Time-dependent diffusion MRI-based microstructural mapping for giant intracranial mesenchymal tumor with FET-CREB fusion: a case description
Introduction
Intracranial mesenchymal tumors are newly defined in the 2021 WHO Classification of Tumors of the Central Nervous System (1). Their primary molecular genetic hallmark is fusion of FET family genes (e.g., EWSR1) with CREB family transcription factors (e.g., CREB1). Rare cases lacking FET-CREB fusions have also been reported (2).
Morphologically, the tumor cells are relatively monomorphic and most commonly display epithelioid or plasmacytoid features. They contain a moderate amount of eosinophilic cytoplasm with indistinct cell borders. The nuclei are round to oval, with vesicular chromatin and often inconspicuous nucleoli. Nuclear atypia is generally mild to moderate. Scattered tumor cells with intranuclear pseudoinclusions may also be observed.
To date, only a limited number of retrospective studies have been published, and the majority of which focus primarily on genetic alterations (3-5). These tumors are typically well circumscribed and most frequently arise along the cerebral convexities, falx cerebri, tentorium, and cerebellopontine angle (5). Radiologically, they often resemble extra-axial brain tumors, making differentiation based solely on conventional morphological imaging challenging.
Diffusion-weighted imaging (DWI) and quantitative measurement of the apparent diffusion coefficient (ADC) can reflect tumor microstructural characteristics. However, conventional DWI is generally performed with a single effective diffusion time, which limits its ability to detect subtle microstructural changes within tumors (6). Time-dependent ADC measurements provide more detailed insights into tumor microarchitecture and have been applied in the evaluation of gliomas (7), prostate cancer (8), and endometrial carcinoma (9).
The time-dependent diffusion model based on IMPULSED (Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion) enables more accurate quantification of tumor microstructure by combining a single long diffusion-time pulsed gradient spin-echo (PGSE) acquisition with two low-frequency oscillating gradient spin-echo (OGSE) acquisitions. In the present study, we applied the IMPULSED model to intracranial mesenchymal tumors harboring FET-CREB fusions. To our knowledge, no prior studies have investigated this approach in this tumor type. Our findings may provide a foundation for future clinical risk stratification and longitudinal therapeutic monitoring.
Case presentation
All procedures performed in this study were in accordance with the ethical standards of the institutional and national research committees and with the Declaration of Helsinki and its subsequent amendments. Written informed consent was obtained from the patient’s guardians for the publication of this article and accompanying images. A copy of the written consent is available for review by the editorial office of this journal.
Clinical summary
A 7-year-old girl presented with a 3-month history of right-sided proptosis. She denied any history of trauma and reported no headaches, vomiting, or visual disturbances during the initial course. However, 10 days before admission, she developed intermittent nighttime headaches and right eye pain, with mild intensity and occurring approximately twice a week. One day before admission, she experienced a single episode of non-projectile vomiting. No seizures, abnormal limb movements, or visual blurring were reported.
Brain magnetic resonance imaging (MRI) performed at another institution demonstrated a right frontal mass measuring 10 cm × 7 cm × 9.4 cm, suggestive of an intracranial lesion with possible extracranial extension.
On admission to our hospital, the patient was fully alert, with a Glasgow Coma Scale score of 15 (verbal 4, eye-opening 5, motor 6). Physical examination revealed right-sided proptosis. The pupils were equal, round, and reactive to light, with a diameter of 2.5 mm bilaterally. Extraocular movements were intact, and no nystagmus was observed. There were no signs of meningeal irritation nor pathological reflexes. Muscle strength was graded IV in the left upper and lower extremities and V in the right extremities. Deep tendon reflexes were preserved, and muscle tone was normal.
Serum tumor markers, including alpha-fetoprotein (AFP) and human chorionic gonadotropin (hCG), were within normal limits.
Multimodal imaging technique and evaluation
Computed tomography (CT) demonstrated a large, well-defined, round mass with marked mass effect and no evident calcification. The adjacent calvarium showed erosive changes and cortical destruction (Figure 1). Brain MRI revealed a well-circumscribed lesion measuring 9.4 cm × 8.8 cm × 7.5 cm located along the right frontal convexity. The mass contained intratumoral cystic components and multiple flow voids. On conventional sequences, the lesion exhibited heterogeneous hypointensity on T1-weighted imaging and hyperintensity on T2-weighted imaging. Following contrast administration, there was marked enhancement of both the tumor and the adjacent dura; however, no dural tail sign was identified. Prominent intralesional vascular flow voids were observed, while peritumoral edema was minimal. Diffusion tensor imaging (DTI) (b=1,000) demonstrated compression and displacement of adjacent white matter tracts without evidence of tract disruption (Figure 1). Based on these imaging findings, an extra-axial neoplasm was suspected, with epithelioid hemangioendothelioma considered the leading diagnostic possibility.
DWI was performed using a routine sequence (performed using only one effective diffusion time) (b=1,000) along with time-dependent diffusion MRI, referring to the model setup by Jiang et al. (10). All scans were conducted on a 3.0 T scanner (Ingenia CX, Philips, Best, the Netherlands) with a 32-channel brain coil. No significant restriction in diffusion was observed with the routine sequence. The time-dependent diffusion MRI used a combination of OGSE and PGSE sequences. OGSE data were acquired at 25 Hz (OGSEN1) (effective diffusion time =10 ms, 1 cycle, b=0, 250, 500, 750, 1,000 s/mm2) and 50 Hz (OGSEN2) (effective diffusion time =5 ms, 2 cycles, b=0, 100, 200, 300 s/mm2). PGSE data were acquired with b=0, 300, 600, 900, 1,200, 1,500, 1,800 s/mm2.
For all sequences, the following parameters were used: three diffusion directions, repetition time/echo time =3,000/110 ms, field of view =220 mm × 220 mm, sampling resolution =2×2 mm2, slice thickness =5 mm, and 11 slices. Fat saturation was performed using Spectral Pre-saturation with Inversion Recovery (SPIR), and the SENSE factor was 3. The total scanning time was approximately 4 minutes 12 seconds (OGSEN1: 1 minute 21 seconds; OGSEN2: 36 seconds; PGSE: 2 minutes 15 seconds).
Time-dependent diffusion MRI signals were fitted using the IMPULSED model to extract microstructural parameters, including cell diameter (d), intracellular volume fraction (Vin), extracellular diffusivity (Dex), and cellularity (Figure 2). To improve reliability, signal intensity within the region of interest (ROI) was measured three times at different representative locations, and the average value was used for final analysis. The resulting parameters were as follows: d=37.9189 µm, Vin =0.1882, Dex =1.8444 µm2/ms and cellularity =0.5096 (Table 1).
Table 1
| Parameter | Mean | SD |
|---|---|---|
| d (μm) | 37.9189 | 5.1149 |
| Vin | 0.1882 | 0.0661 |
| Dex (μm2/ms) | 1.8444 | 0.2657 |
| Cellularity | 0.5096 | 0.2089 |
d, mean cell diameter; Dex, extracellular diffusion coefficient; SD, standard deviation; Vin, intracellular volume fraction.
En bloc surgery and perioperative treatment
Intraoperatively, marked calvarial erosion and destruction were confirmed (Figure 3). The tumor base was densely adherent to the dura mater and demonstrated a rich vascular supply, predominantly originating from the adjacent dura. A well-formed fibrous capsule was identified, providing a clear demarcation between the lesion and the surrounding brain parenchyma. Gross total en bloc resection of the mass, including the involved dura, was achieved. The operative duration was approximately 9 hours, with an estimated intraoperative blood loss of 2,500 mL. Postoperatively, the patient was admitted to the pediatric intensive care unit for 3 days and was subsequently discharged on postoperative day 10. At the time of discharge, muscle strength in the left limb had recovered to grade V.
Pathology and follow-up
Gross examination revealed a yellowish neoplastic mass with a soft consistency and a gelatinous, mucinous cut surface (Figure 3). Histopathological evaluation demonstrated sparsely distributed tumor cells with spindle-shaped, ovoid, or stellate morphology and low mitotic activity. The surrounding stroma exhibited prominent myxoid (mucinous) degeneration. Abundant fibrous collagenous septa subdivided the lesion into lobulated or nodular architectures. In addition, a conspicuous inflammatory infiltrate composed predominantly of lymphocytes and plasma cells was observed within the tumor stroma. The stroma was highly vascularized, characterized by thin-walled vessels and focal hemangioma-like dilatation.
Immunohistochemical staining showed that the tumor cells were positive for SMA, ATRX, EMA, and CD99, but negative for DES, S100, SSTR2, MYOD1, GFAP, OLIG2, CD34, and STAT6. No deletion of ATRX or loss of H3K27me3 expression was observed. Ki-67 staining revealed a labeling index of 2% (Figure 4). Fluorescence in situ hybridization confirmed a break in the EWSR1 gene. Based on these findings, the most plausible diagnosis was intracranial mesenchymal tumor with FET-CREB fusion.
At 7-month postoperative follow-up, the patient remained in good clinical condition, with no radiological evidence of recurrence or metastasis (Figure 5).
Discussion
Scholars first reported primary intracranial mesenchymal tumors with FET-CREB fusion in 2008 (11). In the 2021 WHO Classification of Tumors of the Central Nervous System, these tumors are categorized as a provisional entity under “Mesenchymal non-meningothelial tumors of uncertain differentiation”. Microscopically, the tumors typically show a variably collagenous stromal background, with fibrous septa partitioning tumor cells into nodular architectures, accompanied by abundant myxoid (mucinous) stroma. Intracranial mesenchymal tumors with FET-CREB fusion are locally aggressive and associated with a high recurrence rate (approximately 40%) and a median progression-free survival of 28 months (12). Therefore, histopathologic classification and risk stratification are of particular importance.
DWI is a noninvasive technique that quantifies the displacement of water molecules within tissues. Various microstructural components, including cell membranes and the extracellular matrix, restrict water diffusion, thereby influencing the ADC. Consequently, DWI-derived ADC metrics have been widely applied for histopathologic classification and risk stratification across diverse tumor types. However, under conventional PGSE sequences, the effective diffusion time typically exceeds 30 ms, predominantly probing larger cellular structures. As such, PGSE is limited to longer diffusion times, resulting in relatively constrained ADC measurements. In contrast, oscillating gradient spin-echo (OGSE) sequences shorten the effective diffusion time by applying oscillating gradient waveforms, enabling interrogation of diffusion over shorter temporal scales. Therefore, time-dependent diffusion MRI expands the measurable ADC spectrum, including absolute ADC changes and relative ADC changes, thereby providing additional microstructural information relevant to tumor characterization. In the present study, we characterized the microstructural features of an intracranial mesenchymal tumor harboring the FET-CREB fusion using the IMPULSED model. This approach enables quantification of biologically meaningful parameters, including cell diameter, Vin, Dex, and cellularity. Accumulating evidence from studies of other tumor types further supports the translational and clinical utility of this model. Kamimura et al. (7) evaluated ADC parameters derived from OGSE (50 Hz) and PGSE (0 Hz) sequences to differentiate glioblastoma (GBM) from intracranial metastases. They reported that absolute ADC values obtained from either OGSE (50 Hz) or PGSE (0 Hz) alone did not significantly distinguish the two entities. However, ADC changes and relative ADC changes between short diffusion times (OGSE) and long diffusion times (PGSE) demonstrated discriminatory capability, with both metrics significantly higher in brain metastases than in GBM. In a subsequent study by the same group (7), OGSE was applied to differentiate GBMs from primary central nervous system lymphomas (PCNSLs). At effective diffusion times of 7.1 and 44.5 ms, the 5th and 95th percentile ADC values in PCNSLs were significantly lower than those in GBMs. Notably, the corresponding 5th and 95th percentile values for ADC changes and relative ADC changes were significantly higher in PCNSLs than in GBMs, highlighting the added diagnostic value of diffusion time-dependent metrics. In extra-axial brain tumors, the same group further demonstrated the utility of OGSE in distinguishing functioning from nonfunctioning pituitary adenomas (PAs) (13). ADC changes between effective diffusion times of 7.1 and 36.3 ms were significantly greater in functioning PAs than in nonfunctioning PAs. Similarly, Maekawa et al. (14) investigated diffusivity alterations derived from time-dependent diffusion MRI for the characterization of extra-axial brain tumors. They observed that the greatest difference in mean diffusivity (MD) between PAs and other tumors (meningiomas and vestibular schwannomas) occurred between shorter diffusion times (OGSE, 6.5 ms) and longer diffusion times (PGSE, 35.2 ms), reflecting more pronounced diffusion time dependence. Beyond ADC-based metrics, time-dependent diffusion MRI provides quantitative microstructural parameters. Cao et al. (15) extracted Vin, cell diameter, cellularity, and Dex using time-dependent diffusion modeling. Vin, cellularity, and Dex demonstrated strong diagnostic performance in differentiating high-grade serous ovarian carcinoma from serous borderline ovarian tumors. Moreover, cellularity was positively correlated with P53 expression, whereas Dex showed a positive correlation with Pax-8 expression, suggesting potential links between diffusion-derived microstructural indices and molecular biomarkers. Time-dependent diffusion MRI may also serve as a predictive tool for therapeutic response. Wang et al. (16) reported that the cellularity index was independently associated with pathological complete response to neoadjuvant chemotherapy in breast cancer. A predictive model integrating clinical-pathological characteristics with cellularity outperformed a model based solely on clinical-pathological variables. Notably, cellularity achieved the highest area under the curve (AUC) in the luminal B subtype compared with other molecular subtypes, underscoring its potential subtype-specific predictive value.
Currently, the primary treatment for this disease is surgical intervention, with prognosis influenced by multiple factors (12), including younger age (<14 years), EWSR1-ATF1 fusion, and subtotal resection. For recurrent or incompletely resected tumors, postoperative radiotherapy and chemotherapy may be considered; however, the efficacy of these adjuvant treatments remains uncertain. These tumors are typically encapsulated by a fibrous layer, creating a distinct boundary between the tumor and surrounding normal brain tissue, thereby facilitating en bloc resection. In the present case, however, the tumor’s large size necessitated a substantial bone flap incision to achieve en bloc resection. Compared to the piecemeal resection group, the en bloc resection group exhibited lower total blood loss, transfusion rates, incidence of postoperative complications, and cerebrospinal fluid (CSF) dissemination (17,18). Despite relatively low cellular atypia and proliferation indices, there are occasional reports of rapidly progressive or recurrent tumors (2). Currently, long-term follow-up data remain limited, and the optimal radiotherapy and chemotherapy regimen remains unclear. Even with complete tumor resection during surgery, diligent long-term monitoring is crucial.
Conclusions
Intracranial mesenchymal tumors with FET-CREB fusion are a newly introduced subtype in the 2021 WHO Classification of Tumors of the Central Nervous System. The treatment options and efficacy assessment require further investigation. The IMPULSED-based imaging model proposed in this study can aid in the noninvasive investigation of histological heterogeneity among different individuals, thereby facilitating better personalized treatment selection.
Acknowledgments
None.
Footnote
Funding: None.
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-924/coif). The authors have no conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All procedures performed in this study were in accordance with the ethical standards of the institutional and national research committees and with the Declaration of Helsinki and its subsequent amendments. Written informed consent was obtained from the patient’s guardians for the publication of this article and accompanying images. A copy of the written consent is available for review by the editorial office of this journal.
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
References
- Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D, Hawkins C, Ng HK, Pfister SM, Reifenberger G, Soffietti R, von Deimling A, Ellison DW. The 2021 WHO Classification of Tumors of the Central Nervous System: a summary. Neuro Oncol 2021;23:1231-51. [Crossref] [PubMed]
- Panico F, Bianconi A, Bertero L, Palmiero R, Zeppa P, Ricci AA, Mangherini L, Cofano F, Rudà R, Garbossa D, Zenga F. Multidisciplinary treatment of a rare rapidly progressive intracranial myxoid mesenchymal tumor of uncertain differentiation FET-CREB fusion-negative. Neurol Sci 2025;46:1867-73. [Crossref] [PubMed]
- Gareton A, Pierron G, Mokhtari K, Tran S, Tauziède-Espariat A, Pallud J, Louvel G, Meary E, Capelle L, Chrétien F, Varlet P. ESWR1-CREM Fusion in an Intracranial Myxoid Angiomatoid Fibrous Histiocytoma-Like Tumor: A Case Report and Literature Review. J Neuropathol Exp Neurol 2018;77:537-41. [Crossref] [PubMed]
- Sciot R, Jacobs S, Calenbergh FV, Demaerel P, Wozniak A, Debiec-Rychter M. Primary myxoid mesenchymal tumour with intracranial location: report of a case with a EWSR1-ATF1 fusion. Histopathology 2018;72:880-3. [Crossref] [PubMed]
- Sloan EA, Chiang J, Villanueva-Meyer JE, Alexandrescu S, Eschbacher JM, Wang W, et al. Intracranial mesenchymal tumor with FET-CREB fusion-A unifying diagnosis for the spectrum of intracranial myxoid mesenchymal tumors and angiomatoid fibrous histiocytoma-like neoplasms. Brain Pathol 2021;31:e12918. [Crossref] [PubMed]
- Iima M, Kataoka M, Honda M, Ohashi A, Ohno Kishimoto A, Ota R, Uozumi R, Urushibata Y, Feiweier T, Toi M, Nakamoto Y. The Rate of Apparent Diffusion Coefficient Change With Diffusion Time on Breast Diffusion-Weighted Imaging Depends on Breast Tumor Types and Molecular Prognostic Biomarker Expression. Invest Radiol 2021;56:501-8. [Crossref] [PubMed]
- Kamimura K, Nakano T, Hasegawa T, Nakajo M, Yamada C, Kamimura Y, et al. Differentiating primary central nervous system lymphoma from glioblastoma by time-dependent diffusion using oscillating gradient. Cancer Imaging 2023;23:114. [Crossref] [PubMed]
- Wu D, Jiang K, Li H, Zhang Z, Ba R, Zhang Y, Hsu YC, Sun Y, Zhang YD. Time-Dependent Diffusion MRI for Quantitative Microstructural Mapping of Prostate Cancer. Radiology 2022;303:578-87. [Crossref] [PubMed]
- Ejima F, Fukukura Y, Kamimura K, Nakajo M, Ayukawa T, Kanzaki F, Yanazume S, Kobayashi H, Kitazono I, Imai H, Feiweier T, Yoshiura T. Oscillating Gradient Diffusion-Weighted MRI for Risk Stratification of Uterine Endometrial Cancer. J Magn Reson Imaging 2024;60:67-77. [Crossref] [PubMed]
- Jiang X, Li H, Xie J, McKinley ET, Zhao P, Gore JC, Xu J. In vivo imaging of cancer cell size and cellularity using temporal diffusion spectroscopy. Magn Reson Med 2017;78:156-64. [Crossref] [PubMed]
- Dunham C, Hussong J, Seiff M, Pfeifer J, Perry A. Primary intracerebral angiomatoid fibrous histiocytoma: report of a case with a t(12;22)(q13;q12) causing type 1 fusion of the EWS and ATF-1 genes. Am J Surg Pathol 2008;32:478-84.
- Mezzacappa FM, Smith FK, Zhang W, Gard A, Cabuk FK, Gonzalez-Gomez I, Monforte HL, Liang J, Singh O, Quezado MM, Aldape KD, Gokden M, Bridge JA, Chen J. Potential prognostic determinants for FET::CREB fusion-positive intracranial mesenchymal tumor. Acta Neuropathol Commun 2024;12:17.
- Kamimura K, Tokuda T, Kamizono J, Nakano T, Hasegawa T, Nakajo M, Ejima F, Kanzaki F, Takumi K, Nakajo M, Fujio S, Hanaya R, Tanimoto A, Iwanaga T, Imai H, Feiweier T, Yoshiura T. Time-dependent MR diffusion analysis of functioning and nonfunctioning pituitary adenomas/pituitary neuroendocrine tumors. J Neuroimaging 2025;35:e13254.
- Maekawa T, Hori M, Murata K, Feiweier T, Kamiya K, Andica C, Hagiwara A, Fujita S, Kamagata K, Wada A, Abe O, Aoki S. Investigation of time-dependent diffusion in extra-axial brain tumors using oscillating-gradient spin-echo. Magn Reson Imaging 2023;96:67-74. [Crossref] [PubMed]
- Cao Y, Lu Y, Shao W, Zhai W, Song J, Zhang A, Huang S, Zhao X, Cheng W, Wu F, Chen T. Time-dependent diffusion MRI-based microstructural mapping for differentiating high-grade serous ovarian cancer from serous borderline ovarian tumor. Eur J Radiol 2024;178:111622. [Crossref] [PubMed]
- Wang X, Ba R, Huang Y, Cao Y, Chen H, Xu H, Shen H, Liu D, Huang H, Yin T, Wu D, Zhang J. Time-Dependent Diffusion MRI Helps Predict Molecular Subtypes and Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer. Radiology 2024;313:e240288. [Crossref] [PubMed]
- Cao L, Tian S, Ma W, Ni Z, Tian G, Zhao Y, Wang Q, Xu Z, Wang J, Liang Z, Zhao H, Yang L, Wang B, Ma J. The tentative application of en bloc concept in the pediatric brain tumor: Experience from a large pediatric center in china. Front Oncol 2022;12:1018380. [Crossref] [PubMed]
- Patel AJ, Suki D, Hatiboglu MA, Abouassi H, Shi W, Wildrick DM, Lang FF, Sawaya R. Factors influencing the risk of local recurrence after resection of a single brain metastasis. J Neurosurg 2010;113:181-9. [Crossref] [PubMed]

