Radiologic Features and Surgical Strategy of Hemangioblastomas with Enhanced Cyst Wall

Advanced magnetic resonance imaging findings of cerebellar hemangioblastomas: A report of three cases and a literature review

On conventional magnetic resonance imaging (MRI), hemangioblastomas typically appear as mural nodules with an adjacent surrounding cyst or a solid mass in the cerebellum. However, hemangioblastomas sometimes cannot be reliably distinguished using this imaging technique from other tumors, especially pilocytic astrocytomas and metastatic tumors, because of their similar imaging findings and locations. Herein, we report three cases of cerebellar hemangioblastomas and review their findings on conventional and advanced MRI, including diffusion-weighted imaging (DWI), dynamic susceptibility-weighted contrast-enhanced perfusion-weighted imaging (DSC-PWI), and magnetic resonance spectroscopy (MRS). Solid contrast-enhanced lesions of hemangioblastomas showed increased apparent diffusion coefficient values on DWI, increased relative cerebral blood volume ratio on DSC-PWI, and high lipid/lactate peak on MRS. Therefore, advanced MRI techniques can be helpful in understanding the pathological and metabolic changes of hemangioblastomas and may be useful for their characterization.

Hemangioblastoma masquerading as a ring enhancing lesion in the cerebellum: A case report

RATIONALE

Hemangioblastomas (HGBMs) are very rare, and the cerebellum is usually the most common site of occurrence. HGBMs with ring-enhanced walls are often misdiagnosed as metastases, abscesses, glioblastomas, tuberculomas, and demyelinating diseases. Thus, we present a rare case of HGBM masquerading as a ring-enhancing lesion in the cerebellum.

PATIENT CONCERNS

We present a 33-year-old female who was admitted to our department because of headaches, unstable walking, and visual loss in both eyes. Cranial nerve examination revealed deficits in cranial nerve II.

DIAGNOSIS

Magnetic resonance imaging revealed 2 cystic lesions in the cerebellum, with irregular ring-enhanced cyst walls composed of smaller nodular parts. Immunohistochemical staining of resected specimens established HGBM.

INTERVENTIONS

The lesions were completely resected using a right retrosigmoid approach.

OUTCOMES

Two years of follow-up revealed no recurrence of her symptoms or tumor. She is currently well and performs her daily duties.

LESSONS

HGBMs with enhanced cysts are often misdiagnosed by radiology because of their ring-enhanced nature. Computed tomography angiography may be the best modality for differentiating cerebellar HGBM from other ring-enhancing lesions. Surgery is the gold standard of treatment for these lesions.

Hemangioblastoma with Contrast-Enhanced Cystic Wall: When the Surgical Rule Must Not Be Respected

OBJECTIVE

The purpose of this paper is to describe the variation of surgical plan and technique required in a rare subset of hemangioblastomas compared with the accepted general strategy. The established rule in hemangioblastoma surgery is to avoid cyst wall removal, as it is not neoplastic, and it will not recur if mural nodule is completely removed. However, the wall of the associated cyst is occasionally enhanced by gadolinium on preoperative magnetic resonance imaging.

METHODS

We present the case of a patient with a hemangioblastoma that was progressively compressed by a growing cyst, with the final appearance of a contrast-enhanced cyst wall. We collected similar cases reported in the literature.

RESULTS

Our study points out the need for a tailored preoperative strategy, the usefulness of intraoperative fluorescent dyes, and the crucial role of frozen section histopathologic analysis to confirm diagnosis and optimize treatment.

CONCLUSIONS

When a hemangioblastoma is associated with a contrast-enhanced cyst, care must be taken to intraoperatively confirm the presence of neoplastic cells and eventually remove the neoplastic cyst wall to reduce the risk of recurrence.

CT and MRI characteristic findings of sporadic renal hemangioblastoma: Two case reports

RATIONALE

Hemangioblastomas in the kidney are rare. Although a few cases of renal hemangioblastoma (RH) have been reported, the content of these articles mainly focused on clinical and pathological research, with minimal descriptions of radiologic findings. Moreover, there are no descriptions of magnetic resonance imaging (MRI) with enhancement of this condition. Herein, we report 2 cases of RH with computed tomography (CT) and MRI findings.

PATIENT CONCERNS

Two patients presented to our institution because of dull pain in the left abdomen, and a mass in the left kidney was found by ultrasound examination in each case. The patient had no special family history. Physical examination revealed no obvious tenderness or percussion pain in the renal and ureteral walking areas, and there was no obvious mass. Routine blood and urine tests were normal, and the serum tumor markers were negative. No obvious lesions were found on imaging of the other body parts.

DIAGNOSIS

Similar radiologic findings were observed in both cases and mimicked those of cavernous hemangiomas of the liver, including peripheral nodular enhancement in the corticomedullary phase, progressive centripetal enhancement in the nephrographic and delayed phases, and occasional complete "filling in" in the delayed phase. We made a radiologic diagnosis of renal clear cell carcinoma for patient 1 and suspected renal clear cell carcinoma for patient 2, but the pathological results showed RH.

INTERVENTIONS

Given the suspicion of renal cell carcinoma, both patients underwent partial nephrectomy.

OUTCOME

The recovery of the two patients was uneventful, and there was no evidence of local recurrence or metastasis many years after surgery.

LESSONS

RH is a rare benign tumor that can be easily misdiagnosed as clear cell carcinoma. Characteristic CT and MRI manifestations may improve preoperative diagnostic accuracy to avoid surgery or indicate nephron-sparing surgery.

Central nervous system hemangioblastomas: An age-stratified analysis

BACKGROUND

Hemangioblastomas (HBs) are rare and understudied. The impact of age on clinical features, optimal treatment, and postoperative outcome in HBs has not been systemically studied.

MATERIALS AND METHODS

We performed an institutional study in the West China Hospital, including patients diagnosed with hemangioblastomas between October 2011 and October 2016. Clinical data and surgical outcomes were compared among three different age groups (0-20, 21-59, and ≥ 60 years). We also studied surgical prognostic factors.

RESULTS

187 patients (102 males and 85 females) were identified. HBs in spinal locations were more prevalent in children and adolescents, while the most common site in young and old-age adults was the cerebellum (P = 0.023). Risk of Von Hippel-Lindau syndrome (VHL) was negatively correlated with patient age (P = 0.003). 47.6 % of patients aged 0-20, 23 % of patients aged 21-59, and 6.45 % of patients aged ≥60 years were diagnosed with VHL. Older aged patients had a significantly lower risk of VHL and had a lower tumor recurrence rate. Surgical resection was an adequate and sufficient procedure in all age groups with a favorable surgical outcome (P = 0.823). Solid tumor, VHL disease, and localization in the brainstem were associated with poor outcome in patients with hemangioblastomas.

CONCLUSIONS

Our study showed that HBs in elderly patients were mostly included in the cerebellum and had a solid configuration and large size, while HBs in children were mainly localized in the spinal cord. VHL disease was more common in children and adolescents but rare in patients older than 60 years. The present study found no excess surgical mortality and risks for HBs in elderly patients or children than in younger adults.

Machine Learning Decision Tree Models for Differentiation of Posterior Fossa Tumors Using Diffusion Histogram Analysis and Structural MRI Findings

We applied machine learning algorithms for differentiation of posterior fossa tumors using apparent diffusion coefficient (ADC) histogram analysis and structural MRI findings. A total of 256 patients with intra-axial posterior fossa tumors were identified, of whom 248 were included in machine learning analysis, with at least 6 representative subjects per each tumor pathology. The ADC histograms of solid components of tumors, structural MRI findings, and patients' age were applied to construct decision models using Classification and Regression Tree analysis. We also compared different machine learning classification algorithms (i.e., naïve Bayes, random forest, neural networks, support vector machine with linear and polynomial kernel) for dichotomized differentiation of the 5 most common tumors in our cohort: metastasis (n = 65), hemangioblastoma (n = 44), pilocytic astrocytoma (n = 43), ependymoma (n = 27), and medulloblastoma (n = 26). The decision tree model could differentiate seven tumor histopathologies with terminal nodes yielding up to 90% accurate classification rates. In receiver operating characteristics (ROC) analysis, the decision tree model achieved greater area under the curve (AUC) for differentiation of pilocytic astrocytoma (p = 0.020); and atypical teratoid/rhabdoid tumor ATRT (p = 0.001) from other types of neoplasms compared to the official clinical report. However, neuroradiologists' interpretations had greater accuracy in differentiating metastases (p = 0.001). Among different machine learning algorithms, random forest models yielded the highest accuracy in dichotomized classification of the 5 most common tumor types; and in multiclass differentiation of all tumor types random forest yielded an averaged AUC of 0.961 in training datasets, and 0.873 in validation samples. Our study demonstrates the potential application of machine learning algorithms and decision trees for accurate differentiation of brain tumors based on pretreatment MRI. Using easy to apply and understandable imaging metrics, the proposed decision tree model can help radiologists with differentiation of posterior fossa tumors, especially in tumors with similar qualitative imaging characteristics. In particular, our decision tree model provided more accurate differentiation of pilocytic astrocytomas from ATRT than by neuroradiologists in clinical reads.