Role of MRI in Primary Brain Tumor Evaluation

Authors: Denise Leung MDa, Xiaosi Han MDa, Tom Mikkelsen MD, FRCPCa, and L. Burt Nabors MDa
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  • a From the Departments of Neurology and Neurosurgery, Henry Ford Hospital, Detroit, Michigan, and Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama.

The NCCN Clinical Practice Guidelines in Oncology for Central Nervous System Cancers use radiologic presentation in the initial evaluation of patients with primary brain tumors and in the determination of response to therapy. The dominant modality use is MRI because of its superior image resolution, speed of acquisition, and high safety profile for patients. The interpretation of MRI is a critical aspect of patient care and evaluation. This article reviews the predominant aspects of MRI for brain tumors, the standard sequences, the criteria to consider in determining treatment response, and advanced aspects currently available. The proper integration of this essential imaging modality into patient care ensures timely disease evaluation and guides the use of therapeutic tools.

NCCN: Continuing Education

Accreditation Statement

This activity has been designated to meet the educational needs of physicians and nurses involved in the management of patients with cancer. There is no fee for this article. No commercial support was received for this article. The National Comprehensive Cancer Network (NCCN) is accredited by the ACCME to provide continuing medical education for physicians.

NCCN designates this journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

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This activity is accredited for 1.0 contact hour. Accreditation as a provider refers to recognition of educational activities only; accredited status does not imply endorsement by NCCN or ANCC of any commercial products discussed/displayed in conjunction with the educational activity. Kristina M. Gregory, RN, MSN, OCN, is our nurse planner for this educational activity.

All clinicians completing this activity will be issued a certificate of participation. To participate in this journal CE activity: 1) review the learning objectives and author disclosures; 2) study the education content; 3) take the posttest with a 66% minimum passing score and complete the evaluation at http://education.nccn.org/node/56623; and 4) view/print certificate.

Release date: November 4, 2014; Expiration date: November 4, 2015

Learning Objectives

Upon completion of this activity, participants will be able to:

  • Describe the challenges of MRI assessment in patients receiving bevacizumab
  • Explain the benefits of using MRS in brain tumor evaluation
  • Summarize the role of diffusion MRI and perfusion MRI in tumor diagnosis, grading, prognosis, and response assessment

Overview

Primary brain tumors comprise a diverse group of pathologic types derived from the various cells that compose the central nervous system (CNS). The clinical management of primary brain cancer is typically conducted by a team of health care providers, including neurosurgeons, neurologists, medical oncologists, radiation oncologists, radiologists, and pathologists. Most of these specialties depend on diagnostic imaging of the CNS to characterize tumor types and determine treatment options.

T1/T2-Weighted MRI

MRI is highly sensitive to pathologic alterations of normal parenchyma and has been an important diagnostic tool in the evaluation of intracranial tumors. MRI allows an accurate determination of lesion location, extent, mass effect, atrophy, and subacute or chronic hemorrhage, and an accurate distinction between a vascular structure and adjacent parenchyma. The typical MR scan for a patient with a brain tumor includes T1/T2-weighted, fluid-attenuated inversion recovery (FLAIR), and postcontrast T1-weighted images (Figure 1). T1-weighted images are most useful for depicting anatomic detail and show cerebrospinal fluid and most tumors as low signal intensity, whereas areas of fat and subacute hemorrhage appear as high signal intensity. T2-weighted images are more sensitive for lesion detection and show cerebrospinal fluid and most lesions as high signal intensity, whereas areas of hemorrhage or chronic hemosiderin deposits may appear as low signal. FLAIR images are T2-weighted with low signal cerebrospinal fluid, are highly sensitive for pathology detection, and display most lesions, including tumors and edema, with higher signal intensity than T2 images. However, the tumor focus in FLAIR or T2 images is not well separated from surrounding edema, gliosis, or ischemic changes. T1-weighted images after contrast enhancement generally provide better localization of the tumor nidus and improved diagnostic information relating to tumor grade, blood-brain barrier breakdown, hemorrhage, edema, and necrosis. Contrast-enhanced T1-weighted images also show small focal lesions better, such as metastases, tumor recurrence, and ependymal or leptomeningeal tumor spread. The T1-weighted enhancement of a contrast agent is attributed to blood-brain barrier leakage associated with angiogenesis and capillary damage in regions of active tumor growth and radiation injury.1

Changes in enhancing tumor size based on 2-dimensional measurements of contrast-enhanced T1 images are the basis for the RANO (Response Assessment in Neuro-Oncology) criteria, the current standard for assessing glioma response, and the previously used Macdonald criteria.2,3 To assess tumor size, a measurement is made of the maximal enhancing tumor diameter on an axial gadolinium-enhanced T1-weighted section, and the largest perpendicular diameter is measured on the same image. The product of the 2 diameters is calculated, and the measurements are performed for each measurable lesion to generate a summed product. The RANO criteria also includes assessment of nonenhancing lesions whereas the Macdonald criteria does not, which is the key difference between the criteria. Inclusion of nonenhancing lesions will permit assessment of not only the intrinsic nonenhancing portion of gliomas but also treatment response to antiangiogenic therapy.

Bevacizumab, a recombinant humanized monoclonal antibody against vascular endothelial growth factor

Figure 1
Figure 1

MRI images show a large mass in a patient presenting with hemiparesis on the right side. (A) T1-weighted image shows a hypointensity lesion in the left frontal-parietal region. (B, C) T2-weighted and fluid-attenuated inversion recovery images show a heterogeneous hyperintensity lesion with surrounding edema. (D) T1-weighted image with contrast shows a heterogeneous ring enhancing lesion, a second area of enhancement posterior to the major lesion, and vasogenic edema. Pathology was consistent with glioblastoma.

Citation: Journal of the National Comprehensive Cancer Network J Natl Compr Canc Netw 12, 11; 10.6004/jnccn.2014.0156

(VEGF), recently became a common therapy for recurrent glioblastoma and radiation necrosis. It sequesters soluble VEGF, preventing receptor binding and inhibiting angiogenesis and vascular permeability. Therefore, a dramatic decrease in contrast enhancement is frequently observed after bevacizumab administration, which may not necessarily reflect a true reduction in tumor size. The uncoupling of contrast enhancement and true tumor size can thus lead to an overestimation of treatment response, a phenomenon known as a pseudoresponse.4,5 The impact of bevacizumab on radiation necrosis is another important consideration in assessing radiographic response. Radiation necrosis typically manifests as avid enhancement, edema, and sometimes mass effect, making it difficult to distinguish from tumor progression. Evidence suggests that increased levels of VEGF contribute to leaky vasculature in radiation necrosis, and bevacizumab substantially improves the radiographic appearance by decreasing enhancement and edema.6 Furthermore, pseudoprogression, a subacute radiation effect, is estimated to occur in 20% to 30% of patients with glioblastoma in whom the first postradiation MRI shows an increase in contrast enhancement that subsides with time without intervention.7,8 This phenomenon likely results from transiently increased permeability of the tumor vasculature from irradiation, and its imaging appearance could potentially improve in the presence of bevacizumab.

To address the limitations in the conventional MRI assessment of gliomas in an era of bevacizumab, the RANO working group has developed new guidelines for assessing treatment response in brain tumors.3 The RANO criteria incorporate FLAIR or T2 hyperintensity as a surrogate for nonenhancing tumor in determining tumor progression, in addition to quantitative information for enhancing lesions and clinical status.

Radiographic criteria for response evaluation for low-grade glioma (LGG) are challenging and have not been established.9 LGG usually do not show significant contrast enhancement on MRI, although some faint patchy enhancement is present in approximately 10% of LGG (Figure 2).10 FLAIR sequences provide the best delineation of WHO grade II glioma, although the exact relation between these sequences and the histologic tumor margin has not been established.11,12 Volumetric measurements based on FLAIR images are sensitive to subtle volume shrinkage in response to therapy and are promising as a valuable tool for response assessment in LGG.13,14

MR Spectroscopy

Proton magnetic resonance spectroscopy (MRS) has been in use for more than 20 years.15 It is of interest to clinicians because it allows for the noninvasive biochemical characterization of a region of interest. It is also appealing because it does not require additional software or time-consuming and sophisticated postprocessing.16

Several metabolic parameters interrogated by MRS are useful in brain tumor evaluation. Most brain tumors have decreased N-acetyl aspartate (NAA) signals, and often also have increased choline (Cho) levels, leading to increased Cho/NAA ratios.15 NAA is thought to be of neuronal origin and is presumably decreased in brain tumors because it is displaced by infiltrating tumor cells.17 The Cho peak is derived from contributions from several compounds involved in phospholipid membrane synthesis and degradation,15 and the elevations in Cho level are believed to be caused by high membrane turnover in brain tumors.

The total creatine peak, which is composed of creatine and phosphocreatine, has a role in glycolysis

Figure 2
Figure 2

MRI images in a patient presenting with a general tonic-clonic seizure. (A) T1-weighted image shows a hypointensity lesion in the right parietal region. (B, C) T2-weighted and fluid-attenuated inversion recovery images show a hyperintensity lesion with little edema. (D) T1-weighted image with contrast shows a nonenhancing lesion. Pathology was proven to be a grade II oligodendroglioma.

Citation: Journal of the National Comprehensive Cancer Network J Natl Compr Canc Netw 12, 11; 10.6004/jnccn.2014.0156

and is therefore believed to reflect the energetic state of the tumor. It is often used as the reference point for the quantification of other metabolites because it is believed to have the least variation in MRS studies in any given tissue, although regional variations have been reported.17

The lactate and lipid peaks overlap and are often difficult to separate. Lactate is likely to arise from an increased metabolic rate and is usually elevated in high-grade gliomas (HGG) and metastases.17 It may also result from decreased clearance of the metabolite from necrotic areas. Lipid peaks are also often elevated in HGG and metastases and are often seen in not only the necrotic areas, but also the contrast-enhancing areas.

MRS in Tumor Diagnosis and Grading

A brain mass seen on conventional MRI can reflect a range of differential diagnoses, including abscess, tumefactive demyelination, and ischemic lesions.15 Separating out those that are not neoplastic is beneficial, because this can influence intervention and prognostication.

Surgery for diagnosis and tumor grading remains the gold standard. However, MRS can be particularly helpful when the tumor is surgically inaccessible or not completely resectable, because it can indicate the area that is most likely to be of higher grade and, therefore, the biopsy target.18,19 This can be particularly helpful for determining the borders of infiltrative gliomas so that a near-gross-total resection can be attempted.20 To aid with this, it is important to establish robust markers for different tumor types. One project that has attempted this is the International Network for Pattern Recognition of Tumours Using Magnetic Resonance (INTERPRET).21 The INTERPRET study has collected spectra from brain tumors with known histology from multiple institutions throughout Europe to develop computerized data-recognition schemes to aid radiologists in diagnosis and grading.

MRS has been used to determine glioma grade, often in combination with MR diffusion or perfusion, and results have been compared with the actual histologic grade.2224 Tumor Cho/NAA ratios have been found to be higher in HGGs than in LGGs,23 and the NAA/Cr ratios lower in HGGs than in LGGs.24 Interestingly, although the peritumoral hyperintensity of gliomas on conventional MRI is nonspecific, representing vasogenic edema and/or infiltrative tumor, MRS has been able to determine that Cho/NAA and Cho/Cr are higher in HGGs than in LGGs, helping to delineate tumor extension, and indicating that this area contains useful spectra for tumor grading using this method.23

MRS in Determining Prognosis

Several studies have been able to correlate MRS with the clinical outcomes of overall survival and/or progression-free survival using spectra taken at different time points relative to diagnosis and treatment (Table 1,2538 available online, in this article, at JNCCN.org). At initial presurgical imaging, patients with an elevated Cho/NAA ratio had decreased overall survival after subsequent treatment.25 This was especially true for those with elevated lipid and lactate within the same area on presurgical MRS.25,26

MRS in Determining Treatment Response

MRS is also appealing to clinicians because it may be able to predict early treatment response or failure, allowing for an earlier change in treatment if needed. Some studies have shown a decrease in Cho in response to radiation treatment,39 and that early increases in Cho during radiation treatment are associated with tumor recurrence. Interestingly, this change can precede increased contrast enhancement on conventional MRI by 1 to 2 months.40

MRS can be used to differentiate true disease progression from radiation treatment pseudoprogression, which is difficult to do with conventional MRI. Studies have found that Cho/Cr and Cho/NAA ratios are higher in recurrent disease than in radiation necrosis, and that NAA/Cr ratios are lower.41,42 Cutoff values for tumor criteria for each of these ratios can even be determined.42

One important caveat when interpreting any MRS (or diffusion MRI or MR perfusion) study that uses the normal-appearing contralateral side of the brain as an area for comparison or normalization—and many studies use this method—is that the contralateral hemisphere in patients with brain tumors may not actually be normal. Tumor cells can be present in the contralateral hemisphere despite a normal-appearing MRI or MRS, partly because of the relatively large voxels required for MRS and the partial volume effect of small proportions of infiltrating tumor cells are difficult to resolve.

Diffusion MRI

The apparent diffusion coefficient (ADC) is acquired by diffusion-weighted imaging and is a quantitative representation of the mobility of water molecules in the imaged tissue. It is often inversely related to the cellularity of the tissue, which can impede the movement of water molecules. Different intracranial masses have different, albeit overlapping, ADC values and this can be a useful adjunct to conventional MRI for lesion diagnosis. These techniques are not in widespread use, but prospective validation studies are underway.

Diffusion tensor imaging (DTI) measures the directional movement of water in at least 6 noncollinear directions. Derivatives of DTI can highlight fiber tract patterns in 3 dimensions and their connectivity. For diseases in which the fiber tracts are destroyed, DTI can reflect histologic components and differentiate between lymphoma and glioblastoma, and between meningiomas with WHO grade I histology and atypical meningiomas. DTI has also been used to delineate among abscesses, cystic metastases, and necrotic glioblastomas.43 Because DTI allows for visualization of fiber tracts, it can also be helpful for surgical planning, especially when a large mass has displaced the fiber tracts.44 It may also be useful for a more precise sculpting of the boost radiation in intensity-modulated radiation treatment planning.45

Diffusion MRI in Tumor Diagnosis and Grading

Much interest has been shown in using diffusion MRI as an adjunct to diagnose brain masses and grade primary brain tumors. Not only is diffusion MRI noninvasive, but images can be easily obtained on conventional MRI machines. DTI was able to differentiate brain abscess, necrotic glioblastoma, and cystic metastases, which can all look similar on conventional MRI. One study segmented each lesion into nonoverlapping zones: cystic cavity, enhancing rim, and different areas of edema. Using different measurements and patterns generated from these measurements, obtained through processing of the DTI data, researchers found that differences in the enhancing rim could differentiate glioblastoma from metastasis and that differences in the cystic cavity could be used to identify abscess from these other disease entities.43 DTI has been used in a similar fashion to differentiate primary CNS lymphoma from glioblastoma46 and atypical from classic meningioma.44,47

Measurements obtained from DTI data have been used to measure cellularity and tumor infiltration and to determine astrocytic tumor grade.48 Researchers have been able to fuse the anatomic imaging of each patient with the DTI imaging so that their results could be correlated with the histopathology only from the region of interest that was biopsied or resected. Other groups have also had success with astrocytic tumor grading using different ADC parameters.49 However, these studies overwhelmingly exclude tumors with any oligodendroglioma component, which may make generalization difficult.

Diffusion MRI in Prognosis

Evidence suggests that diffusion MRI can be used to predict both progression-free and overall survivals in patients with HGG. One group showed that measurements derived from serial ADC from intratreatment MRI correlated well with overall survival. They performed serial diffusion MRI scans 1 week before the beginning of first-line radiation treatment, and then at 1, 3, and 10 weeks after the initiation of radiation. Subsequent MRI scans occurred at 2- to 3-month intervals. This group created a functional diffusion map (fDM), on a voxel-by-voxel basis, of the serial ADC data to quantify the change in diffusion during and after treatment. They were able to define a threshold percentage change in diffusion that was prognostic for median survival as early as 3 weeks after the start of radiation treatment. When they combined the 3-week fDM with the conventional radiologic response at 10 weeks, a composite index was generated that could define 3 groups of patients with distinct median overall survival times.29 Another group used fDMs derived before first-line chemoradiation and 4 weeks after completion of radiation.30 These imaging time points are the more common clinical ones. These researchers examined the volume fraction of tissue that showed changes in ADC and were able to correlate these with progression-free and overall survivals (Table 1,2538 available online, in this article, at JNCCN.org).

Diffusion MRI in Determining Treatment Response

ADC maps have also been combined with perfusion MRI in an attempt to determine the markers that identify an early treatment response or failure, so that treatment can be changed earlier in patients with markers for failure. One study of patients with HGG on first-line chemoradiation treatment derived ADC and cerebral blood volume (CBV) maps pretreatment and at 3 weeks midtreatment.33 The investigators developed a composite biomarker using these 2 maps to define 3 groups of patients who had different median overall survivals: nonresponders, partial responders, and responders.

Diffusion MRI has been used to help differentiate true disease progression from pseudoprogression. In a study, ADC maps and histogram analyses were derived from patients with glioblastoma who showed new or enlarged enhancing lesions after completion of first-line chemoradiation with temozolomide.50 The patients were defined as having pseudoprogression or true progression based on confirmation contrast-enhanced MRI after 6 cycles of adjuvant treatment. The researchers were able to distinguish a cutoff point on histogram analysis to differentiate between patients with true progression and those with pseudoprogression.

MR Perfusion

The physics behind MR perfusion is more complex than for CT perfusion, largely because of the nonlinear relationship of the contrast bolus concentration to the tissue attenuation. In general, perfusion processing can be used to assess blood volume, velocity, and oxygenation. Two methods can be used to obtain perfusion information using an intravascular exogenous nondiffusible contrast agent, usually gadolinium-based (Gd-DTPA).

One method using Gd-DTPA is called dynamic susceptibility contrast-enhanced MR perfusion (DSC). The other method is called dynamic contrast-enhanced MR perfusion (DCE), also known as permeability MRI. DCE uses the serial acquisition of T1-weighted images before, during, and after Gd-DTPA injection. The derived signal intensity versus time curve reflects a composite of vessel permeability, tissue perfusion, and extravascular extracellular space. It reflects the washin, plateau, and wash-out of the bolus and provides information about the tissue properties.

DSC is also called bolus-tracking or perfusion-weighted imaging. CBV and cerebral blood flow (CBF) can be derived from these data. For brain tumors, CBV is quite robust, requires less post-processing, and is widely used.51 One study comparing, among other techniques, DSC and DCE, found that DSC showed better diagnostic performance in distinguishing recurrent HGGs from stable disease.52

There can be considerable variation between MRI centers, and therefore standardization and optimization of protocols are concerns with MR perfusion. Several efforts are underway to address these issues, including involvement by the American College of Radiology Imaging Network, whose protocols are becoming the de facto standard for many clinical trials.

MR Perfusion in Tumor Diagnosis and Grading

Just as with the MRI techniques mentioned previously, interest has been shown in using MR perfusion as an adjunct to conventional MRI in the diagnosis of brain lesions, again because it is noninvasive and can have prognostic and treatment implications. One group was able to use MR perfusion in distinguishing several entities from each other, including HGGs, LGGs, hemangioblastomas, abscesses, schwannomas, meningiomas, primary CNS lymphomas, and metastases.53 This study used a region of interest that was the most enhancing on T1-weighted Gd-DTPA images and was not able to distinguish HGG from metastasis, meningioma, or CNS lymphoma. This same group was able to use MR perfusion to distinguish between HGG and metastasis by selecting a region of interest that involved the peritumoral edema, possibly because this area is infiltrated by tumor cells in HGG, but is likely vasogenic edema in metastasis, which has a lower CBV.54

Studies have shown some benefit to using MR perfusion to differentiate different glioma grades. Most studies have tried to establish cutoff values in CBV or CBF to separate HGGs from LGGs.34,55,56 The cutoff values have varied from study to study, likely because of differences in methods for selecting the patient population (including the inclusion or exclusion of tumors with oligodendroglial elements) and the regions of interest, and differences in statistical methods.

MR Perfusion in Prognosis

Correlating CBV using MR perfusion-derived parameters with prognosis has been an active area of interest. In general, a higher CBV is associated with a poorer outcome.3438 Some studies have noted that oligodendrogliomas often have high CBV, which is often a marker for higher-grade histopathology in other glioma types, but without the expected poor prognosis (Table 1,2538 available online, in this article, at JNCCN.org.

MR Perfusion in Determining Treatment Response

CBV has been found to have some correlation with treatment response. In light of the difficulties with conventional MRI in evaluating treatment response to bevacizumab, 1 group examined patients with recurrent HGG treated with bevacizumab and correlated CBV changes before and after treatment with progression-free survival, overall survival, and risk of death.37,57 They found a threshold value and discovered that both the pretreatment and posttreatment CBV could predict overall survival. Posttreatment CBV could also predict progression-free survival. When both the pretreatment and posttreatment CBV was above the threshold, patients had a significantly worse overall survival.

MR perfusion has been used to help differentiate progressive disease from radiation necrosis. One group used non-model-based indices of signal intensity-time curves to analyze their data, partly to show that complicated physiologic models are unnecessary, noting that such indices have been used previously for other solid tumors.58 They believe that these indices can be helpful so that MR perfusion can be used more routinely, without having to use time-consuming models, and would be ideal for multicenter trials because they do not require technical expertise for the data analysis. Several indices were used and found to be significantly different among the groups.

Although each has different limitations, these newer MRI techniques—spectroscopy, diffusion, perfusion—are all powerful tools in the adjunctive diagnosis of primary brain tumors, and also have a role in predicting prognosis and determining treatment response.

Conclusions

MRI is a powerful and flexible instrument for evaluating patients with primary brain tumors. The integration of the RANO criteria into treatment evaluation helps reduce early termination of effective therapies because of treatment-associated imaging changes. Advanced aspects of MRI, including spectroscopy, diffusion, and perfusion, provide dynamic information related to brain tumor response and progression. Further efforts to develop quality assurance metrics and standard interpretation algorithms will increase uniformity as these components are more widely deployed.

The authors have disclosed that they have no financial interests, arrangements, affiliations, or commercial interests with the manufacturers of any products discussed in this article or their competitors.

EDITOR

Kerrin M. Green, MA,Assistant Managing Editor, JNCCN—Journal of the National Comprehensive Cancer Network

Ms. Green has disclosed that she has no relevant financial relationships.

CE AUTHORS

Deborah J. Moonan, RN, BSN, Director, Continuing Education & Grants, has disclosed that she has no relevant financial relationships.

Ann Gianola, MA, Manager, Continuing Education & Grants, has disclosed that she has no relevant financial relationships.

Kristina M. Gregory, RN, MSN, OCN, Vice President, Clinical Information Operations, has disclosed that she has no relevant financial relationships.

Rashmi Kumar, PhD, Senior Manager, Clinical Content, has disclosed that she has no relevant financial relationships.

Maria Ho, PhD, Oncology Scientist/Senior Medical Writer, has disclosed that she has no relevant financial relationships.

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Correspondence: L. Burt Nabors, MD, Department of Neurology, Division of Neuro-Oncology, University of Alabama at Birmingham, 510 20th Street South, FOT 1020, Birmingham, AL 35294. E-mail: bnabors@uab.edu

Supplementary Materials

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    MRI images show a large mass in a patient presenting with hemiparesis on the right side. (A) T1-weighted image shows a hypointensity lesion in the left frontal-parietal region. (B, C) T2-weighted and fluid-attenuated inversion recovery images show a heterogeneous hyperintensity lesion with surrounding edema. (D) T1-weighted image with contrast shows a heterogeneous ring enhancing lesion, a second area of enhancement posterior to the major lesion, and vasogenic edema. Pathology was consistent with glioblastoma.

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    MRI images in a patient presenting with a general tonic-clonic seizure. (A) T1-weighted image shows a hypointensity lesion in the right parietal region. (B, C) T2-weighted and fluid-attenuated inversion recovery images show a hyperintensity lesion with little edema. (D) T1-weighted image with contrast shows a nonenhancing lesion. Pathology was proven to be a grade II oligodendroglioma.

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