Preoperative vascular heterogeneity based on dynamic susceptibility contrast MRI in predicting spatial pattern of locally recurrent high-grade gliomas.

OBJECTIVES: To investigate if spatial recurrence pattern is associated with patient prognosis, and whether MRI vascular habitats can predict spatial pattern. METHODS: In this retrospective study, 69 patients with locally recurrent high-grade gliomas (HGGs) were included. The cohort was divided into intra-resection cavity recurrence (ICR) and extra-resection cavity recurrence (ECR) patterns, according to the distance between the location of the recurrent tumor and the resection cavity or surgical region. Four vascular habitats, high angiogenic tumor, low angiogenic tumor, infiltrated peripheral edema, and vasogenic peripheral edema, were segmented and vascular heterogeneity parameters were analyzed. The survival and diagnostic performance under different spatial recurrence patterns were analyzed by Kaplan-Meier and ROC. A nomogram model was constructed by regression analysis and validated by bootstrapping technique. RESULTS: Progression-free survival (PFS) and overall survival (OS) were longer for ICR (n = 32) than those for ECR (n = 37) (median PFS: 8 vs. 5 months, median OS: 17 vs. 13 months, p < 0.05). MRI vascular habitat analyses showed ECR had higher median relative cerebral blood volume (rCBVmedian) at each habitat than ICR (all p < 0.01). The rCBVmedian at IPE had good diagnostic performance (AUC: 0.727, 95%CI: 0.607, 0.828). The AUC of the nomogram based on MRI vascular habitats and clinical factors was 0.834 (95%CI: 0.726, 0.913) and was confirmed as 0.833 (95%CI: 0.830, 0.836) by bootstrapping validation. CONCLUSIONS: The spatial pattern of locally recurrent HGGs is associated with prognosis. MRI vascular heterogeneity parameter could be used as a non-invasive imaging marker to predict spatial recurrence pattern. CLINICAL RELEVANCE STATEMENT: Vascular heterogeneity parameters based on MRI vascular habitat analyses can non-invasively predict the spatial patterns of locally recurrent high-grade gliomas, providing a new diagnostic basis for clinicians to develop the extent of surgical resection and postoperative radiotherapy planning. KEY POINTS: • Intra-resection cavity pattern was associated with longer progression-free survival and overall survival in locally recurrent high-grade gliomas. • Higher vascular heterogeneities in extra-resection cavity recurrence than in intra-resection cavity recurrence and the vascular heterogeneity parameters had good diagnostic performance in discriminating spatial recurrence pattern. • A nomogram model based on MRI vascular habitats and clinical factors had good performance in predicting spatial recurrence pattern.

Gd-EOB-DTPA-Enhanced Magnetic Resonance Imaging Combined with T1 Mapping Identifies Dysplastic Module and Hepatocellular Carcinoma: A Retrospective Study.

BACKGROUND: Hepatocellular carcinoma (HCC) is the leading type of liver cancer in adults, often resulting in fatal outcomes for those with cirrhosis. Dysplastic nodule (DN) is a liver nodule that is substantial in size, ranging from 1-2 cm. However, accurately distinguishing between DN and HCC on imaging has posed a challenge. OBJECTIVE: The aim of this study is to assess the usefulness of Gd-EOB-DTPA-enhanced MRI T1 mapping in distinguishing between DN and HCC. METHODS: This study analyzed 66 patients with confirmed HCC or DN who underwent Gd-EOB-DTPA-enhanced MRI T1 mapping before surgery or puncture at the Army Medical Center in China. The T1 values of each lesion were measured before and after Gd-EOB-DTPA administration, and various calculations were made, including absolute and percentage reduction in T1 value and coefficient of variation. The t-test was used to compare these values between the two groups, and the efficacy of T1 mapping values for differential diagnosis of HCC and DN was evaluated using the receiver operating characteristic curve (ROC). RESULTS: The study found that T1pre, T1hp, ΔT1, ΔT1%, and CV in the HCC group were significantly higher than in the DN group (p < 0.01). The accuracy of T1hp, ΔT1, and CVT1-hp in identifying HCC from DN was high, with AUCs of 0.955, 0.910, and 0.932, respectively. ΔT1% also had some accuracy, with an AUC of 0.818. CONCLUSION: Our results provide preliminary evidence that Gd-EOB-DTPA-enhanced MRI T1, CVT1-hp mapping, can be a valuable tool in diagnosing and differentiating between HCC and DN.

An experimental study on the early diagnosis of traumatic brain injury in rabbits based on a noncontact and portable system.

Closed cerebral hemorrhage (CCH) is a common symptom in traumatic brain injury (TBI) patients who suffer intracranial hemorrhage with the dura mater remaining intact. The diagnosis of CCH patients prior to hospitalization and in the early stage of the disease can help patients get earlier treatments that improve outcomes. In this study, a noncontact, portable system for early TBI-induced CCH detection was constructed that measures the magnetic induction phase shift (MIPS), which is associated with the mean brain conductivity caused by the ratio between the liquid (blood/CSF and the intracranial tissues) change. To evaluate the performance of this system, a rabbit CCH model with two severity levels was established based on the horizontal biological impactor BIM-II, whose feasibility was verified by computed tomography images of three sections and three serial slices. There were two groups involved in the experiments (group 1 with 10 TBI rabbits were simulated by hammer hit with air pressure of 600 kPa by BIM-II and group 2 with 10 TBI rabbits were simulated with 650 kPa). The MIPS values of the two groups were obtained within 30 min before and after injury. In group 1, the MIPS values showed a constant downward trend with a minimum value of -11.17 ± 2.91° at the 30th min after 600 kPa impact by BIM-II. After the 650 kPa impact, the MIPS values in group 2 showed a constant downward trend until the 25th min, with a minimum value of -16.81 ± 2.10°. Unlike group 1, the MIPS values showed an upward trend after that point. Before the injury, the MIPS values in both group 1 and group 2 did not obviously change within the 30 min measurement. Using a support vector machine at the same time point after injury, the classification accuracy of the two types of severity was shown to be beyond 90%. Combined with CCH pathological mechanisms, this system can not only achieve the detection of early functional changes in CCH but can also distinguish different severities of CCH.