In the postoperative or post-radiation phase, tissues at the primary site of a treated malignant tumour exhibit local changes (e.g. oedema, inflammation and fibrosis) that can mimic tumour recurrence or residual tumour tissue on MRI scans through eliciting high signal intensity on T2WIs and post-contrast T1WIs . Noting a suspicious lesion at the site of a treated cancer on post-treatment imaging scans often calls for further evaluation of the said lesion through an invasive approach by acquiring tissue samples for accurate histopathological characterization of the nature of the lesion .
Diffusion-weighted imaging can offer an insight into the cellular composition of scanned tissue through displaying varying degrees of signal attenuation. Since tumour tissues are typically more cellular than tissues with post-treatment benign changes, differences in the degrees of signal attenuation on DWI and in ADC values are expected . In the head and neck region, the use of DWI is becoming increasingly popular nowadays as opposed to the past where motion and magnetic susceptibility artifacts were more pronounced .
In the current study, DW-MRI has proved superior to conventional MRI assessment in terms of diagnostic accuracy, sensitivity and specificity (90%, 88.9% and 91.7% versus 73.3%, 83.3% and 58.3%, respectively). This largely supports the notion that incorporating a DWI protocol in the post-treatment imaging assessment of patients with non-lymphoid head and neck malignancies could have a potentially beneficial role in characterizing the nature of suspicious lesions. The mean ADC value of the lesions was significantly lower in the “locoregional recurrence/residual tumour” group (1.08 × 10−3 mm2/s) compared to the “post-treatment benign changes” group (1.95 × 10−3 mm2/s); P < 0.001. This finding is in consonance with the previously published data which consistently reported that higher ADC values would be expected with post-treatment benign changes while lower ADC values would be expected with recurrent/residual malignant lesions [6,7,8,9, 15].
The lesions were falsely diagnosed by DW-MRI in 3/30 cases in this study (10%). In one of those cases, the diagnosis was false-positive, while in the other two, it was false-negative. In DWI, hypercellular tissue (e.g. malignant tissue) often exhibits high signal intensity on the ADC map with high b values (e.g. b1000) resulting in a low ADC value, owing to the limited extracellular space with subsequent restriction to the motion of water molecules. However, this does not mean that all tissues exhibiting high signal intensity on b1000 images are malignant because signal intensity is influenced both by the motion-probing gradient-induced signal loss and the original T2-weighted signal. Hence, in benign tissue (e.g. fibrous tissue), even in the case of strong signal decay, a hyperintensity at b1000 may remain. This remaining signal at b1000, referred to as the “T2 shine-through” effect, is difficult to differentiate from the hyperintensity observed in malignant tissues with restricted diffusion. Such effect can be minimized by using higher b values, but most often cannot be completely abolished . This could explain the false-positive case in the current study. On the other hand, in recurrent/residual malignant lesions, the relatively high ADC values that may lead to faulty interpretations as “post-treatment benign changes” might be related to the presence of oedema and post-radiation liquefactive necrosis . This could explain the false-negative cases in the study. Moreover, in the three cases that were falsely diagnosed by DW-MRI, the relatively small sizes of the lesions might have partially influenced the visual imaging assessment outcomes.
Looking at the ranges of the ADC measurements in this study, an overlap between the ranges of the two study groups can be clearly noticed. This finding is in consonance with the previously mentioned similar research by Jajodia et al.  where faulty interpretation by DWI, as well as an overlap between the ranges of the ADC measurements, has also been demonstrated. It is hypothesized that this overlap could be due to the inclusion of different anatomical locations as well as different histopathological types of the primary tumours. Similar overlaps were noted in other studies with different tumour sites, as shown in the study conducted by Hein et al. . Possibly, with more data being gathered on specific anatomical locations in the head and neck region, a more defined and accurate range of ADC measurements—possibly also specific for each tumour type—could be obtained. It is also worth pointing out that, besides the varying anatomical locations and the heterogeneity of the malignant tumours included, the variability in the recorded ADC measurements between different studies could also be attributed to the variability in the ROI placement methods, where some authors adopt the freehand tool while others rely on point or region measurement. Modifications to the DWI technique have been suggested by some researchers in order to nullify the equipment-related aspect of measurement variability. Vidiri et al.  have suggested the use of smaller FOV for a more accurate ADC measurement. Meanwhile, Koontz et al.  have devised a tool to bypass the variability in the ADC measurements they have tested, with promising results. Several authors have also investigated the advantages of using high b values (e.g. b2000) in the assessment of post-treatment head and neck lesions [19,20,21,22]. Furthermore, it has been suggested that the overlap between the ranges of the ADC measurements can potentially be patched by integrating the DWI along with positron emission tomography/computed tomography (PET/CT) to help in the assessment process. Alternatively, positron emission tomography/magnetic resonance imaging (PET/MRI) can serve as a replacement to PET/CT in the head and neck region [23,24,25].
In the present study, quantitative assessment using an ADC cutoff value of 1.43 × 10−3 mm2/s has proved to be of similar accuracy as the visual qualitative assessment by DW-MRI (90%), but with higher sensitivity and NPV. This slightly disagrees with the recent series by Jajodia et al.  which reported a slight difference in the diagnostic power between ADC measurement and visual assessment by DW-MRI, in favour of the latter. Yet, this difference might have not been demonstrated in the current study due to the relatively limited number of patients.
Fellow research groups had postulated different ADC cutoff values in order to differentiate recurrent/residual malignant lesions from post-treatment benign changes in the head and neck, with different accuracies. Desouky and colleagues  demonstrated 100% sensitivity and 74% specificity when using an ADC cutoff value of 0.96 × 10−3 mm2/s for differentiating recurrent squamous cell carcinomas from post-treatment changes in the region of the larynx only. Other authors, however, proposed slightly higher ADC cutoff values. For example, Vaid et al.  attained 90.13% sensitivity and 82.5% specificity when using a cutoff value of 1.2 × 10−3 mm2/s to differentiate between a variety of post-treatment lesions at different sites in the head and neck in a heterogeneous group of patients as regards the histopathology of their primary cancers. Similarly, an ADC value of 1.3 × 10−3 mm2/s contributed to the best results when it was used as a cutoff value by Razek et al.  (84% sensitivity/90% specificity) and Jajodia et al.  (94% sensitivity/83.3% specificity).
The current study was not without limitations. Of course, the small sample size was the main drawback. Other limitations included patient heterogeneity, as regards locations of primary tumours, their histopathological types and types of treatment received, and selection bias, where some patients, e.g. thyroid cancer patients, were not included in the sampled population, while others, e.g. laryngeal cancer patients, were included but in small numbers that do not accurately represent their true incidence in the target population. This bias was attributed mainly to the consecutive enrollment of patients into the study.