Researchers and clinicians interested in novel diagnostic images and image-guided procedures in tumor treatment.For high-grade glioma, the most dismal primary brain tumor, maximal surgical resection, followed by chemotherapy and radiotherapy, is the routine treatment regime. However, the post-operation lesions often show pseudoprogression or pseudoresponse on MRI images during the procedure, posing a dilemma regarding further treatment options for clinical practitioners (1). Although numerous developments are ongoing to facilitate post-operation glioma diagnosis, receiving histological results from tissue biopsies is still the mainstay diagnostic strategy. Amide-proton-transfer (APT) imaging is a novel molecular technique that gives contrast based on endogenous cellular proteins in tissue (2). The early preclinical and clinical results have showed that application of APT-weighted (APTw) imaging to malignant brain tumors has much potential for diagnosis and prognosis (3-7). This study was designed to validate the diagnostic accuracy of APTw image-guided biopsy in patients with suspected treatment effects vs. recurrent tumors.

Nineteen patients with uncertainty regarding treatment effects versus active tumor were recruited, and all patients provided written, informed consent. As shown in Fig. 1, MRI was done on a Philips 3T MRI scanner (Achieva), within three days prior to their surgical procedure. A fast 3D APTw imaging sequence (RF saturation power = 2 μT; saturation time = 800 ms; 15 slices of slice thickness = 4.4 mm) was used (4). To correct for B0 field inhomogeneity effects, APTw imaging was acquired with a six-offset protocol (±3, ±3.5, ±4 ppm from water), together with a WASSR scan (8). The total scan time was 10 min 40 sec. APTw images were calculated using MTRasym(3.5ppm) analysis (2).

Patients proceeded with their clinically indicated brain biopsy after MRI scanning. Two-to-four biopsy sites were chosen after reviewing APTw and conventional MR (T₂w, FLAIR and Gd-T₁w) images. Then, these ROIs were labeled on the co-registered MR image in the BrainLab neuro-navigation frameless biopsy system and tissues were obtained accordingly. Biopsies were hematoxylin-and-eosin stained (H&E) and Ki-67 (MIB-1 antibody)-stained to evaluate cellularity and proliferation, respectively. Pathology slides were reviewed by a neuropathologist, blinded to the imaging features, and the biopsied samples were divided into two groups: treatment effects or active tumor, based on mitosis, proliferation, and pleomorphism of tumor cells, and the proportion of radiation-induced necrosis. Tumor cell density (cellularity) and Ki-67 positive cells (proliferation) were counted by software ImagePro on microscope captured digital photos.

A neuroradiologist recorded the APTw intensities of all corresponding ROIs for each patient. The APTw signal intensity for each targeted tissue sample, compared with the contralateral normal brain area, was reported. Pearson’s correlation analysis was applied to evaluate the correlation between APTw intensities and cellularity or proliferation, t-test was used to assess the difference of APTw intensities between treatment effects and tumor recurrence. ROC analysis was conducted for APTw signals to differentiate treatment effect from active samples.

APTw image features of treatment effects and active tumor

53 samples were obtained totally (22 with treatment effects and 31 with active tumor). For treatment effects and active tumor (Fig. 2), T₂w MRI showed a hyperintense lesion (compared to contralateral brain tissue), and Gd-T1w imaging revealed a heterogeneous enhancing mass. However, on APTw MRI, treatment effects were found to be homogeneously isointense to mild hyperintense, while active tumor displayed clear heterogeneous hyperintensity.

Quantitative analysis

There were strong positive correlations between APTw signal intensities and cellularity (R = 0.640, P < 0.001), and between APTw signal intensities and proliferation of biopsies (R = 0.521, P < 0.001) (Fig. 3). The average APTw intensities were significantly lower in treatment effects and tumor recurrence (1.29 ± 0.48% vs. 2.97 ± 0.77%, P < 0.001) (Fig. 4). Using the pathological results as the gold standard, the ROC analysis showed that the area under curve (AUC) for APTw to differentiate between treatment effects and active tumor reached up to 0.959 (the cut-off APTw value was 2.27%, the sensitivity was 0.955, the specificity was 0.871) (Fig. 5).

Our initial data show that the APTw imaging signal, as a surrogate biomarker of active glioma, has the potential to differentiate treatment effects from tumor recurrence in brain cancer diagnosis and treatment. Registering APTw images to neuro-navigation would potentially improve the diagnostic accuracy of biopsy. APTw imaging is a more specific MRI technology that may eventually avoid biopsy in many patients that require a tissue only for diagnosis.