Genomic mapping and survival prediction in glioblastoma: molecular subclassification strengthened by hemodynamic imaging biomarkers.

PURPOSE: To correlate tumor blood volume, measured by using dynamic susceptibility contrast material-enhanced T2*-weighted magnetic resonance (MR) perfusion studies, with patient survival and determine its association with molecular subclasses of glioblastoma (GBM). MATERIALS AND METHODS: This HIPAA-compliant retrospective study was approved by institutional review board. Fifty patients underwent dynamic susceptibility contrast-enhanced T2*-weighted MR perfusion studies and had gene expression data available from the Cancer Genome Atlas. Relative cerebral blood volume (rCBV) (maximum rCBV [rCBV(max)] and mean rCBV [rCBV(mean)]) of the contrast-enhanced lesion as well as rCBV of the nonenhanced lesion (rCBV(NEL)) were measured. Patients were subclassified according to the Verhaak and Phillips classification schemas, which are based on similarity to defined genomic expression signature. We correlated rCBV measures with the molecular subclasses as well as with patient overall survival by using Cox regression analysis. RESULTS: No statistically significant differences were noted for rCBV(max), rCBV(mean) of contrast-enhanced lesion or rCBV(NEL) between the four Verhaak classes or the three Phillips classes. However, increased rCBV measures are associated with poor overall survival in GBM. The rCBV(max) (P = .0131) is the strongest predictor of overall survival regardless of potential confounders or molecular classification. Interestingly, including the Verhaak molecular GBM classification in the survival model clarifies the association of rCBV(mean) with patient overall survival (hazard ratio: 1.46, P = .0212) compared with rCBV(mean) alone (hazard ratio: 1.25, P = .1918). Phillips subclasses are not predictive of overall survival nor do they affect the predictive ability of rCBV measures on overall survival. CONCLUSION: The rCBV(max) measurements could be used to predict patient overall survival independent of the molecular subclasses of GBM; however, Verhaak classifiers provided additional information, suggesting that molecular markers could be used in combination with hemodynamic imaging biomarkers in the future.

Morphologic MRI features, diffusion tensor imaging and radiation dosimetric analysis to differentiate pseudo-progression from early tumor progression.

Pseudo-progression (PsP) refers to the paradoxical increase of contrast enhancement within 12 weeks of chemo-radiation therapy in gliomas attributable to treatment effects rather than early tumor progression (ETP). This study was performed to evaluate the utility of morphologic imaging features, diffusion tensor imaging (DTI) and radiation dosimetric analysis of magnetic resonance imaging (MRI) changes in differentiating PsP from ETP. Serial MRI examinations of 163 patients treated for high-grade glioma were reviewed. 46 patients showed a recurrent or progressive enhancing lesion within 12 weeks of radiotherapy. We used an in-house modified scoring system based on 20 different morphologic features (modified VASARI features) to assess the MRI studies. DTI analyses were performed in 24 patients. MRI changes were defined as recurrent volume (Vrec) and registered with pretreatment computed tomography dataset, and the actual dose received by the Vrec during treatment was calculated using dose-volume histograms. Bidimensional product of T2-FLAIR signal abnormality and enhancing component was larger in the ETP group. DTI metrics revealed no significant difference between the two groups. There was no statistically significant difference in the location of Vrec between PsP and ETP groups. Morphologic MRI features and DTI have a limited role in differentiating between PsP and ETP. The larger sizes of the T2-FLAIR signal abnormality and the enhancing component of the lesion favor ETP. There was no correlation between the pattern of MRI changes and radiation dose distribution between PsP and ETP groups.

Application of the Lugano Classification for Initial Evaluation, Staging, and Response Assessment of Hodgkin and Non-Hodgkin Lymphoma: The PRoLoG Consensus Initiative (Part 1-Clinical).

Our objective was to provide consensus recommendations from a consortium of academic and industry experts in the field of lymphoma and imaging for consistent application of the Lugano classification. Methods: Consensus was obtained through a series of meetings from July 2019 until September 2021 sponsored by the Pharma Imaging Network for Therapeutics and Diagnostics (PINTaD) as part of the PINTaD Response Criteria in Lymphoma Working Group (PRoLoG) consensus initiative. Results: Consensus recommendations clarified technical considerations for PET/CT and diagnostic CT from the Lugano classification, including updating the FDG avidity of different lymphoma entities, clarifying the response nomenclature, and refining lesion classification and scoring, especially with regard to scores 4 and 5 and the X category of the 5-point scale. Combination of metabolic and anatomic responses is clarified, as well as response assessment in cases of discordant or missing evaluations. Use of clinical data in the classification, especially the requirement for bone marrow assessment, is further updated on the basis of lymphoma entities. Clarification is provided with regard to spleen and liver measurements and evaluation, as well as nodal response. Conclusion: Consensus recommendations are made to comprehensively address areas of inconsistency and ambiguity in the classification encountered during response evaluation by end users, and such guidance should be used as a companion to the 2014 Lugano classification.

Application of the Lugano Classification for Initial Evaluation, Staging, and Response Assessment of Hodgkin and Non-Hodgkin Lymphoma: The PRoLoG Consensus Initiative (Part 2-Technical).

The aim of this initiative was to provide consensus recommendations from a consortium of academic and industry experts in the field of lymphoma and imaging for the consistent application of imaging assessment with the Lugano classification. Methods: Consensus was obtained through a series of meetings from July 2019 to October 2021 sponsored by the PINTaD (Pharma Imaging Network for Therapeutics and Diagnostics) as part of the ProLoG (PINTaD RespOnse criteria in Lymphoma wOrking Group) consensus initiative. Results: Consensus recommendations encompass all technical imaging aspects of the Lugano classification. Some technical considerations for PET/CT and diagnostic CT are clarified with regards to required imaging series and scan visits, as well as acquisition and reconstruction of PET images and influence of lesion size and background activity. Recommendations are given on the role of imaging and clinical reviewers as well as on training and monitoring. Finally, an example template of an imaging case report form is provided to support efficient collection of data with Lugano Classification. Conclusion: Consensus recommendations are made to comprehensively address technical and imaging areas of inconsistency and ambiguity in the classification encountered by end users. Such guidance should be used to support standardized acquisition and evaluation with the Lugano 2014.

Model selection for DCE-T1 studies in glioblastoma.

Dynamic contrast enhanced T(1)-weighted MRI using the contrast agent gadopentetate dimeglumine (Gd-DTPA) was performed on 10 patients with glioblastoma. Nested models with as many as three parameters were used to estimate plasma volume or plasma volume and forward vascular transfer constant (K(trans)) and the reverse vascular transfer constant (k(ep)). These constituted models 1, 2, and 3, respectively. Model 1 predominated in normal nonleaky brain tissue, showing little or no leakage of contrast agent. Model 3 predominated in regions associated with aggressive portions of the tumor, and model 2 bordered model 3 regions, showing leakage at reduced rates. In the patient sample, v(p) was about four times that of white matter in the enhancing part of the tumor. K(trans) varied by a factor of 10 between the model 2 (1.9 ↔ 10(-3) min(-1)) and model 3 regions (1.9 ↔ 10(-2) min(-1)). The mean calculated interstitial space (model 3) was 5.5%. In model 3 regions, excellent curve fits were obtained to summarize concentration-time data (mean R(2) = 0.99). We conclude that the three parameters of the standard model are sufficient to fit dynamic contrast enhanced T(1) data in glioblastoma under the conditions of the experiment.

Tumor vascular leakiness and blood volume estimates in oligodendrogliomas using perfusion CT: an analysis of perfusion parameters helping further characterize genetic subtypes as well as differentiate from astroglial tumors.

The purpose of this study was to determine the usefulness of perfusion CT (PCT) parameters particularly blood volume and neovascular permeability estimates (permeability surface area-product, PS) in the evaluation of oligodendrogliomas (OG), correlation with genetic subtypes of OGs (with or without loss of heterozygosity/LOH on 1p/19q) as well as comparison of perfusion parameters of OGs with astroglial tumors. Pre-operative PCT done in 21 patients with OGs was retrospectively correlated with our previously published PCT data for 32 patients with astroglial neoplasms (Jain R et al., AJNR Am J Neuroradiol 29:694-700, 2008). All OGs were also analyzed for genetic subtypes of with or without LOH. PCT parameters PS and cerebral blood volume (CBV) were obtained for the entire lesion and a statistical analysis done to correlate various histopathological variants. Low grade OGs (n = 13) showed slightly lower CBV (1.42 vs. 1.72 ml/100 g; P value 0.391) and PS (0.56 vs. 0.95 ml/100 g/min; P value 0.099) as compared to high grade OGs (n = 8), though not statistically significant. LOH positive OGs (n = 13) showed higher mean CBV (1.59 vs. 1.45; P value 0.712) and slightly lower PS (0.68 vs. 0.75; P value 0.718) as compared to LOH negative OGs (n = 8), although not statistically significant. Low grade OGs (n = 13) showed higher mean CBV 1.42 ml/100 g as compared to low grade astroglial tumors (n = 8) 0.95 ml/100 g (P value = 0.08), however no statistically significant difference was noted for PS (0.56 vs. 0.52 ml/100 g/min, P value 0.695). Statistically significant differences were observed in CBV and PS values of high grade OGs and high grade astroglial tumors with the high grade glial tumors showing higher mean CBV (2.79 vs. 1.72; P value 0.03) as well as higher PS (2.37 vs. 0.95; P value < 0.01), however this difference was not significant if only comparing grade III OGs with grade III astroglial tumors. PCT perfusion parameters including PS values do not help grade OGs despite showing a trend for higher CBV and PS in higher grade OGs. Similarly LOH positive OGs also showed slightly higher CBV, but again failed to reach any statistically significant level. Low grade OGs showed slightly higher CBV as compared to low grade astroglial tumors, whereas higher grade OGs showed significantly lower PS values as compared to higher grade astroglial tumors despite showing high CBV.

Predicting survival in glioblastomas using diffusion tensor imaging metrics.

PURPOSE: To retrospectively correlate various diffusion tensor imaging (DTI) metrics in patients with glioblastoma multiforme (GBM) with patient survival analysis and also degree of tumor proliferation index determined histologically. MATERIALS AND METHODS: Thirty-four patients with histologically confirmed treatment naive GBMs underwent DTI on a 3.0 Tesla (T) scanner. Region-of-interest was placed on the whole lesion including the enhancing as well as nonenhancing component of the lesion to determine the various DTI metrics. Kaplan-Meier estimates and Cox proportional hazards regression methods were used to assess the relationship of DTI metrics (minimum and mean values) and Ki-67 with progression free survival (PFS). To study the relationship between DTI metrics and Ki-67, Pearson's correlation coefficient was computed. RESULTS: Univariate analysis showed that patients with fractional anisotropy (FA)(mean) ≤ 0.2, apparent diffusion coefficient (ADC)(min) ≤ 0.6, planar anisotropy (CP)(min) ≤ 0.002, spherical anisotropy (CS)(mean) > 0.68 and Ki-67 > 0.3 had lower PFS rate. The multivariate analysis demonstrated that only CP(min) was the best predictor of survival in these patients, after adjusting for age, Karnofsky performance scale and extent of resection. No significant correlation between DTI metrics and Ki-67 were observed. CONCLUSION: DTI metrics can be used as a sensitive and early indicator for PFS in patients with glioblastomas. This could be useful for treatment planning as high-grade gliomas with lower ADC(min), FA(mean), CP(min), and higher CS(mean) values may be treated more aggressively.

Treatment induced necrosis versus recurrent/progressing brain tumor: going beyond the boundaries of conventional morphologic imaging.

Brain tumor patients undergo various combinations therapies, leading to very complex and confusing imaging appearances on follow up MR imaging and hence, differentiating recurrent or progressing tumors from treatment induced necrosis or effects has always been a challenge in neuro-oncologic imaging. This particular topic has become more relevant these days because of the advent of newer anti-angiogenic and anti-neoplastic chemotherapeutic agents as well as use of salvage radiation therapy. Various clinically available functional imaging modalities can provide additional physiologic and metabolic information about the tumors which could be useful in identifying viable tumor from treatment induced necrosis and hence, can guide treatment planning. In this review we will discuss various functional neuro-imaging modalities, their advantages and limitations and also their utility in treatment planning.

MRI Pre- and Post-Embolization Enhancement Patterns Predict Surgical Outcomes in Intracranial Meningiomas.

PURPOSE: To evaluate the effects of preoperative embolization on overall surgical outcomes after meningioma resection and determine whether pre- and postembolization tumor enhancement patterns on magnetic resonance imaging (MRI) scans can be used to assess the efficacy of embolization. METHODS: We developed a prospective database of all patients who underwent surgical resection with or without preoperative embolization for extra-axial intracranial meningiomas from 2004 to 2010. Using specialized computer software, the total volume of enhancement was calculated in pre- and postembolization MRI scans to quantify the percentage of embolization, which was described as the embolization fraction (EF). RESULTS: A total of 89 patients underwent surgical resection. Fifty two patients underwent embolization prior to surgery. Tumor location significantly correlated with the decision to embolize preoperatively. Adequate embolization was achieved in 58% of patients. Forty four patients (84.6%) had a postsurgical Karnofsky performance score (KPS) of 80 or above, while 46 patients (88.4%) had a postsurgical Glascow Outcome Score (GOS) of 4 or 5. The mean EF was 25.03% with a median of 18.72%. A greater extent of embolization as quantified by EF led to decreased intraoperative blood loss (r = -.319, P = .022) and better postsurgical outcomes as defined by KPS (r = .279, P = .044). CONCLUSIONS: Pre- and postembolization tumor enhancement patterns on magnetic resonance imaging defined as EF correlate with improved surgical facilitation and postoperative functional outcomes in the management of intracranial meningioma.

Prognostic vascular imaging biomarkers in high-grade gliomas: tumor permeability as an adjunct to blood volume estimates.

RATIONALE AND OBJECTIVES: Despite recent advances in the treatment of high-grade gliomas, overall survival (OS) remains poor, which underlines the importance of searching for and determining prognostic imaging biomarkers. The purpose of our retrospective study was to correlate patient survival with relative cerebral blood volume (rCBV) and permeability surface area-product (PS) measured using perfusion computed tomography (PCT) in patients with high-grade gliomas. METHODS: This study was composed of 54 patients with high-grade gliomas (World Health Organization [WHO] grade III, n = 14; WHO grade IV, n = 40) who underwent pretreatment PCT. Kaplan-Meier survival estimates were computed to describe OS for patients with high-versus-low PCT parameters, as well as grade III and IV gliomas. RESULTS: Differences in OS between high and low rCBV, PS, and rCBV + PS were significant (P < .001) for all high-grade gliomas. After adjustment for WHO grade, rCBV (P = .041) and rCBV + PS (P = .013) estimates remained significant, whereas PS estimates were not (P = .214). PS estimates showed a statistically significant difference for OS in the grade III glioma group (P = .011), whereas for grade IV gliomas, rCBV estimates were statistically significant (P = .019). rCBV + PS was statistically significant for OS in both grade III (P = .001) and grade IV (P = .004) glioma groups. CONCLUSIONS: Blood volume and permeability estimates measured using PCT can help predict survival in patients with high-grade gliomas. Patients with high PCT parameters showed worse OS compared to the patients with low PCT. Both rCBV and rCBV + PS remained statistically significant even after adjustment for WHO grade, suggesting these may be better predictors of OS than histological grade.

Central nervous system tuberculosis: pathophysiology and imaging findings.

With the onset of the human immunodeficiency virus pandemic, the incidence of tuberculosis, including central nervous system (CNS) tuberculosis, has increased in developed countries. It is no longer a disease confined to underdeveloped and developing countries. The imaging appearance has become more complex with the onset of multidrug-resistant tuberculosis. Imaging plays an important role in the early diagnosis of CNS tuberculosis and may prevent unnecessary morbidity and mortality. This article presents an extensive review of typical and atypical imaging appearances of intracranial tuberculosis, and discusses pathogenesis, patterns of involvement, and advances in imaging of intracranial tuberculosis.

Sigmoid kidney associated with double urethra.

An unusual case of crossed renal ectopia (sigmoid kidney) in an adult, compounded with double urethra, is being presented for its rarity and mode of presentation.

Correlation of immunohistologic and perfusion vascular parameters with MR contrast enhancement using image-guided biopsy specimens in gliomas.

RATIONALE AND OBJECTIVES: The purpose of this study was to correlate the status of magnetic resonance contrast enhancement with immunohistologic vascular parameters such as microvascular cellular proliferation (MVCP), microvascular density (MVD), vascular endothelial growth factor receptor-2 (VEGFR-2) expression, and World Health Organization (WHO) grade obtained from image-guided biopsy specimens. We also compared perfusion computed tomography (PCT) parameters such as cerebral blood volume (CBV), cerebral blood flow (CBF), and permeability surface area-product (PS) with the presence or absence of contrast enhancement. MATERIALS AND METHODS: A total of 26 image-guided biopsy specimens in 16 patients with treatment naive gliomas were obtained from contrast-enhancing (CE) and nonenhancing (NE) regions of the glioma. Contrast enhancement status was correlated with MVD, MVCP, VEGFR-2 expression, and WHO grade obtained from the biopsy specimen as well as with the PCT parameters. RESULTS: Contrast enhancement showed statistically significant correlation with MVCP (P = .003) and PS (P = .007) when compared with various immunohistologic and perfusion vascular parameters. WHO grade of the biopsy specimen showed statistically significant correlation with contrast enhancement (P = .002), MVCP (P < .001), and PS values (P = .028). CONCLUSION: Contrast enhancement in gliomas is primarily from a break in blood-brain barrier as evidenced by its correlation with PS and MVCP, whereas it was not statistically correlated with CBV and MVD even though it showed a positive trend. Contrast enhancement also showed significant correlation with WHO grade suggesting a biopsy from CE region in a heterogeneous glioma probably will still yield the most aggressive part of the glioma is also shown by its association with MVCP and PS estimates.

Differentiating treatment-induced necrosis from recurrent/progressive brain tumor using nonmodel-based semiquantitative indices derived from dynamic contrast-enhanced T1-weighted MR perfusion.

Differentiating treatment-induced necrosis (TIN) from recurrent/progressive tumor (RPT) in brain tumor patients using conventional morphologic imaging features is a very challenging task. Functional imaging techniques also offer moderate success due to the complexity of the tissue microenvironment and the inherent limitation of the various modalities and techniques. The purpose of this retrospective study was to assess the utility of nonmodel-based semiquantitative indices derived from dynamic contrast-enhanced T1-weighted MR perfusion (DCET1MRP) in differentiating TIN from RPT. Twenty-nine patients with previously treated brain tumors who showed recurrent or progressive enhancing lesion on follow-up MRI underwent DCET1MRP. Another 8 patients with treatment-naive high-grade gliomas who also underwent DCET1MRP were included as the control group. Semiquantitative indices derived from DCET1MRP included maximum slope of enhancement in initial vascular phase (MSIVP), normalized MSIVP (nMSIVP), normalized slope of delayed equilibrium phase (nSDEP), and initial area under the time-intensity curve (IAUC) at 60 and 120 s (IAUC(60) and IAUC(120)) obtained from the enhancement curve. There was a statistically significant difference between the 2 groups (P < .01), with the RPT group showing higher MSIVP (15.78 vs 8.06), nMSIVP (0.046 vs 0.028), nIAUC(60) (33.07 vs 6.44), and nIAUC(120) (80.14 vs 65.55) compared with the TIN group. nSDEP was significantly lower in the RPT group (7.20 × 10(-5) vs 15.35 × 10(-5)) compared with the TIN group. Analysis of the receiver-operating-characteristic curve showed nMSIVP to be the best single predictor of RPT, with very high (95%) sensitivity and high (78%) specificity. Thus, nonmodel-based semiquantitative indices derived from DCET1MRP that are relatively easy to derive and do not require a complex model-based approach may aid in differentiating RPT from TIN and can be used as robust noninvasive imaging biomarkers.