Whole body MRI with qualitative and quantitative analysis of DWI for assessment of bone marrow involvement in lymphoma

AIM

Our study aimed to investigate the role of qualitative and quantitative whole body MRI with DWI for assessment of bone marrow involvement (BMI) in newly diagnosed lymphoma using FDG PET-CT and bone marrow biopsy (BMB) as reference standard.

MATERIALS AND METHODS

We retrospectively evaluated 56 patients with newly diagnosed lymphoma (21 Hodgkin's lymphoma and 35 non-Hodgkin's lymphoma) who underwent random unilateral BMB, FDG PET-CT and Wb-MRI-DWI for initial staging. In a patient-based analysis, results of Wb-MRI-DWI were compared with FDG PET-CT and BMB. For quantitative analysis, mean ADC values of posterior iliac crest were correlated with BMI and bone marrow cellularity.

RESULTS

WB-MR-DWI obtained excellent concordance with FDG PET-CT both in HL (k = 1.000; 95% CI 1.000-1.000) and in DLBCL (k = 1.000; 95% CI 1.000-1.000). In other NHL, WB-MRI-DWI obtained a good correlation with BMB (k = 0.611; 95% CI 0.295-0.927) while FDG PET-CT had poor concordance (k = 0.067; 95% CI 0.372-0.505). WB-MR-DWI has no false negative errors but 4 false positive results consisting in focal lesions consensually reported by FDG PET-CT and resolved after therapy. No significant correlation between ADC mean value and BMI was found (p = 0.0586).

CONCLUSION

Our data suggest that Wb-MRI-DWI is a valid technique for BMI assessment in lymphoma patients, thanks to its excellent concordance with FDG PET-CT and good concordance with BMB (superior than FDG PET-CT). If further investigations will confirm our results on larger patient groups, it could become a useful tool in the clinical workup.

Risk of malignancy in pulmonary nodules: A validation study of four prediction models

OBJECTIVES

Clinical prediction models assess the likelihood of malignancy in pulmonary nodules detected by computed tomography (CT). This study aimed to validate four such models in a UK population of patients with pulmonary nodules. Three models used clinical and CT characteristics to predict risk (Mayo Clinic, Veterans Association, Brock University) with a fourth model (Herder et al. [4]) additionally incorporating (18)Fluorine-Fluorodeoxyglucose (FDG) avidity on positron emission tomography-computed tomography (PET-CT).

MATERIALS AND METHODS

The likelihood of malignancy was calculated for patients with pulmonary nodules (4-30mm diameter) and data used to calculate the area under the receiver operating characteristic curve (AUC) for each model. The models were used in a restricted cohort of patients based on each model's exclusion criteria and in the total cohort of all patients.

RESULTS

Two hundred and forty-four patients were studied, of whom 139 underwent FDG PET-CT. Ninety-nine (40.6%) patients were subsequently confirmed to have malignant nodules (33.2% primary lung cancer, 7.4% metastatic disease). The Mayo and Brock models performed similarly (AUC 0.895 and 0.902 respectively) and both were significantly better than the Veterans Association model (AUC 0.735, p<0.001 and p=0.002 respectively). In patients undergoing FDG PET-CT, the Herder model had significantly higher accuracy than the other three models (AUC 0.924). When the models were tested on all patients in the cohort (i.e. including those outside the original model inclusion criteria) AUC values were reduced, yet remained high especially for the Herder model (AUC 0.916). For sub-centimetre nodules, AUC values for the Mayo and Brock models were 0.788 and 0.852 respectively.

CONCLUSIONS

The Mayo and Brock models showed good accuracy for determining likelihood of malignancy in nodules detected on CT scan. In patients undergoing FDG PET-CT for nodule evaluation, the highest accuracy was seen for the model described by Herder et al. incorporating FDG avidity.