18F-FDG PET/CT is currently a standard imaging technology for diagnosis, staging, and prediction of prognosis in patients with HL or NHL. It has been extensively utilized in the managing of malignant lymphoma patients, and there is increasing evidence of the prognostic significance of PET/CT parameters [17].
In analyzing FDG PET, SUVmax is the most widely used index for various purposes relatively because of the suitability and great reproducibility of measurement; it reveals the metabolic activity of the most aggressive tumor cell. Recently, researchers have been minded by metabolic tumor volume (MTV) which is a measurement of tumor volume with a high metabolism, and total lesion glycolysis (TLG), which is the product of mean SUV and MTV. MTV and TLG are volume-based indexes that reflect tumor burden, and they are expected to be effective in prognosis prediction and response evaluation [1, 18, 19]. In our study, a total of 103 lesions were assessed in 40 patients, and quantitative indexes at baseline and the end of treatment (6–8 weeks after end of chemotherapy) are measured. We compare all baseline and post-therapy PET/CT parameters between the four groups, namely PMR (partial metabolic response) and CMR (complete metabolic response), which are collectively known as responsive lesions, SMD (stable metabolic disease) and PMD (progressive metabolic disease): grouped together as non-responsive lesions. We found that baseline SUV of the CMR group was significantly higher than that of SMD group, yet it is lower than that of PMR group. The pre-treatment SUV of PMR group was significantly higher than the SMD and PMD groups. The post-treatment SUV of the CMR group was significantly lower than that of all other groups. The post-treatment SUV of PMD group was significantly higher than all other groups (Fig. 5).
Our study results matched the study carried out by Huang et al. [20] in which response to treatment was assessed in patients after the completion of six to eight cycles of treatment. The complete remission rate [complete response (CR) + unconfirmed complete response (Cru)] and overall response rate after therapy were significantly higher in the low SUVmax group (pre-treatment SUVmax ≤ 9.0) than in the high SUVmax group.
There are several subtypes of aggressive lymphoma. These include AID-associated lymphoma, Burkitt lymphoma, CNS lymphoma, diffuse large B-cell lymphoma (DLBCL), mantle cell lymphoma, and peripheral T-cell lymphoma. Another significant impact of baseline SUVmax is the prediction of the presence of more aggressive histological components and suggestion of foci of aggressive transformation which has potential diagnostic and therapeutic implications. Ngeow et al. [21] observe that in a patient with indolent lymphoma, sites with SUV of > 10 suggest the possibility of transformation or the possibility of the presence of an aggressive component in addition to what is suggested by the histology. In our study, we noticed that patient with more aggressive histological types as T-cell lymphoma or DLBCL has the highest baseline SUVmax reaching about 26 and 17, respectively, yet the prediction of treatment response is multifactorial that is not only depend on histological type of the tumor.
Recent studies suggest that MTV and TLG are more inclusive parameters that better represent the whole metabolic tumor burden than SUVmax, but with a limitation point that they require accurate standardization of tumor segmentation. These studies suggest the usefulness of MTV and TLG for expectation of treatment response and prediction of prognosis [17]. However, in our study, baseline MTV and TLG did not surpass baseline SUVmax in terms of initial (baseline) response evaluation. No significant difference was found in our study between the baseline MTV and TLG in both responsive and non-responsive groups. Although we notice that the range of baseline MTV and TLG is low in responsive than non-responsive groups, it is clinically insignificant and their statistical analysis is insignificant (as their P values 0.11 and 0.9, respectively); the increase in baseline MTV and TLG is noticeable mainly in non-responder groups; however, it is statistically not accurate predicting of treatment response (Fig. 6).
In contrast to our finding, Albano et al. [22] conducted a prospective study that included 123 elderly patients initially diagnosed with HL. Comparison of baseline metabolic PET/CT quantitative parameters between no complete and complete response groups after first-line treatment was made. The baseline L-L SUV R (lesion-to-liver ratio), baseline L-BP SUV R (lesion-to-blood pool ratio), baseline MTV, and baseline TLG were significantly lower in the complete metabolic response group than in the no-complete response group (P values of 0.032, 0.042, 0.004, and 0.005, respectively).
Akhtari et al. [23] assumed that three-dimensional measurement of tumor burden measured on baseline PET/CT such as MTV and TLG might more precisely risk-stratify the patients. They evaluated 267 patients with a median follow-up of 4.96 years, of which 27 patients had relapse or refractory disease and 12 died. They stated that baseline MTV and TLG interrelated significantly with freedom of progression (FFP); patients with TMTV ˃ 268 and TLG ˃ 1703 had shorter FFP times and were to harbor bulky disease and staged as IIB-advanced disease.
On the contrary, Mettler et al. [24] in a retrospective study including 310 patients with baseline PET/CT scans available stated that baseline TMTV unsuccessfully predicted PFS and OS in patients diagnosed with advanced-stage Hodgkin lymphoma.
The utility of PET/CT in assessing response after the end of treatment has been confirmed in several studies. End-of-treatment FDG PET/CT is used to evaluate the efficacy of treatment, monitoring of residual tumor and predicting relapse [25, 26]. The percentage of ΔSUVmax (between baseline and end of therapy) is a semiquantitative method with excellent inter-observer agreement and improved prognostic value of E-PET (end-of-therapy PET) [21]. Itti et al. [27] reported that ΔSUVmax% > 72.9% is an important predictor of progression-free survival (PFS) at the end of treatment in DLBCL patients.
In our study, we noticed that ∆SUV and ∆TLG followed by ∆MTV, post-treatment MTV, post-treatment TLG, and post-treatment SUV (in descending order) had the largest area under the receiver operating characteristic (ROC) curve which arranges PET/CT variable according to their diagnostic performance (sensitivity and specificity) in distinguishing the responsive from the non-responsive group. All post-treatment quantitative PET/CT parameters were significantly lower than pre-treatment values in PMR, CMR, and SMD groups and significantly higher than pre-treatment values in the PMD group.
Our study results are also matched with other studies which include baseline and post-treatment quantitative PET/CT parameters. In a study done by Zhou et al. [28] with 43 patients investigated, 28 patients underwent both baseline and end-of-treatment PET/CT scan; these patients were also evaluated for 1 and 2 years to estimate progression-free survival (PFS) and revealed that the ΔSUVmax% between baseline and end-of-therapy PET was significantly different between the progression (n = 14) and progression-free groups (n = 14) (41.70% vs. 82.34%). When using ΔSUVmax% as a predictor of progression, patients with lower ΔSUVmax% (< 66.95%) had low PFS compared with those with higher ΔSUVmax% (> 66.95%). In our study, we suggested that ∆SUVmax of CMR group was significantly higher than that of all other groups and the ∆SUVmax of the PMR group was significantly higher than that of SMD group. The ∆SUVmax of SMD group was also significantly higher than that of PMD groups. Also, ∆SUVmax of the PMD group was significantly lower than all other groups.
In Kim et al. study [29] of 57 patients, two target lesion sets were defined in each patient for analysis: (target A) a single hottest lesion and (target B) a maximum of five hottest lesions (where quantitative PET indexes of all lesions were summed into a single value). Quantitative indexes at initial and end-of-treatment (EOT) PET images were measured, and their percent differences (%Δ) were calculated, which revealed that baseline SUVmax, baseline MTV, and all end-of-therapy PET parameters were significant prognostic factors with both targets A and B, whereas TLG was not. Among them, baseline SUVmax presented the most significant ratio. In our study, we found that ∆MTV of CMR group was significantly higher than ∆MTV of all other groups and the ∆MTV of the PMR group was significantly higher than that of SMD group. The ∆MTV of SMD group was also significantly higher than the PMD groups. Also, ∆MTV of the PMD group was significantly lower than that of all other groups.
On the contrary, we suggested that ΔTLG may play a future role in predicting the patient response as we found that ∆TLG of CMR group was significantly higher than that of all other groups and the ∆TLG of the PMR group was significantly higher than that of SMD group. The ∆TLG of SMD group was also significantly higher than that of PMD groups. Also, ∆TLG of the PMD group was significantly lower than all other groups.
Regarding the post-treatment quantitative parameters, we noticed that post-treatment SUV and post-treatment MTV of the CMR group were significantly lower than those of all other groups. Post-treatment SUV and post-treatment MTV of PMD group were significantly higher than those of all other groups. The post-treatment TLG of the CMR group was significantly lower than all other groups, while post-treatment TLG of the PMR group was significantly lower than SMD and PMD groups.
These results mean that from baseline PET/CT parameters only baseline SUVmax had a significant prognostic value in the evaluation of treatment response. ΔSUVmax, ΔMTV, and ΔTLG% from baseline to post-therapy PET/CT seem to have a role in the prediction of patient prognosis.
There are few limitations of this study. First, the sample size is small with single-center experience due to the high cost of the technique. Second, adequate follow-up of patients was not achieved to correlate our results with the patients’ progression-free survival or overall survival; multicenter study and research group cooperation using a large number of lymphoma patients may be needed to obtain more accurate results.