A Holistic Approach to CT Protocol and Dose Management.

PURPOSE: Challenges from administrative support, scanners' heterogeneity, patient size variation, and protocol mapping hinder CT protocol and dose management. We present a holistic approach to overcome these challenges. METHODS: A dose tracking software was selected with two key requirements: intelligent protocol mapping and customizable dose threshold settings according to the patient size. A multifaceted workflow was carefully implemented. It included patient size-dependent dose thresholds for e-mail alerts, a base protocol archive on a website with a unified format using an in-house developed reformat software upon protocol export, prompt dose alert follow-up, and well-controlled protocol changes. The thresholds were iteratively updated following protocol changes or review of dose statistics. The program outcome was evaluated using 11 protocols from January 2020 to May 2023 (N = 148,678) in comparison to ACR's achievable dose (AD) and dose reference levels (DRLs). RESULTS: The 75th percentile dose data were lower than the ACR's DRL on average, ranging from -4.9% to -36%. The median doses were in a range of -23% to 19% on average in comparison with the ACR's AD. The median value from pulmonary embolism scans initially showed 36% higher than the AD but was gradually reduced to nearly 3% lower than the AD. The percentage of unjustified alerted cases decreased from 80% in first half year of 2020 to 17% in the first 5 months of 2023. CONCLUSIONS: The results showed that our holistic approach to protocol and dose management has been effective. The impact to practice has been prompt and sustainable.

Opportunistic CT Screening-Machine Learning Algorithm Identifies Majority of Vertebral Compression Fractures: A Cohort Study.

Vertebral compression fractures (VCF) are common in patients older than 50 years but are often undiagnosed. Zebra Medical Imaging developed a VCF detection algorithm, with machine learning, to detect VCFs from CT images of the chest and/or abdomen/pelvis. In this study, we evaluated the diagnostic performance of the algorithm in identifying VCF. We conducted a blinded validation study to estimate the operating characteristics of the algorithm in identifying VCFs using previously completed CT scans from 1200 women and men aged 50 years and older at a tertiary-care center. Each scan was independently evaluated by two of three neuroradiologists to identify and grade VCF. Disagreements were resolved by a senior neuroradiologist. The algorithm evaluated the CT scans in a separate workstream. The VCF algorithm was not able to evaluate CT scans for 113 participants. Of the remaining 1087 study participants, 588 (54%) were women. Median age was 73 years (range 51-102 years; interquartile range 66-81). For the 1087 algorithm-evaluated participants, the sensitivity and specificity of the VCF algorithm in diagnosing any VCF were 0.66 (95% confidence interval [CI] 0.59-0.72) and 0.90 (95% CI 0.88-0.92), respectively, and for diagnosing moderate/severe VCF were 0.78 (95% CI 0.70-0.85) and 0.87 (95% CI 0.85-0.89), respectively. Implementing this VCF algorithm within radiology systems may help to identify patients at increased fracture risk and could support the diagnosis of osteoporosis and facilitate appropriate therapy. © 2023 Amgen, Inc. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems.

OBJECTIVE: We aimed to evaluate the effectiveness of utilizing artificial intelligence (AI) to quantify the extent of pneumonia from chest CT scans, and to determine its ability to predict clinical deterioration or mortality in patients admitted to the hospital with COVID-19 in comparison to semi-quantitative visual scoring systems. METHODS: A deep-learning algorithm was utilized to quantify the pneumonia burden, while semi-quantitative pneumonia severity scores were estimated through visual means. The primary outcome was clinical deterioration, the composite end point including admission to the intensive care unit, need for invasive mechanical ventilation, or vasopressor therapy, as well as in-hospital death. RESULTS: The final population comprised 743 patients (mean age 65  ±â€¯ 17 years, 55% men), of whom 175 (23.5%) experienced clinical deterioration or death. The area under the receiver operating characteristic curve (AUC) for predicting the primary outcome was significantly higher for AI-assisted quantitative pneumonia burden (0.739, p = 0.021) compared with the visual lobar severity score (0.711, p < 0.001) and visual segmental severity score (0.722, p = 0.042). AI-assisted pneumonia assessment exhibited lower performance when applied for calculation of the lobar severity score (AUC of 0.723, p = 0.021). Time taken for AI-assisted quantification of pneumonia burden was lower (38 ± 10 s) compared to that of visual lobar (328 ± 54 s, p < 0.001) and segmental (698 ± 147 s, p < 0.001) severity scores. CONCLUSION: Utilizing AI-assisted quantification of pneumonia burden from chest CT scans offers a more accurate prediction of clinical deterioration in patients with COVID-19 compared to semi-quantitative severity scores, while requiring only a fraction of the analysis time. ADVANCES IN KNOWLEDGE: Quantitative pneumonia burden assessed using AI demonstrated higher performance for predicting clinical deterioration compared to current semi-quantitative scoring systems. Such an AI system has the potential to be applied for image-based triage of COVID-19 patients in clinical practice.

Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional long short-term memory networks.

Purpose: Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in coronavirus disease 2019 (COVID-19) patients but are not part of clinical routine because the required manual segmentation of lung lesions is prohibitively time consuming. We aim to automatically segment ground-glass opacities and high opacities (comprising consolidation and pleural effusion). Approach: We propose a new fully automated deep-learning framework for fast multi-class segmentation of lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional long short-term memory (ConvLSTM) networks. Utilizing the expert annotations, model training was performed using five-fold cross-validation to segment COVID-19 lesions. The performance of the method was evaluated on CT datasets from 197 patients with a positive reverse transcription polymerase chain reaction test result for SARS-CoV-2, 68 unseen test cases, and 695 independent controls. Results: Strong agreement between expert manual and automatic segmentation was obtained for lung lesions with a Dice score of 0.89 ± 0.07 ; excellent correlations of 0.93 and 0.98 for ground-glass opacity (GGO) and high opacity volumes, respectively, were obtained. In the external testing set of 68 patients, we observed a Dice score of 0.89 ± 0.06 as well as excellent correlations of 0.99 and 0.98 for GGO and high opacity volumes, respectively. Computations for a CT scan comprising 120 slices were performed under 3 s on a computer equipped with an NVIDIA TITAN RTX GPU. Diagnostically, the automated quantification of the lung burden % discriminate COVID-19 patients from controls with an area under the receiver operating curve of 0.96 (0.95-0.98). Conclusions: Our method allows for the rapid fully automated quantitative measurement of the pneumonia burden from CT, which can be used to rapidly assess the severity of COVID-19 pneumonia on chest CT.

Decreased Hospital Length of Stay for ICH and PE after Adoption of an Artificial Intelligence-Augmented Radiological Worklist Triage System.

The purpose of the study was to determine whether there was a difference in the length of stay (LOS) for inpatients diagnosed with intracranial hemorrhage (ICH) or pulmonary embolism (PE) prior to and following implementation of an (AI) triage software. A retrospective review was performed for patients that underwent CT imaging procedures related to ICH and PE from April 2016 to October 2019. All patient encounters that included noncontrast head computed tomography (CT) or CT chest angiogram (CTCA) procedures, identified by the DICOM study descriptions, from April 2016 to April 2019 were included for ICH and PE, respectively. All patients that were diagnosed with ICH or PE were identified using ICD9 and ICD10 codes. Three separate control groups were defined as follows: (i) all remaining patients that underwent the designated imaging studies, (ii) patients diagnosed with hip fractures, and (iii) all hospital wide encounters, during the study period. Pre-AI and post-AI time periods were defined around the deployment dates of the ICH and PE modules, respectively. The reduction in LOS was 1.30 days (95% C.I. 0.1-2.5), resulting in an observed percentage decrease of 11.9% (p value = 0.032), for ICH and 2.07 days (95% C.I. 0.1-4.0), resulting in an observed percentage decrease of 26.3% (p value = 0.034), for PE when comparing the pre-AI and post-AI time periods. Reductions in LOS were observed in the ICH pre-AI and post-AI time period group for patients that were not diagnosed with ICH, but that underwent related imaging, 0.46 days (95% C.I. 0.1-0.8) resulting in an observed percentage decrease of 5% (p value = 0.018), and inpatients that were diagnosed with hip fractures, 0.60 days (95% C.I. 0.1-1.2) resulting in an observed percentage decrease of 8.3% (p value = 0.004). No other significant decrease in length of stay was observed in any of the other patient groups. The introduction of computer-aided triage and prioritization software into the radiological workflow was associated with a significant decrease in length of stay for patients diagnosed with ICH and PE.

Utility of True Fast Imaging with Steady-State Precession in Detecting Arachnoid Veils of the Posterior Fossa.

INTRODUCTION: Arachnoid membranes are well recognized as a cause of cerebrospinal fluid (CSF) flow impairment in disorders such as obstructive hydrocephalus and syringohydromyelia, but can be difficult to detect with standard noninvasive imaging techniques. True fast imaging with steady-state precession (TrueFISP) can exhibit brain pulsations and CSF dynamics with high spatiotemporal resolution. Here, we demonstrate the utility of this technique in the diagnosis and management of arachnoid membranes in the posterior fossa. CASE PRESENTATIONS: Three symptomatic children underwent cine TrueFISP imaging for suspicion of CSF membranous obstruction. Whereas standard imaging failed to or did not clearly visualize the site of an obstructive lesion, preoperative TrueFISP identified a membrane in all 3 cases. The membranes were confirmed intraoperatively, and postoperative TrueFISP helped verify adequate marsupialization and recommunication of CSF flow. Two out of the 3 cases showed a decrease in cerebellar tonsillar pulsatility following surgery. All children showed symptomatic improvement. CONCLUSION: TrueFISP is able to detect pulsatile arachnoid membranes responsible for CSF outflow obstruction that are otherwise difficult to visualize using standard imaging techniques. We advocate use of this technology in pre- and postsurgical decision-making as it provides a more representative image of posterior fossa pathology and contributes to our understanding of CSF flow dynamics. There is potential to use this technology to establish prognostic biomarkers for disorders of CSF hydrodynamics.

Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional LSTM networks.

Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in Coronavirus disease 2019 (COVID-19) patients, but are not part of the clinical routine since required manual segmentation of lung lesions is prohibitively time-consuming. We propose a new fully automated deep learning framework for quantification and differentiation between lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional Long Short-Term Memory (LSTM) networks. Utilizing the expert annotations, model training was performed using 5-fold cross-validation to segment ground-glass opacity and high opacity (including consolidation and pleural effusion). The performance of the method was evaluated on CT data sets from 197 patients with positive reverse transcription polymerase chain reaction test result for SARS-CoV-2. Strong agreement between expert manual and automatic segmentation was obtained for lung lesions with a Dice score coefficient of 0.876 ± 0.005; excellent correlations of 0.978 and 0.981 for ground-glass opacity and high opacity volumes. In the external validation set of 67 patients, there was dice score coefficient of 0.767 ± 0.009 as well as excellent correlations of 0.989 and 0.996 for ground-glass opacity and high opacity volumes. Computations for a CT scan comprising 120 slices were performed under 2 seconds on a personal computer equipped with NVIDIA Titan RTX graphics processing unit. Therefore, our deep learning-based method allows rapid fully-automated quantitative measurement of pneumonia burden from CT and may generate the big data with an accuracy similar to the expert readers.

EGFR/ErbB2-Targeting Lapatinib Therapy for Aggressive Prolactinomas.

CONTEXT: Approximately 10% to 20% of prolactinomas are resistant to dopamine agonist therapy. The ErbB signaling pathway may drive aggressive prolactinoma behavior. OBJECTIVE: We evaluated lapatinib, an ErbB1-epidermal growth factor receptor (EGFR)/ErbB2 or human EGFR2 (HER2) tyrosine kinase inhibitor (TKI), in aggressive prolactinomas. DESIGN: A prospective, phase 2a multicenter trial was conducted. SETTING: This study took place at a tertiary referral pituitary center. PATIENTS: Study participants included adults with aggressive prolactinomas showing continued tumor growth despite maximally tolerated dopamine agonist therapy. INTERVENTION: Intervention included oral lapatinib 1250 mg/day for 6 months. MAIN OUTCOME MEASURES: The primary end point was 40% reduction in any tumor dimension assessed by magnetic resonance imaging at study end; tumor response was assessed by Response Evaluation Criteria in Solid Tumors criteria. Secondary end points included prolactin (PRL) reduction, correlation of response with EGFR/HER2 expression, and safety. RESULTS: Owing to rigorous inclusion criteria, of 24 planned participants, only 7 consented and 4 were treated. None achieved the primary end point but 3 showed stable disease, including 2 with a 6% increase and 1 with a 16.8% decrease in tumor diameter. PRL response was not always concordant with tumor response, as 2 showed 28% and 59% increases in PRL. The fourth participant had a PRL-secreting carcinoma and withdrew after 3 months of lapatinib because of imaging and PRL progression. EGFR/HER2 expression did not correlate with treatment response. Lapatinib was well tolerated overall, with reversible grade 1 transaminitis in 2 patients, grade 2 rash in 2 patients, and grade 1 asymptomatic bradycardia in 2 patients. CONCLUSIONS: An oral TKI such as lapatinib may be an effective option for a difficult-to-treat patient with an aggressive prolactinoma.

Epicardial adipose tissue is associated with extent of pneumonia and adverse outcomes in patients with COVID-19.

AIM: We sought to examine the association of epicardial adipose tissue (EAT) quantified on chest computed tomography (CT) with the extent of pneumonia and adverse outcomes in patients with coronavirus disease 2019 (COVID-19). METHODS: We performed a post-hoc analysis of a prospective international registry comprising 109 consecutive patients (age 64 ±â€¯16 years; 62% male) with laboratory-confirmed COVID-19 and noncontrast chest CT imaging. Using semi-automated software, we quantified the burden (%) of lung abnormalities associated with COVID-19 pneumonia. EAT volume (mL) and attenuation (Hounsfield units) were measured using deep learning software. The primary outcome was clinical deterioration (intensive care unit admission, invasive mechanical ventilation, or vasopressor therapy) or in-hospital death. RESULTS: In multivariable linear regression analysis adjusted for patient comorbidities, the total burden of COVID-19 pneumonia was associated with EAT volume (ß = 10.6, p = 0.005) and EAT attenuation (ß = 5.2, p = 0.004). EAT volume correlated with serum levels of lactate dehydrogenase (r = 0.361, p = 0.001) and C-reactive protein (r = 0.450, p < 0.001). Clinical deterioration or death occurred in 23 (21.1%) patients at a median of 3 days (IQR 1-13 days) following the chest CT. In multivariable logistic regression analysis, EAT volume (OR 5.1 [95% CI 1.8-14.1] per doubling p = 0.011) and EAT attenuation (OR 3.4 [95% CI 1.5-7.5] per 5 Hounsfield unit increase, p = 0.003) were independent predictors of clinical deterioration or death, as was total pneumonia burden (OR 2.5, 95% CI 1.4-4.6, p = 0.002), chronic lung disease (OR 1.3 [95% CI 1.1-1.7], p = 0.011), and history of heart failure (OR 3.5 [95% 1.1-8.2], p = 0.037). CONCLUSIONS: EAT measures quantified from chest CT are independently associated with extent of pneumonia and adverse outcomes in patients with COVID-19, lending support to their use in clinical risk stratification.

Improvement in ventriculomegaly following cervicomedullary decompressive surgery in children with achondroplasia and foramen magnum stenosis.

The role of cervicomedullary decompression (CMD) in the care of hydrocephalic achondroplastic children who present with simultaneous foramen magnum stenosis is not well understood. We sought to determine the percentage of symptomatic achondroplastic children with foramen magnum stenosis who had stabilization or improvement in ventriculomegaly following CMD. The authors retrospectively reviewed the records of pediatric patients at Cedars-Sinai Medical Center with achondroplasia and signs of progressive ventriculomegaly who underwent CMD for symptomatic foramen magnum stenosis between the years 2000 and 2018. Clinical outcomes included changes in fontanelle characteristics, head circumference (HC) percentile, and incidence of ventriculoperitoneal (VP) shunting. Radiographic outcomes measured included changes in Evans ratio. We excluded individuals who were shunted before CMD from our study. Sixteen children presented with symptomatic foramen magnum stenosis and full anterior fontanelle or jump in the HC percentiles. Two children underwent placement of a VP shunt before decompressive surgery and were excluded from further analysis. Of the remaining 14 children who underwent CMD, 13 (93%) showed softening or flattening of their fontanelles post-operatively. Ten of these 14 children had both pre- and post-operative HC percentile records available, with 8 showing increasing HC percentiles before surgery. Seven of those eight children (88%) showed a deceleration or stabilization of HC growth velocity following decompression of the foramen magnum. Among 10 children with available pre- and post-operative brain imaging, ventricular size improved in 5 (50%), stabilized in 2 (20%), and slightly increased in 3 (30%) children after decompression. Two children (14%) required a shunt despite decompression of the foramen magnum. A significant proportion of children with concomitant signs of raised intracranial pressure or findings of progressive ventriculomegaly and foramen magnum stenosis may have improvement or stabilization of these findings following CMD. CMD may decrease the need for VP shunting and its associated complications in the select group of hydrocephalic children with achondroplasia presenting with symptomatic foramen magnum stenosis.

Quantitative Burden of COVID-19 Pneumonia on Chest CT Predicts Adverse Outcomes: A Post-Hoc Analysis of a Prospective International Registry.

PURPOSE: To examine the independent and incremental value of CT-derived quantitative burden and attenuation of COVID-19 pneumonia for the prediction of clinical deterioration or death. METHODS: This was a retrospective analysis of a prospective international registry of consecutive patients with laboratory-confirmed COVID-19 and chest CT imaging, admitted to four centers between January 10 and May 6, 2020. Total burden (expressed as a percentage) and mean attenuation of ground glass opacities (GGO) and consolidation were quantified from CT using semi-automated research software. The primary outcome was clinical deterioration (intensive care unit admission, invasive mechanical ventilation, or vasopressor therapy) or in-hospital death. Logistic regression was performed to assess the predictive value of clinical and CT parameters for the primary outcome. RESULTS: The final population comprised 120 patients (mean age 64 ± 16 years, 78 men), of whom 39 (32.5%) experienced clinical deterioration or death. In multivariable regression of clinical and CT parameters, consolidation burden (odds ratio [OR], 3.4; 95% confidence interval [CI]: 1.7, 6.9 per doubling; P = .001) and increasing GGO attenuation (OR, 3.2; 95% CI: 1.3, 8.3 per standard deviation, P = .02) were independent predictors of deterioration or death; as was C-reactive protein (OR, 2.1; 95% CI: 1.3, 3.4 per doubling; P = .004), history of heart failure (OR 1.3; 95% CI: 1.1, 1.6, P = .01), and chronic lung disease (OR, 1.3; 95% CI: 1.0, 1.6; P = .02). Quantitative CT measures added incremental predictive value beyond a model with only clinical parameters (area under the curve, 0.93 vs 0.82, P = .006). The optimal prognostic cutoffs for burden of COVID-19 pneumonia as determined by Youden's index were consolidation of greater than or equal to 1.8% and GGO of greater than or equal to 13.5%. CONCLUSIONS: Quantitative burden of consolidation or GGO on chest CT independently predict clinical deterioration or death in patients with COVID-19 pneumonia. CT-derived measures have incremental prognostic value over and above clinical parameters, and may be useful for risk stratifying patients with COVID-19.

Rebound high-pressure headache after treatment of spontaneous intracranial hypotension: MRV study.

BACKGROUND: Rebound high-pressure headaches may complicate treatment of spontaneous intracranial hypotension (SIH), but no comprehensive study of such patients has been reported and little is known about its frequency and risk factors. We therefore studied patients undergoing treatment for SIH and performed magnetic resonance venography (MRV) to assess for cerebral venous sinus stenosis, a risk factor for idiopathic intracranial hypertension. METHODS: We studied a consecutive group of patients who underwent treatment for SIH. Rebound high-pressure headache was defined as a reverse orthostatic headache responsive to acetazolamide. MRV was obtained in all patients and lateral sinus stenosis was scored according to the system published by Higgins et al., with 0 being normal and 4 signifying bilateral signal gaps. RESULTS: The mean age of the 46 men and 67 women was 45.9 years (range 13-71 years) at the time of onset of SIH. Rebound high-pressure headache was diagnosed in 31 patients (27.4%); 14% of patients with an MRV score of 0, 24% with a score of 1, and 46% with a score of 2 or 3 (p = 0.0092). Also, compared to SIH patients who did not develop rebound high-pressure headaches (n = 82), those with rebound high-pressure headaches were younger, more often female, and more often had an extradural CSF collection on spinal imaging. CONCLUSIONS: Rebound high-pressure headache occurs in about one-fourth of patients following treatment of SIH and is more common in those with restriction of cerebral venous outflow.

Pituitary Imaging.

Modern pituitary imaging is MRI. However, computed tomography (CT) still has limited usefulness. In addition, because CT offers much better bone detail and calcium detection, there are some cases in which such additional information is necessary. Before the advent of CT, plain radiography, pneumoencephalography, and angiography were used to diagnose pituitary masses. More recently, CT, and then especially MRI, made it possible to primarily delineate lesions within and around the pituitary gland rather than depend on secondary information that could only suggest their presence.

Sellar and clival plasmacytomas: case series of 5 patients with systematic review of 65 published cases.

PURPOSE: Parasellar plasmacytomas are rare tumors localized to the sellar region arising from plasma cells. Knowledge of clinical, imaging, surgical, and pathological characteristics is limited to single case reports. METHODS: A retrospective analysis of five primary cases was conducted, followed by systematic review of English language articles using PubMed in accordance with PRISMA guidelines. RESULTS: Five primary case patients include four men and one woman, ages 60-77, followed up to 3 years. A systematic review identified 65 additional patients, of whom 65% presented with cranial nerve palsies and 15% with hypopituitarism. Sixteen percent had history of known multiple myeloma (MM) while 37% were diagnosed concurrently with MM on presentation of parasellar plasmacytoma. Imaging showed median tumor size of 38 mm (range, 4-70 mm), with MRI intensity similar to that of other sellar masses. Surgical biopsy with immunohistochemical studies confirmed plasmacytoma diagnosis. Eighty-one percent underwent parasellar radiotherapy, and chemotherapy initiated in 59% of the 69 patients with MM. Overall survival rate was 74% at follow-up (median 12 months), with 18% having parasellar recurrences and 38% progressing to systemic MM after presentation of a solitary plasmacytoma (median 3 months). CONCLUSIONS: Parasellar plasmacytomas are rare tumors that should be considered in the differential diagnosis for lesions involving the sella and arising from the clivus, especially when cranial nerve paresis is apparent, even in the absence of known MM. Although recurrence rates for parasellar plasmacytoma is low, patients should be monitored for progression to MM. Treatment depends on the presence of systemic disease at diagnosis.

Sporadic Hemangioblastoma Arising from the Infundibulum.

Hemangioblastomas are rare vascular tumors most often found in the posterior fossa and cervical spinal cord and commonly associated with von Hippel-Lindau Disease. We report a case of sporadic hemangioblastoma in a patient without von Hippel-Lindau Disease. Imaging characteristics included a solid, suprasellar mass that was homogeneously enhancing. These findings most resembled a pituicytoma or choroid glioma because of the close association with the infundibulum and the homogeneous avid enhancement. Microscopically, the neoplasm was seen to be composed of vascular channels associated with foamy stromal cells, containing clear cytoplasmic vacuoles. Microscopic and immunohistochemical findings were consistent with hemangioblastoma. Hemangioblastomas are a rare form of vascular tumor most commonly associated with von-Hippel Lindau disease. Our finding of non-cystic hemangioblastoma arising from the infundibulum demonstrates that, while rare, hemangioblastomas should be considered on the differential diagnosis for an avidly enhancing suprasellar mass.

Quantitative chemical exchange saturation transfer MRI of intervertebral disc in a porcine model.

PURPOSE: Previous studies have associated low pH in intervertebral discs (IVDs) with discogenic back pain. The purpose of this study was to determine whether quantitative CEST (qCEST) MRI can be used to detect pH changes in IVDs in vivo. METHODS: The exchange rate ksw between glycosaminoglycan (GAG) protons and water protons was determined from qCEST analysis. Its dependence on pH value was investigated in GAG phantoms with varying pH and concentrations. The relationship between ksw and pH was studied further in vivo in a porcine model on a 3T MR scanner and validated using a pH meter. Sodium lactate was injected into the IVDs to induce various pH values within the discs ranging from 5 to 7. RESULTS: Phantom and animal results revealed that ksw measured using qCEST MRI is highly correlated with pH level. In the animal studies, the relationship can be described as ksw =9.2 × 106 × 10-pH + 196.9, R2 = 0.7883. CONCLUSION: The exchange rate between GAG and water protons determined from qCEST MRI is closely correlated with pH value. This technique has the potential to noninvasively measure pH in the IVDs of patients with discogenic pain. Magn Reson Med 76:1677-1683, 2016. © 2016 International Society for Magnetic Resonance in Medicine.

Spontaneous retroclival hematoma in pituitary apoplexy: case series.

OBJECT: Pituitary apoplexy is a rare and potentially life-threatening disorder that is most commonly characterized by a combination of sudden headache, visual disturbance, and hypothalamic/hormonal dysfunction. In many cases, there is hemorrhagic infarction of an underlying pituitary adenoma. The resulting clinical symptoms are due to compression of the remaining pituitary, cavernous sinuses, or cranial nerves. However, there are only 2 case reports in the literature describing spontaneous retroclival expansion of hemorrhage secondary to pituitary apoplexy. Ten cases of this entity with a review of the literature are presented here. METHODS: This is a single-institution retrospective review of 2598 patients with sellar and parasellar masses during the 10-year period between 1999 and 2009. The pituitary and brain MRI and MRI studies were reviewed by 2 neuroradiologists for evidence of apoplexy, with particular attention given to retroclival extension. RESULTS: Eighteen patients (13 men and 5 women; mean age 54 years) were identified with presenting symptoms of sudden onset of headache and ophthalmoplegia, and laboratory findings consistent with pituitary apoplexy. Ten of these patients (8 men and 2 women; mean age 55 years) had imaging findings consistent with retroclival hematoma. CONCLUSIONS: Retroclival hemorrhage was seen in the majority of cases of pituitary apoplexy (56%), suggesting that it is more common than previously thought.

Anti-NMDA encephalitis: an uncommon, autoimmune mediated form of encephalitis.

We report an interesting case of a 19 year old female with findings on MRI suggestive of viral encephalitis. An extensive workup was negative for infectious causes and she was subsequently diagnosed with anti-NMDA encephalitis. Anti-NMDA encephalitis is a highly lethal but treatable form of autoimmune encephalitis that has recently been characterized. It is frequently found in young women and associated with an underlying teratoma. Although rare, this diagnosis should be considered in young females for whom a rapid onset of encephalitis cannot be explained by more common causes.