)quantitative measurements were used to assess response/relapse. Tissue samples were analyzed using computerized segmentation for vascularization and number of neoplastic and giant cells. Pearson's correlation/Spearman's rank coefficient and Kruskal-Wallis tests were used to assess correlations between histopathology and radiology. Six patients (28 ± 8years; five men) were evaluated. On CT, good responders showed progressive re-ossification (+7.8HU/month) and cortical remodeling (woven bone). MRI showed an SI decrease relative to muscle on T1-weighted (-0.01 A.U./month) and on fat-saturated T2-weighted sequences (-0.03 A.U./month). Time-intensity-curves evolved from a type IV with high first pass, high amplitude, and steep wash-out to a slow type II. An increase in time-to-peak (+100%) and a decrease in Ktrans (-71%) were observed. This is consistent with microscopic examination, showing a decrease of giant cells (-76%), neoplastic cells (-63%), and blood vessels (-28%). There was a strong statistical significant inverse correlation between time-to-peak and microvessel density (ρ = -0.9, p = 0.01). Significantly less neoplastic (p = 0.03) and giant cells (p = 0.04) were found with a time-intensity curve type II, compared to a type IV. Two patients showed relapse after initial good response when stopping denosumab. Inverse imaging and pathological findings were observed. CT and (DCE-)MRI show a good correlation with pathology and allow adequate evaluation of response to denosumab and detection of therapy failure.

Comparison of a STIR- and T1-based radiomics model to differentiate between plexiform neurofibromas and malignant peripheral nerve sheath tumors in neurofibromatosis type 1 (NF1) (S17.010)

Comparison of a STIR- and T1-based radiomics model to differentiate between plexiform neurofibromas and malignant peripheral nerve sheath tumors in neurofibromatosis type 1 (NF1) (S17.010)

A deep learning-based reconstruction approach for accelerated magnetic resonance image of the knee with compressed sense: evaluation in healthy volunteers

To evaluate the feasibility of combining compressed sense (CS) with a newly developed deep learning-based algorithm (CS-AI) using convolutional neural networks to accelerate 2D MRI of the knee. In this prospective study, 20 healthy volunteers were scanned with a 3T MRI scanner. All subjects received a fat-saturated sagittal 2D proton density reference sequence without acceleration and four additional acquisitions with different acceleration levels: 2, 3, 4 and 6. All sequences were reconstructed with the conventional CS and a new CS-AI algorithm. Two independent, blinded readers rated all images by seven criteria (overall image impression, visible artifacts, delineation of anterior ligament, posterior ligament, menisci, cartilage, and bone) using a 5-point Likert scale. Signal- and contrast-to-noise ratios were calculated. Subjective ratings and quantitative metrics were compared between CS and CS-AI with similar acceleration levels and between all CS/CS-AI images and the non-accelerated reference sequence. Friedman and Dunn´s multiple comparison tests were used for subjective, ANOVA and the Tukey Kramer test for quantitative metrics. Conventional CS images at the lowest acceleration level (CS2) were already rated significantly lower than reference for 6/7 criteria. CS-AI images maintained similar image quality to the reference up to CS-AI three for all criteria, which would allow for a reduction in scan time of 64% with unchanged image quality compared to the unaccelerated sequence. SNR and CNR were significantly higher for all CS-AI reconstructions compared to CS (all p < 0.05). AI-based image reconstruction showed higher image quality than CS for 2D knee imaging. Its implementation in the clinical routine yields the potential for faster MRI acquisition but needs further validation in non-healthy study subjects. Combining compressed SENSE with a newly developed deep learning-based algorithm using convolutional neural networks allows a 64% reduction in scan time for 2D imaging of the knee. Implementation of the new deep learning-based algorithm in clinical routine in near future should enable better image quality/resolution with constant scan time, or reduced acquisition times while maintaining diagnostic quality.

Quantitative MR Neurography in Multifocal Motor Neuropathy and Amyotrophic Lateral Sclerosis

The aim of this study was to assess the phenotype of multifocal motor neuropathy (MMN) and amyotrophic lateral sclerosis (ALS) in quantitative MR neurography. In this prospective study, 22 patients with ALS, 8 patients with MMN, and 10 healthy volunteers were examined with 3T MR neurography, using a high-resolution fat-saturated T2-weighted sequence, diffusion-tensor imaging (DTI), and a multi-echo T2-relaxometry sequence. The quantitative biomarkers fractional anisotropy (FA), radial and axial diffusivity (RD, AD), mean diffusivity (MD), cross-sectional area (CSA), T2-relaxation time, and proton spin density (PSD) were measured in the tibial nerve at the thigh and calf, and in the median, radial, and ulnar nerves at the mid-upper arm. MMN showed a characteristic imaging pattern of decreased FA (p = 0.018), increased RD (p = 0.014), increased CSA (p < 0.001), increased T2-relaxation time (p < 0.001), and increased PSD (p = 0.025) in the upper arm nerves compared to ALS and controls. ALS patients did not differ from controls in any imaging marker, nor were there any group differences in the tibial nerve (p > 0.05). MMN shows a characteristic pattern of quantitative DTI and T2-relaxometry parameters in the upper-arm nerves, primarily indicating demyelination. Peripheral nerve changes in ALS seem to be below the detection level of current state-of-the-art quantitative MR neurography.

Synthetic T2-weighted fat sat based on a generative adversarial network shows potential for scan time reduction in spine imaging in a multicenter test dataset

ObjectivesT2-weighted (w) fat sat (fs) sequences, which are important in spine MRI, require a significant amount of scan time. Generative adversarial networks (GANs) can generate synthetic T2-w fs images. We evaluated the potential of synthetic T2-w fs images by comparing them to their true counterpart regarding image and fat saturation quality, and diagnostic agreement in a heterogenous, multicenter dataset.MethodsA GAN was used to synthesize T2-w fs from T1- and non-fs T2-w. The training dataset comprised scans of 73 patients from two scanners, and the test dataset, scans of 101 patients from 38 multicenter scanners. Apparent signal- and contrast-to-noise ratios (aSNR/aCNR) were measured in true and synthetic T2-w fs. Two neuroradiologists graded image (5-point scale) and fat saturation quality (3-point scale). To evaluate whether the T2-w fs images are indistinguishable, a Turing test was performed by eleven neuroradiologists. Six pathologies were graded on the synthetic protocol (with synthetic T2-w fs) and the original protocol (with true T2-w fs) by the two neuroradiologists.ResultsaSNR and aCNR were not significantly different between the synthetic and true T2-w fs images. Subjective image quality was graded higher for synthetic T2-w fs (p = 0.023). In the Turing test, synthetic and true T2-w fs could not be distinguished from each other. The intermethod agreement between synthetic and original protocol ranged from substantial to almost perfect agreement for the evaluated pathologies.DiscussionThe synthetic T2-w fs might replace a physical T2-w fs. Our approach validated on a challenging, multicenter dataset is highly generalizable and allows for shorter scan protocols.Key Points• Generative adversarial networks can be used to generate synthetic T2-weighted fat sat images from T1- and non-fat sat T2-weighted images of the spine.• The synthetic T2-weighted fat sat images might replace a physically acquired T2-weighted fat sat showing a better image quality and excellent diagnostic agreement with the true T2-weighted fat images.• The present approach validated on a challenging, multicenter dataset is highly generalizable and allows for significantly shorter scan protocols.