Citations

Background: Post-treatment prognosis and monitoring are critical for determining the timing of salvage treatment in glioblastoma patients but has been challenging due to difficulties differentiating progression from treatment effects in conventional images. This exploratory study aimed to establish the correlation of radiomics image features from time series of amino acid tracer 18F-DOPA PET images, with outcomes, using machine learning and dimension reduction analysis. Methods: 18F-DOPA PET images were collected for a patient cohort with wild-type IDH and unmethylated MGMT who underwent dose-escalated radiation therapy. Quantitative features were derived from the high uptake region (T/N > 2.0) in pre- and post-radiation therapy follow-up 18F-DOPA PET images. A customized workflow was utilized for pre-selecting predictive features, followed by manifold learning. Machine learning algorithms were employed to establish associations between imaging features and remaining survival (RS), defined as the time between a follow-up scan and date of death. Results: The ML models exhibited 81–83% ROC_AUC in predicting RS evaluated on an independent test dataset. A RS map is proposed for monitoring tumor alterations through serial 18F-DOPA PET scans, demonstrating superior sensitivity and better correlation with survival compared to the RANO criteria. Conclusions: Our study demonstrates that ML models utilizing FU 18F-DOPA PET images have the potential to effectively predict future survival outcomes in patients with glioblastoma treated with dose-escalated radiation therapy. The capability to assess changes in tumor over time through imaging can potentially assist in patient stratification and the selection of salvage treatments, while also aiding in distinguishing treatment effects from genuine tumor progression.

Rosai–Dorfman Disease (RDD), also known as sinus histiocytosis with massive lymphadenopathy, is a rare non-Langerhans cell histiocytic neoplasm. Although the disease classically presents as massive painless lymphadenopathy in young adults, RDD can also involve the central nervous system in some patients. CNS lesions, can cause headaches, neurologic deficits, and even neurologic deficits. The imaging appearance of CNS RDD typically mimics that of meningiomas: well-circumscribed dural-based lesions that often have dural tails. However, some imaging clues also exist that might help a radiologist recognize RDD, even before histopathologic confirmation. This radiology-pathology report of a patient with CNS RDD highlights the most pertinent clinical, imaging, and pathologic features of CNS RDD, and discusses what the neuroradiologist needs to know about the disease.

Abstract BACKGROUND Glioma radiotherapy planning requires accurate tumor delineation. While T1- contrast-enhanced-MRI (T1-CE-MRI) is the standard, due to blood-brain-barrier breakdown dependencies, T1-CE-MRI fails to reflect the extent of glioma. Studies using amino acid PET tracers report glioma uptake up to 3cm-4cm beyond T1-CE. In this study, amino acid tracer 18F-fluoro-dihydroxyphenylalanine (18F-DOPA) uptake was correlated with histopathological features to determine tumor thresholds. METHODS Using registered 18F-DOPA-PET and T1-CE-MRI images in the Stealth Neuronavigation system targeting concordant and discordant regions, 181 stereotactic biopsy samples (newly-diagnosed=74; recurrent=107) were obtained from 59 enrolled astrocytoma patients across two prospective phase II clinical trials between 2010-2019. An experienced neuropathologist reviewed each sample with hematoxylin and eosin stain and assigned an alphanumeric score: mitotic activity (0=no tumor; 1=no mitosis; 2=few/scattered mitosis; 3=frequent mitosis) and cellular density (A=<25%; B=25%-50%; C=50%-75%; D=>75%). Samples assigned 1C-1D, 2B-2D, or 3A-3D were categorized as histopathological high-score (aggressive disease), remaining samples as low-score. Relative mean (rFDOPA_mean) tumor-to-background uptake ratios were computed for 5mm uniformly expanded volumes from each Stealth biopsy coordinate using the crescent and wedge normalization methods. Relative uptake was compared overall and separately within newly-diagnosed/recurrent disease subgroups. An optimal rFDOPA_mean threshold to delineate high- from low-score was determined using the maximal Youden index of ROC curves. RESULTS Overall, high-score samples (n=116) had higher median (IQR) rFDOPA_mean uptake than low-score samples (n=65): high-score rFDOPA:mean=1.70(1.16-2.26), low-score rFDOPA:mean=1.16(0.83-1.49), Kruskal-Wallis p<0.001. The uptake difference between high- vs. low-score samples was observed within newly-diagnosed and recurrent subgroups, but was only significant for newly-diagnosed (p<0.001). For newly-diagnosed, an rFDOPA:mean=1.49 cutoff between high- and low-score groups shows 69% accuracy, 63% sensitivity, 80% specificity (AUC=0.782). Using the wedge normalization method, rFDOPA_mean values were 0.2 higher than crescent method values. CONCLUSIONS This work presents histologically verified 18F-DOPA-PET thresholds for aggressive disease in newly-diagnosed astrocytoma patients. Separate thresholds will need to be determined for recurrent glioma patients.

AbstractAdvances in computer-aided design and computer-aided manufacturing software have improved translational applications of virtual surgical planning (VSP) in craniomaxillofacial surgery, allowing for precise and accurate fabrication of cutting guides, stereolithographic models, and custom implants. High-resolution computed tomography (CT) imaging has traditionally been the gold standard imaging modality for VSP in craniomaxillofacial surgery but delivers ionizing radiation. Black bone magnetic resonance imaging (MRI) reduces the risks related to radiation exposure and has comparable functionality when compared with CT for VSP. Our group has studied the accuracy of utilizing black bone MRI in planning and executing several types of craniofacial surgeries, including cranial vault remodeling, maxillary advancement, and mandibular reconstruction using fibular bone. Here, we review clinical applications of black bone MRI pertaining to VSP and three-dimensional (3D)-printed guide creation for craniomaxillofacial surgery. Herein, we review the existing literature and our institutional experience comparing black bone MRI and CT in VSP-generated 3D model creation in cadaveric craniofacial surgeries including cranial vault reconstruction, maxillary advancement, and mandibular reconstruction with fibular free flap. Cadaver studies have demonstrated the ability to perform VSP and execute the procedure based on black bone MRI data and achieve outcomes similar to CT when performed for cranial vault reshaping, maxillary advancement, and mandibular reconstruction with free fibula. Limitations of the technology include increased time and costs of the MRI compared with CT and the possible need for general anesthesia or sedation in the pediatric population. VSP and 3D surgical guide creation can be performed using black bone MRI with comparable accuracy to high-resolution CT scans in a wide variety of craniofacial reconstructions. Successful segmentation, VSP, and 3D printing of accurate guides from black bone MRI demonstrate potential to change the preoperative planning standard of care. Black bone MRI also reduces exposure to ionizing radiation, which is of particular concern for the pediatric population or patients undergoing multiple scans.

Abstract BACKGROUND Interpretation of serial magnetic resonance imaging (MRI) for glioblastoma following radiation therapy (RT) is complicated by difficulty differentiating tumor from treatment-related changes, even using updated RANO criteria. The incorporation of novel imaging such as 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (18F-DOPA) PET/CT to post-treatment serial imaging may improve prognostication and better facilitate future treatment decisions. METHODS The secondary analysis of a recent phase II prospective clinical trial of 18F-DOPA PET/CT-directed dose-escalated RT included patients with IDH-wildtype, MGMT-unmethylated glioblastoma who underwent post-treatment serial 18F-DOPA PET/CT surveillance. Quantitative features were extracted from pre-RT and post-RT serial PET/CT images, and robust prognostic features were selected using an in-house workflow. Both an automated machine learning (ML) algorithm and an interpretable ML algorithm were utilized to correlate surveillance PET image features with subsequent survival of greater than 12 months versus less than 12 months from the surveillance timepoint. Changes from pre-RT to post-RT PET/CT (delta model) were also assessed for association with post-RT survival and validated with a separate cohort. RESULTS Thirty-five patients with IDH-wildtype, MGMT-unmethylated glioblastoma who had at least one available (range: 1-14) post-treatment 18F-DOPA PET/CT were included. Twenty-four were used for model training, while 11 were used for validation. Ultimately, a five-feature post-RT model utilizing two shape, two texture, and one first-order radiomic feature was selected. For the delta model, five texture, two shape, and one first order radiomic feature were selected. The models show 90% accuracy in predicting survival < 12 months post-surveillance on the training set, and 68%-73% accuracy (AUC 0.64-0.73) for the validation cohort. Delta features were significantly associated with overall survival (p < 0.05). CONCLUSIONS Post-RT serial 18F-DOPA PET/CT imaging can help distinguish true tumor progression in patients with glioblastoma using a radiomics model. Tumor response evaluated for changes from pre-RT to post-RT 18F-DOPA PET/CT also predicted subsequent overall survival.

Abstract While dose escalation of radiotherapy (DERT) has failed to improve overall survival (OS) or progression-free survival (PFS) for glioblastoma in previous studies, a recent phase II clinical trial utilizing 18F-DOPA-PET-directed DERT demonstrated improved PFS in MGMT-unmethylated patients and OS in MGMT-methylated patients compared to historical controls. This planned secondary analysis sought to determine 1) how 18F-DOPA-PET changes RT volumes beyond standard MRI-planning, 2) which patients benefit most and least from this protocol, 3) which are mostly likely to experience clinically significant radionecrosis after DERT, and 4) patterns of failure after DERT. For 69 evaluable patients, median MRI-defined, PET-defined, and combined low-dose gross tumor volumes (GTV51) were 54 cc (range 9-248), 23 cc (0.4-179), and 62 cc (10-260), respectively. Median MRI-defined, PET-defined, and combined high-dose GTVs (GTV76) were 32 cc (range 4-136), 6 cc (0.1-138), and 34 cc (4-162), respectively. 18F-DOPA-PET resulted in a median volumetric expansion of 13% (0-243%) and 5% (0-217%) from MRI-defined low-dose and high-dose GTV’s, respectively. Central failures ( >95% of recurrence tumor volume) occurred within the 76 Gy, 60 Gy, and 51 Gy isodose lines in 32 (46%), 60 (87%), and 64 (93%) patients, respectively. Recursive partitioning analysis stratified patients by OS and PFS. Patients with 18F-DOPA-PET-defined GTV76 > 7.8cc, MRI-defined GTV76 > 42.7cc, and MGMT promotor-unmethylated tumors had the shortest OS, while patients with smaller PET and MRI-defined tumors had the longest OS (median 10.4 vs. 64.6 months, p< 0.001). Similarly, PFS was worst in patients with 18F-DOPA-PET-defined GTV76 > 2.17 cc who had biopsy only (median PFS 3.2 months, p< 0.001). Patients with 18F-DOPA-PET-defined GTV51 > 50 cc had the highest risk of grade 3+ radionecrosis (p< 0.001). In conclusion, larger 18F-DOPA-PET and MRI-defined tumor volumes were associated with worse outcomes, and 18F-DOPA-PET-directed DERT appears to reduce risk of central recurrence in high-dose volumes.

Background Little is known about the impact that cardiovascular (CV) risk factors have on the formation of various carotid atherosclerotic plaque features. This study set out to assess the association between CV risk factors and plaque characteristics on computed tomography (CT) angiography (CTA). Materials and methods A retrospective review was completed of consecutive patients that underwent a carotid endarterectomy and had CTA imaging of the head and neck vasculature. Atherosclerotic plaques of both carotid arteries were evaluated for calcification(s), low-density plaque (LDP) components, ulceration(s), and degree of stenosis. Various clinical CV risk factors were assessed using medical records. Last recorded laboratory levels were dichotomized into categories: total cholesterol <200 or ≥200 mg/dL, low-density lipoprotein (LDL) <130 or ≥130 mg/dL, high-density lipoprotein <35 or ≥35 mg/dL, and triglyceride <200 or ≥200 mg/dL. Results Of 97 included patients, 62 were male (63.9%); the average age was 72.7 (standard deviation = 9.5). Calcifications were in 95/97 (97.9%) of patients (one or both carotid plaques); LDP components were in 73/97 (75.3%), and ulcerations were in 21/97 (21.6%). Elevated total cholesterol and elevated LDL levels were both associated with a higher likelihood of LDP components ( p = 0.004 and p = 0.02, respectively). There were no other statistically significant associations between individual plaque features or severity of arterial stenosis and CV risk factors. Conclusion In carotid atherosclerotic plaques, LDP components are more frequently present in one or both carotid arteries in patients with elevated total cholesterol and/or LDL levels. Such findings raise the possibility that cholesterol levels may be directly related to the formation of specific high-risk plaque features.