Leptomeningeal enhancement on preoperative brain MRI in patients with glioblastoma and its clinical impact

The development of a combined clinico-radiomics model for predicting post-operative recurrence in atypical meningiomas: a multicenter study

PURPOSE

Atypical meningiomas could manifest early recurrence after surgery and even adjuvant radiotherapy. We aimed to construct a clinico-radiomics model to predict post-operative recurrence of atypical meningiomas based on clinicopathological and radiomics features.

MATERIALS AND METHODS

The study cohort was comprised of 224 patients from two neurosurgical centers. 164 patients from center I were divided to the training cohort for model development and the testing cohort for internal validation. 60 patients from center II were used for external validation. Clinicopathological characteristics, radiological semantic, and radiomics features were collected. A radiomic signature was comprised of four radiomics features. A clinico-radiomics model combining the radiomics signature and clinical characteristics was constructed to predict the recurrence of atypical meningiomas.

RESULTS

1920 radiomics features were extracted from the T1 Contrast and T2-FLAIR sequences of patients in center I. The radiomics signature was able to differentiate post-operative patients into low-risk and high-risk groups based on tumor recurrence (P < 0.001). A clinic-radiomics model was established by combining age, extent of resection, Ki-67 index, surgical history and the radiomics signature for recurrence prediction in atypical meningiomas. The model achieved a good prediction performance with the integrated AUC of 0.858 (0.802-0.915), 0.781 (0.649-0.912) and 0.840 (0.747-0.933) in the training, internal validation and external validation cohort, respectively.

CONCLUSIONS

The present study established a radiomics signature and a clinico-radiomics model with a favorable performance in predicting tumor recurrence for atypical meningiomas.

Leptomeningeal enhancement in multiple sclerosis and other neurological diseases: A systematic review and Meta-Analysis

BACKGROUND

The lack of systematic evidence on leptomeningeal enhancement (LME) on MRI in neurological diseases, including multiple sclerosis (MS), hampers its interpretation in clinical routine and research settings.

PURPOSE

To perform a systematic review and meta-analysis of MRI LME in MS and other neurological diseases.

MATERIALS AND METHODS

In a comprehensive literature search in Medline, Scopus, and Embase, out of 2292 publications, 459 records assessing LME in neurological diseases were eligible for qualitative synthesis. Of these, 135 were included in a random-effects model meta-analysis with subgroup analyses for MS.

RESULTS

Of eligible publications, 161 investigated LME in neoplastic neurological (n = 2392), 91 in neuroinfectious (n = 1890), and 75 in primary neuroinflammatory diseases (n = 4038). The LME-proportions for these disease classes were 0.47 [95%-CI: 0.37-0.57], 0.59 [95%-CI: 0.47-0.69], and 0.26 [95%-CI: 0.20-0.35], respectively. In a subgroup analysis comprising 1605 MS cases, LME proportion was 0.30 [95%-CI 0.21-0.42] with lower proportions in relapsing-remitting (0.19 [95%-CI 0.13-0.27]) compared to progressive MS (0.39 [95%-CI 0.30-0.49], p = 0.002) and higher proportions in studies imaging at 7 T (0.79 [95%-CI 0.64-0.89]) compared to lower field strengths (0.21 [95%-CI 0.15-0.29], p < 0.001). LME in MS was associated with longer disease duration (mean difference 2.2 years [95%-CI 0.2-4.2], p = 0.03), higher Expanded Disability Status Scale (mean difference 0.6 points [95%-CI 0.2-1.0], p = 0.006), higher T1 (mean difference 1.6 ml [95%-CI 0.1-3.0], p = 0.04) and T2 lesion load (mean difference 5.9 ml [95%-CI 3.2-8.6], p < 0.001), and lower cortical volume (mean difference -21.3 ml [95%-CI -34.7--7.9], p = 0.002).

CONCLUSIONS

Our study provides high-grade evidence for the substantial presence of LME in MS and a comprehensive panel of other neurological diseases. Our data could facilitate differential diagnosis of LME in clinical settings. Additionally, our meta-analysis corroborates that LME is associated with key clinical and imaging features of MS. PROSPERO No: CRD42021235026.

The Nomogram of MRI-based Radiomics with Complementary Visual Features by Machine Learning Improves Stratification of Glioblastoma Patients: A Multicenter Study

BACKGROUND

Glioblastomas (GBMs) represent both the most common and the most highly malignant primary brain tumors. The subjective visual imaging features from MRI make it challenging to predict the overall survival (OS) of GBM. Radiomics can quantify image features objectively as an emerging technique. A pragmatic and objective method in the clinic to assess OS is strongly in need.

PURPOSE

To construct a radiomics nomogram to stratify GBM patients into long- vs. short-term survival.

STUDY TYPE

Retrospective.

POPULATION

One-hundred and fifty-eight GBM patients from Brain Tumor Segmentation Challenge 2018 (BRATS2018) were for model construction and 32 GBM patients from the local hospital for external validation.

FIELD STRENGTH/SEQUENCE

1.5 T and 3.0 T MRI Scanners, T₁ WI, T₂ WI, T₂ FLAIR, and contrast-enhanced T₁ WI sequences ASSESSMENT: All patients were divided into long-term or short-term based on a survival of greater or fewer than 12 months. All BRATS2018 subjects were divided into training and test sets, and images were assessed for ependymal and pia mater involvement (EPI) and multifocality by three experienced neuroradiologists. All tumor tissues from multiparametric MRI were fully automatically segmented into three subregions to calculate the radiomic features. Based on the training set, the most powerful radiomic features were selected to constitute radiomic signature.

STATISTICAL TESTS

Receiver operating characteristic (ROC) curve, sensitivity, specificity, and the Hosmer-Lemeshow test.

RESULTS

The nomogram had a survival prediction accuracy of 0.878 and 0.875, a specificity of 0.875 and 0.583, and a sensitivity of 0.704 and 0.833, respectively, in the training and test set. The ROC curve showed the accuracy of the nomogram, radiomic signature, age, and EPI for external validation set were 0.858, 0.826, 0.664, and 0.66 in the validate set, respectively.

DATA CONCLUSION

Radiomics nomogram integrated with radiomic signature, EPI, and age was found to be robust for the stratification of GBM patients into long- vs. short-term survival.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

Leptomeningeal Spread in Glioblastoma: Diagnostic and Therapeutic Challenges

BACKGROUND

Glioblastoma (GBM) is the most common and aggressive primary malignant brain tumor. Leptomeningeal spread (LMS) is a severe complication of GBM, raising diagnostic and therapeutic challenges in clinical routine.

METHODS

We performed a review of the literature focused on LMS in GBM. MEDLINE and EMBASE databases were queried from 1989 to 2019 for articles describing diagnosis and therapeutic options in GBM LMS, as well as risk factors and pathogenic mechanisms.

RESULTS

We retrieved 155 articles, including retrospective series, case reports, and early phase clinical trials, as well as preclinical studies. These articles confirmed that LMS in GBM remains (a) a diagnostic challenge with cytological proof of LMS obtained in only 35% of cases and (b) a therapeutic challenge with a median overall survival below 2 months with best supportive care alone. For patients faced with suggestive clinical symptoms, whole neuroaxis magnetic resonance imaging and cerebrospinal fluid analysis are both recommended. Liquid biopsies are under investigation and may help prompt a reliable diagnosis. Based on the literature, a multimodal and personalized therapeutic approach of LMS, including surgery, radiotherapy, systemic cytotoxic chemotherapy, and intrathecal chemotherapies, may provide benefits to selected patients. Interestingly, molecular targeted therapies appear promising in case of actionable molecular target and should be considered.

CONCLUSION

As the prognosis of glioblastoma is improving over time, LMS becomes a more common complication. Our review highlights the need for translational studies and clinical trials dedicated to this challenging condition in order to improve diagnostic and therapeutic strategies.

IMPLICATIONS FOR PRACTICE

This review summarizes the diagnostic tools and applied treatments for leptomeningeal spread, a complication of glioblastoma, as well as their outcomes. The importance of exhaustive molecular testing for molecular targeted therapies is discussed. New diagnostic and therapeutic strategies are outlined, and the need for translational studies and clinical trials dedicated to this challenging condition is highlighted.

Clinical Characteristics of High-Grade Glioma with Primary Leptomeningeal Seeding at Initial Diagnosis in a Single Center Study

BACKGROUND

High-grade glioma (HGG) with primary leptomeningeal seeding (PLS) at initial diagnosis is rare. The purpose of this study was to identify its clinical features and to describe the clinical treatment outcomes.

METHODS

We retrospectively reviewed the medical records of patients with HGG (World Health Organization grade III or IV) at our institution between 2004 and 2019, and patients with PLS at the initial diagnosis were enrolled in the study. Clinical features, such as the location of leptomeningeal seeding, surgical methods, and degree of resection, were sorted based on electronic medical records also containing performance scale, and hematological and serological evaluations. Radiological findings and immunohistochemical categories were confirmed. Furthermore, we sought to determine whether controlling intracranial pressure (ICP) via early cerebrospinal fluid (CSF) diversion increases overall survival (OS) after the initial diagnosis.

RESULTS

Of the 469 patients with HGG in our institution, less than 2% had PLS at the initial diagnosis. Most patients suffered from headache, diplopia, and dizziness. Pathological findings included 7 glioblastomas and 2 anaplastic astrocytomas. Seven of the 9 patients underwent CSF diversion. All patients were administered concurrent chemoradiotherapy (CCRT) with temozolomide, 89% of which started adjuvant temozolomide and 33% of which completed the six cycles of adjuvant temozolomide. The OS of patients with HGG and PLS was 8.7 months (range, 4-37), an extremely poor result compared to that of other studies. Also, the 1-year and 2-year OS rates were 44.4% and 16.7%, respectively.

CONCLUSION

Diagnosis and treatment of HGG with PLS are challenging. Aggressive control of ICP followed by early initiation of standard CCRT seems to be helpful in improving symptoms. However, despite aggressive treatment, the prognosis is poor. A multicenter trial and research may be necessary to create a standardized protocol for this disease.