With the advancement of new lines of malignancy treatment alternatives, different imaging modalities are rising, joined by new procedures and rules to survey tumor status and to foresee reaction to chemotherapy [8]. During the treatment plan, it is imperative to evaluate early tumor reaction, so treatment regimens can be suitably custom-made to get greatest tumor reaction [9].
In the study directed by Soldatos et al. [10] that included 23 patients who inferred that expansion of functional sequences to the conventional MR imaging protocol may build affectability for assurance of treatment reaction in soft tissue sarcomas treated preoperatively with neoadjuvant treatment. A number of preclinical and clinical studies have noted that pre-therapy ADC values may indicate therapy outcomes, with most studies showing that tumors with higher ADC values respond less favorably to treatments [11,12,13].
Contrarily, our study showed that the pre-therapy ADC values in the progressive group showed no difference from those in the non-progressive group.
In support of our results, DeVries et al. [14] highlighted the potential pitfall of using mean tumor ADC values for prognostication in 34 rectal cancer patients undergoing chemoradiation. They showed no differences between mean pretreatment ADC in the 18 patients who responded and the 16 patients who were non-responders. The association between high ADC values and less favorable responses to treatment may not apply to all therapy types [13].
In our study, the ADC values after neoadjuvant treatment in the non-progressive group were significantly higher than those before neoadjuvant treatment (1.63 ± 0.42 vs. 1.35 ± 0.41) with (p < 0.05). However, the ADC values after neoadjuvant treatment in the progressive group were not significantly different from those before neoadjuvant treatment.
That is comparable to the work of Wang et al. [15] who investigated the role of DWI in monitoring the therapeutic response after neoadjuvant chemotherapy in osteosarcoma of long bones in 34 patients; they found that in patients with good response, the post-neoadjuvant chemotherapy values were significantly higher than the pre-neoadjuvant chemotherapy values.
The ADC values after neoadjuvant treatment in our series were negatively related to tumor volumes variations (VOL%) after neoadjuvant treatment, i.e., tumors that increased in size showed lower ADC values than the tumors that decreased in size after neoadjuvant therapy with the Pearson correlation coefficient r = − 0.46 (p < 0.005).
In our series, the ADC values in the non-progressive group were significantly higher than those of the progressive group after neoadjuvant treatment (1.63 ± 0.42 vs. 1.24 ± 0.35) with (p < 0.005). That is comparable to the work of Wang et al. [15] who found that the post-neoadjuvant chemotherapy ADC value in patients with a good response was higher than that of poor response.
In our study, ADC variations (ADC%) in the non-progressive group were significantly higher than those of the progressive group (27.09 ± 48.09 vs. − 3.08 ± 23.5) % with (p < 0.05).
Our results were supported by the work of Baunin et al. [16] on patients diagnosed with osteosarcoma and found that good responders had a significantly higher ADC variation (ADC%) than poor responders (38.3 ± 15.09 vs. 12.02 ± 22.9). However, the ADC differential (ADC2-ADC1) of the tumor was also calculated in these cases.
The comparison of ADC results between different series expressed as absolute ADC values still remain difficult. One way to standardize the results is to use ADC differentials (ADC2-ADC1) or variations (ADC%). ADC variations (ADC%) in percentage terms should be more reproducible and could also be more easily understood by clinicians for comparison to histological analysis [16].
In our series, ADC variations (ADC%) were inversely correlated with morphologic changes, regardless of the effectiveness of anticancer therapy expressed as changes of tumor size based on (RECIST, mRECIST, and three-dimensional volumetric assessment). Linear regression analysis revealed a Pearson correlation coefficient of r = (− 0.424, − 0.478, and − 0.479) respectively with (p < 0.005). This relationship was independent of the neoadjuvant therapy protocol or length of the treatment period, with the shortest imaging interval being 30 days, although treatment regimens and imaging intervals were too heterogeneous for statistical analysis.
This is comparable to the study done by Dudeck et al. [17] in which variations in ADC (ADC%) were inversely correlated with changes of tumor volumes (VOL%) with a Pearson correlation coefficient of r = (− 0.925) and (p < 0.0001). Unlike Dudeck et al.’s study [17], our study revealed that an increase in the ADC value was not always associated with a reduction of tumor volume. Likewise, a decrease in ADC was not always associated with an increase in tumor volume in all patients.
Based on RECIST 1.1, out of the 23 patients who showed increased ADC values after neoadjuvant therapy in our series: In 16/23 (63.5%) of patients, there was decrease in tumor sizes while in 6/23 (26%) of patients, there was increase in tumor sizes and 1/23 of patients showed almost no changes in tumor size.
Based on mRECIST, we found that 4/6 of the patients, who showed increased tumor sizes despite increased ADC values, showed the decreased size of the contrast-enhanced portion of the tumor. The other two patients showed the increased size of the contrast-enhanced portion with increased cystic components of the tumor.
Similarly, out of the (13) patients who showed decreased ADC values, 12/13 (92.3%) of patients showed increase in tumor sizes and only one patient showed decrease in tumor size (according to RECIST 1.1); this one patient still showed decreased size according to mRECIST, and this patient was pathologically proven case of extraskeletal Ewing sarcoma who received concomitant chemo-radiotherapy (CCRTH) in the treatment protocol.
In support to our work, Stacchiotti et al. [18] and Taieb et al. [19] stated that in soft-tissue tumors, the effect of targeted therapies can result in different modifications compared with standard cytotoxic chemotherapy.
In an attempt to standardize magnetic resonance imaging techniques and interpretation after neoadjuvant radiotherapy for routine use and within clinical trials, Wardelmann et al. [20] stated that internal signal/density characteristics should be used in combination to assess response. For example, diminished enhancement and reduction in the size of restricted components/rising ADC on DWI may be interpreted as a response.
Our study showed that, according to RECIST 1.1, the disease control rate (defined as the percentage of CR + PR + SD patients) was 63.8 % (23/36); however, according to mRECIST, the disease control rate was 69.4% (25/36). Evaluation of response to treatment by RECIST1.1 and mRECIST corresponded in 25/36 patients (69.4%) (PR/SD/PD: 4/11/10, respectively). Three patients who were evaluated as a progressive disease by RECIST1.1 were evaluated by mRECIST is a non-progressive disease (two patient’s response changed from PD to PR, one from PD to SD).
Our study had limitations namely the small sample size and heterogeneous group of patients with different sarcoma subtypes.