Purpose
We investigated the efficacy of pelvic magnetic resonance imaging (MRI) in the diagnosis of bone marrow involvement (BMinv) in diffuse large B-cell lymphoma (DLBCL) patients.
Patients and methods
This was a retrospective study of data from a previous study (NCT02733887). We included 171 patients who underwent bone marrow biopsy (BMB) and bone marrow smear (BMS), pelvic MRI, and whole-body positron emission tomography-computed tomography (PET/CT) from January 2016 to December 2019 at a single center. BMB/BMS and whole-body PET/CT results were used as reference standards against which we calculated the diagnostic value of pelvic MRI for BMinv in DLBCL patients. A chi-square test was used to compare detection rates, and a receiver operating characteristic curve was used to evaluate diagnostic value of pelvic MRI. Propensity-score matching was performed according to clinical information, and Kaplan-Meier curves were constructed to compare progression-free survival (PFS) and overall survival (OS) of patients.
Results
The BMinv detection rate of pelvic MRI (42/171) was higher (P = 0.029) than that of BMB/BMS (25/171), and similar to that of PET/CT (44/171; P = 0.901). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of pelvic MRI were 83.33%, 98.37%, 94.15%, 95.24%, and 93.80%, respectively. Median PFS values were as follows: BMB/BMS-positive, 17.8 months vs. BMB/BMS-negative, 26.9 months (P = 0.092); PET/CT-positive, 24.8 months vs. PET/CT-negative, 33.0 months (P = 0.086); pelvic MRI-positive, 24.9 months vs. pelvic MRI-negative, 33.1 months (P<0.001). Median OS values were as follows: BMB/BMS-positive, 22.3 months vs. BMB/BMS-negative, 29.8 months (P = 0.240); PET/CT-positive, 27.9 months vs. PET/CT-negative, 33.9 months (P = 0.365); pelvic MRI-positive, 27.3 months vs. pelvic MRI-negative, 35.8 months (P = 0.062).
Conclusion
Pelvic MRI is effective for detecting BMinv in DLBCL patients, providing a more accurate indication of PFS than BMB/BMS and PET/CT do. It may ultimately be used to improve the accuracy of clinical staging, guide patient treatment, and evaluate prognosis.