Diffusion Weighted Image (DWI) has various roles such as tissue characterization, the prediction and monitoring of the response to treatment and differentiation of recurrent tumors from post-therapeutic changes. The malignant tumors have a lower ADC compared to benign lesions. Follow-up of early response to cancer treatment is reflected in an ADC increase in the primary tumor and nodal metastases; whereas nonresponding lesions tend to reveal only a slight increase or even a decrease in ADC during follow-up. However, there are many limitations regarding the performance of DWI in the head and neck region, therefore, many attempts has been performed to overcome the flaws of the diffusion-weighted single-shot-echo planar imaging.

The pharmacokinetic analyses of dynamic contrast enhanced MRI (DCE-MRI) can provide physiological condition of the tissue, and Tofts and Kermode Model has been applied to the head and neck region. Some researchers have used it for the prediction and monitoring of the tumor response to cancer therapy. The general consensus is that the early changes of these parameters during the early phase after the treatment are useful for the interpretation of the response to the treatment. However, the parameters reported in the literature vary considerably; therefore, it is difficult to compare the values of the parameters among research groups.

Both DWI and the pharmacokinetic analysis of the DCE-MRI have shown a wide range of potential benefits in this region, but more comparative studies with established scan techniques and the quantification of the data are required.

Chikui T, Ohga M, Kitamoto E, Shiraishi T, Kawano S, et al. (2014) Quantification of Diffusion and Permeability of MRI in the Head and Neck Region. J Radiol Radiat Ther 2(2): 1047.

•    Diffusion
•    Permeability
•    MRI
•    Head and neck

DWI: Diffusion-Weighted Image; DCE-MRI: Dynamic Contrast-Enhanced MRI; CM: Contrast Mediuwm; TIC; Time-Intensity Curve; WR: Washout Ratio; TK model: Tofts And Kermode Model; SI: Signal Intensity: Signal Intensity; MPG: Motion-Probing Gradient; ADC: Apparent Diffusion Coefficient; EPI: Echo Planar Imaging; SS-EPI: Single-Shot-Echo Planar Imaging; MS-EPI: Multi-Shot-Echo Planar Imaging; HASTE: Half-Fourier SingleShot Turbo Spin-Echo; SPLICE: Split Acquisition of Fast Spin Echo Signals; CRT: Chemoradiotherapy; RT: Radiotherapy; CR: Complete Response; PR: Partial Response, DTI: Diffusion Tensor Imaging; FA: Fractional Anisotropy; BV: Blood Volume; BF: Blood Flow; GRE-EPI: Gradient Echo Type EPI; EES: Extra vascular Extracellular Space; AIF: Arterial Input Function; SPGR: Spoiled Gradient Echo Sequence; UD: Undifferentiated; SCC: Squamous Cell Carcinoma; ML: Malignant Lymphoma; HNSCC: Head and Neck Squamous Cell Carcinoma; PG: Parotid Gland; FA: Flip Angle

In Diffusion-Weighted MRI (DWI), the random microscopic motion of water protons determines the image contrast. Changes in proton self-diffusion are an early indicator of alterations in the cellular homeostasis in acute ischemic stroke; therefore, DWI has become an important tool for the early detection of ischemic stroke [1,2]. This technique is currently being evaluated for various extracranial lesions. Many limitations regarding the performance of extracranial DWI have recently been overcome, and it has various roles such as tissue characterization, the prediction and monitoring of the response to treatment and differentiation of recurrent tumors from post-therapeutic changes, such as fibrosis [3,4].

Dynamic Contrast-Enhanced MRI (DCE-MRI), in which multiphase scans are taken following the intravenous injection of a Contrast Medium (CM), has been widely used in clinical practice. The conventional assessment is the classification of the TimeIntensity Curve (TIC) regarding the time to peak enhancement (T peak) and the Washout Ratio (WR). However, this does not provide information about the underlying pharmacokinetic parameters in the tissue. Conversely, the pharmacokinetic analyses can provide such information, and the most popular Tofts and Kermode Model (TK model) can provide information about the micro vessel permeability and the extracellular space [5-8]. A TK model analysis has been applied for the head and neck region, and some researchers have used it for the prediction and monitoring of the tumor response to cancer therapy.

The aim of this review is to present an overview of the principle, theory and clinical application of DWI and DCE-MRI for the head and neck region.

DWI

The principle of DWI: The most common approach to render MRI sensitive to diffusion is to use a spin echo pulse sequence, in which equal rectangular gradient pulses are played out before and after the 180°-refocusing pulse [9,10]. Without motion, the phase shift due to the two gradients will cancel out. If all spins move coherently (like stationary flow), all will acquire the same phase shift. However, if the spins move at random, the individual spins acquire various phase shifts, which leads to decreased Signal Intensity (SI) (Figure 1).

For simplicity, a Motion-Probing Gradient (MPG) is first applied to one direction belonging on the x-axis. The SI can be expressed as:

 

Where b is the diffusion sensitizing factors, and Dxx is the Apparent Diffusion Coefficient (ADC).

b can be expressed as:

here, γ is the gyromagnetic ratio, G is the strength of the gradient, δ is the duration of the one Motion Probing Gradient (MPG) lobe and Δ is the duration of time between the start of the MPG and that of the next MPG. By using multiple b values (at least two), we can obtain a Dxx value.

The diffusion time (τd )is determined as:

 

The τd is considered to be the spent time for the material to diffuse during a pair of MPGs [9]. Note that as the diffusion time becomes larger in vivo, even if the b value is the same, the Dxx becomes smaller because barriers such as the cell membrane and sub cellular organelles restrict the diffusion of the water proton.

The diffusion coefficient can be calculated from eq. (1) by using multiple b values (at least two). The SI of DWI changes based on the direction of the MPG, and this phenomenon is called anisotropic diffusion [10]. It is well known that both the nerve and muscle fibers show anisotropic diffusion. However, in clinical practice, the isotropic DWI, which excludes the anisotropic aspect, is commonly used for other organs and tissues.

Another method involves the simultaneous application of MPGs with three directions and the combination of the changes in the polarity of the MPGs [12].

Technical limitations of DWI in the maxillofacial region: In clinical practice, diffusion-weighted Single-Shot-Echo Planar Imaging (SS-EPI) is commonly used, in which all data points necessary for the reconstruction of an image are sampled after a 90-180° RF pulse combination at a time [9]. The most critical point that must be kept in mind when performing DWI is to prevent the effects of macroscopic motion, like unwanted body motion, pulsing motion and so on, while retaining the information about the microscopic motion. This is the reason why SS-EPI, which is a type of ultrafast imaging, has been commonly used.

However, DW-SS-EPI has several flaws, which are especially prominent when used in the maxillofacial region [3,4,10]. These mainly consist of the problems derived from SS-EPI itself or those due to the strong Motion Probing-Gradient magnetic fields (MPGs).

EPI has a very small bandwidth per pixel in the phase encoding direction; therefore, EPI is very sensitive to causes of off-resonance, such as local susceptibility variation due to a dental prosthesis and the pneumatic space. The accumulated phase errors may induce image distortion. To compensate for the low bandwidth per pixel, SS-EPI has been combined with parallel imaging techniques. It reduces the amount of k-space data with an array of receiver coils. It increases the intervals of the lines of data acquisition in the k-space; therefore, it results in increased bandwidth in the phase-encoding direction. Moreover, it can shorten the echo time (TE), thereby diminishing the T2*-filtering [10].

Multishot-Echo-Planar Imaging (MS-EPI) is known to provide high resolution DWI with reduced geometric distortions compared to SS-EPI. The data acquisition can be divided into a number of shots with interleaved k-space trajectories, which reduces the image distortion. The navigator echo has been used to monitor the motion-induced phase shifts between each interleaf and to correct them. Moreover, cardiac gating or a pulse trigger can be used to reduce the effect of the pulsation [10-14]. Yamashita applied MS-EPI to the temporal bone, and demonstrated that MS-EPI was associated with higher sensitivity and accuracy than SS-EPI for the detection of cholesteatoma [15].

The steeply ramped gradient fields may generate significant eddy currents during their rapid on/off transition. If the eddy currents have not decayed during image readout, the residual magnetic field will be misread, and this will result in various distortions like scaling, parallel translation and shear deformation. Eddy current-related distortions are exacerbated in EPI due to the low bandwidth in the phase encoding.

Recently, the modification of the gradient pulse sequence by inserting additional gradients of opposite polarity has been applied so that the effects of individual eddy current are counterbalanced. The most widely implemented modification in clinical EPI-DWI is the twice-refocused spin-echo preparation (bipolar) [16]. Kyriazi demonstrated that artifact reduction makes the bipolar DWI sequence preferable for abdominopelvic applications [17]. To the best of our knowledge, there have been no reports of bipolar DWI in the head and neck region; however, this technique will like be used in this area due to its advantages over other techniques.

Despite the improvement of the image quality by using a combination of the EPI and parallel imaging techniques, image degeneration is still sometimes problematic. Hence, other (nonEPI) techniques which are insensitive to artifacts, such as half-Fourier single-shot turbo spin-echo (HASTE), the split acquisition of fast spin-echo signals (SPLICE) and diffusion-weighted line scan imaging, have been applied for the maxillofacial region [18- 21].

Sakamoto evaluated 46 lesions and demonstrated that HASTE DWI is useful for predicting the malignancy of head and neck lesions [19]. Verhappen demonstrated that EPI-DWI has geometric distortions, which resulted in a lower interobserver agreement of ADCs of lesions than HASTE-DWI [18]. On the other hand, they also demonstrated that the lesions were more easily visualized on EPI-DWI compared with HASTE-DWI, due to the lower SNR of the latter sequence [18].

SPLICE is a modified technique using single-shot fast spin echo, which combines diffusion-sensitive stimulated-echo preparation and split-echo acquisition. Sakamoto applied this technique to 67 head and neck lesions, and demonstrated that no cases showed severe image distortion on DWI with SPLICE, and reliable ADC maps were obtained in all cases [20]. Yoshino also demonstrated the utility of SPLICE for evaluating salivary gland lesions [21].

A sophisticated method that combines fast spin-echo and radial scanning has been proposed, and has commonly been known as PROLLELER, or BLADE. In one TR, the data are acquired within a rectangle-shaped blade in parallel lines of the k-space. In the subsequent TRs, the blade is rotated centered at the origin to measure the remaining parts of the k-space. The oversampled data at the center of the k-space are used to correct the inconsistencies between the data from each blade [22,23].

Clinical application of DWI for the maxillofacial region: One of the first successful DWI investigations to be performed in the head and neck region showed the potential for distinguishing solid from cystic lesions, and the general results showed that the mean ADC value of benign solid tumors is higher than that of malign tumors [24,25].

Many researchers have confirmed that ADC is an important tool for the differential diagnosis of salivary gland tumors. Warthin’s tumors include polyclonal lymphocytes with conspicuous follicles and a germinal center, which resulted in low ADC values. On the other hand, pleomorphic adenoma has a rich stromal composition like myxomatous tissue, which results in higher ADC values. A final distinction between Warthin’s tumors and malignant tumors is difficult, owing to the overlapping of the ADC values of the two categories [26-29]. Therefore, Yabuuchi proved the value of combining the results from DWI and DCE-MRI [29].

DWI has been applied for the differential diagnosis of metastatic and reactive nodes [30-35]. The general consensus is that metastatic lymph nodes consistently have a significantly lower ADC compared to benign lymph nodes. The densely packed enlarged cells and increased mitotic figures may act as a barrier to the diffusion of water molecules. On the contrary, Sumi demonstrated that a higher ADC suggested the high possibility of metastasis [33]. The contradictory results may be related to the ratio of the necrotic areas in the regions of interest examined. Zhange et al. demonstrated the importance of the separation of necrotic and solid portions, and the ADC values of these portions are useful in differentiating between the causes of cervical lymphadenopathy [34], Moreover, Park et al. performed high resolution DWI and suggested that the ADC of the lymph node was dependent on whether the hilum was included in the region of interest [35]. Therefore, further studies of the DWI with high spatial resolution will be needed.

Many researchers have discussed both the prediction and monitoring of the tumor response to cancer therapy [36-44]. Hatakenaka evaluated 38 patients with head and neck squamous cell carcinoma (HNSCC) treated by Chemoradiotherapy (CRT) or Radiotherapy (RT) with a radiation dose to the gross tumor volume of more than 60 Gy. They demonstrated that a higher pretreatment ADC value suggested a higher possibility of local recurrence [36]. Onishi evaluated 64 consecutive patients with SCC of the hypopharynx or oropharynx treated with definitive RT, and demonstrated a high ratio of local control in the tumors with lower ADC values [37]. However, either Vandecaveye or King[40-42] could not corroborate these results in the studies. Therefore, the usefulness of the pre-treatment ADC for predicting the response to cancer therapy is controversial.

On the other hand, many researchers have supported that the increase in the ADC during the early phase after the treatment (or during the treatment) is associated with a good response to the treatment [38,41-44]. The tumor ADC increases after initiating treatment because of cellular damage leading to tumor lysis, a loss of cell membrane integrity and apoptosis. Although tissue responses like fibrosis and fat infiltration also modify the ADC, the ADC increase can be observed in response to a range of cancer therapies within one to two months in many cancers. A study of 33 patients with cervical lymph node metastases from SCC showed a significantly higher increase in the mean ADC one week after the start of combined chemo- and radiation therapy in the Complete Response (CR) group compared with that in the partial response (PR) group [41]. Similar results were obtained in a study in which 30 patients treated by CRT for HNSCC underwent MRI exams before and at two and four weeks after starting treatment. The two-year locoregional control rate was significantly higher for the tumors with larger ADC increases between the pre-treatment and early post-treatment measurements [42].

We performed DWI exams with b factors of 0, 500, 1,000 and 1,500 s/mm2 before and after preoperative CRT (n = 37). The histological evaluation of the effects of CRT was performed according to Ohboshi and Shimosato’s classification in the excised specimen after surgery. These criteria grade the tumor response from I (minimal change) to IV (complete disappearance of the tumor cells) [45]. Patients with grades IIb, III and IV responses are considered to be responders, while those with grades IIa and I responses are considered to be non-responders. There was no significant difference between the pre-treatment ADC of the responders [(1.11±0.11) x 10-3mm2 /s] and that of the nonresponders [(1.06±0.07) x 10-3mm2 /s] (P=0.189). However, the post-treatment ADC of the responders [(1.36±0.15)x 10-3mm2 /s] was significantly higher than that of non-responders [(1.21±0.21) x 10-3mm2 /s] (P=0.047) (Figure 2).

As discussed above, DW MRI can have a major impact on both the differential diagnosis and the monitoring of the tumor response to treatment. The choice of timing for follow-up studies is very difficult, because this decision depends on the tumor type and the methods of treatment [43].

The principle of diffusion tensor imaging (DTI), and its applications in the maxillofacial region: Considering the anisotropic nature of the tissue, a diffusion tensor

is required to fully characterize the diffusion. D Could be obtained by using the following equation:

Where G t( ") is the function of the gradient magnetic field. Equation (1) is the simplest special form of equation (6). MPGs in more than six directions are necessary for the estimation of D [11].

Most quantities of D are eigenvalues o (λ1 , λ2 andλ3, λ1 , >λ2 >λ3,) and three eigenvectors. Eigenvalues are the diffusion coefficients along the three intrinsic coordinated directions.

Several scalar parameters to represent the Diffusion Tensor (DT) have been proposed. Fractional anisotropy (FA) is a representative parameter, which shows the anisotropy, and can be determined as follows:

In anisotropic tissues such as nerve fiber [46] and skeletal muscle [47], a 3D tissue fiber structure can be assessed with fiber tractography. The fiber tractographic analysis of DT MRI data is based on the assumption that the primary eigenvector of the DT coincide with the local fiber orientation.

There have been only a few reports of DTI and tractography in the maxillofacial region [48-51]. Hodaie evaluated five trigeminal neuralgia patients treated with Gamma Knife radiosurgery, which they found resulted in a 47% drop in FA values at the target [48]. By using tractography, Taoka described the facial nerve and evaluated the displacement of the facial nerve by a vestibular schwanomma in the cerebellopontine angle [49]. An attempt to depict the inferior alveolar nerve was also reported [50].

In muscle, the first eigenvalue represents the diffusion along the main direction of the muscle fiber, and the second and third eigenvalues represent the diffusion of water within the endomysium and throughout the fiber radius, respectively [52,53]. Shiraishi et al. applied DTI to the masseter muscle and showed that the first eigenvalue (λ1 ) represents diffusion along the main direction of muscle. They also demonstrated that the eigenvalues for the diffusion of the masseter muscle were sensitive to the jaw position. The values of λ2 and λ3 during jaw opening were significantly lower than those at rest, and they considered that the phenomenon reflected a decrease in myofibril size and accompanying shrinkage of the endomysium [54,55].

These results are compatible with the results obtained from the extremities [56-58]. They considered that information provided by the DW and DT images has the potential to aid in the diagnosis of temporomandibular disorder (type I), hyperplasia of the tendon, and aponeuroses of the masticatory muscles.

However, these reports were all preliminary research studies. Therefore, the usefulness of DTI in the maxillofacial region will need to be evaluated in the future.

Dynamic contrast-enhanced MRI (DCE-MRI)

The theory of the quantification of DCE-MRI: Fundamentally, dynamic MR scans can be grouped into two categories; T1 -weighted DCE-MRI and T2 *-weighted DCE-MRI. The presence of CM within the vessel causes dephasing and shortens the T2 * value. T2 *-weighted sequences are therefore used to monitor the passage of the CM, because there is a transient darkening of the tissue during the first passage of the CM. Generally, the quantification is performed based on the assumption that the CM is confined in the capillary bed, which provides valuable information about perfusion, such as the blood volume (BV), blood flow (BF) and transit time. Such imaging requires fast acquisition (i.e., sub second and a few seconds); therefore, the gradient echo type EPI (GRE-EPI) has been widely used to allow for greater anatomical coverage. In the normal brain, the CM is confined to the vessels due to the brain-blood barrier, so the change of the T1 relaxation time surrounding the vessel is extremely small. However, the susceptibility effect (the shortening of the T2* relaxation time) covers a much wider range. This is one reason why T2*-weighted DCE-MRI is commonly used to evaluate the perfusion of the brain [59]. However, GRE-EPI has limited applications in extracranial tissues owing to the great intrinsic sensitivity of its susceptibility. The image quality is especially poor in the head and neck region because of the pneumatic space and the presence of oral prostheses.

On the other hand, the basic principal of T1 -weighted DCEMRI is the shortening of the T1 value, which results in an increase of the SI. The shortening effect of the T1 relaxation time occurs when the paramagnetic ion approaches within 5 of a water proton. In most tissues, except the normal brain, the CM leaks into the extravascular Extracellular Space (EES), and this causes the shortening of the T1 relaxation time. Hence, T1 -weighted DCE-MRI could be applied to almost all tissues, including the maxillofatiocal region.

A simple evaluation of T1 -weighted DCE-MRI is the subjective assessment of the pattern of the TIC or the simple quantification of the TIC, like the time to peak enhancement (Tpeak) and the Washout Ratio (WR). Although the semiquantitative evaluations described above have been widely applied in the maxillofacial region[60-64], they do not provide information on the underlying pharmacokinetic nature of the tissue. A pharmacokinetic analysis can show the underlying physiological characteristics of the lesion. We will now introduce the methods used for the pharmacokinetic analysis, and also describe the clinical application of this technique.

Although various kinds of compartment models [7,65] have been suggested for the quantification of T1 -weighted DCE MRI, the TK model [5,6,66] has been the most widely applied for various tissues. The TK model assumes the equilibrium of contrast media between the plasma and the extravascular-extracellular space (EES), and the isodirectional permeability. Therefore, the equilibrium is described by:

Where t is the time, Ct is the CM in the tissue, Cp is the concentration of CM in plasma, Ktrans is the influx forward volume transfer constant (into the EES from the plasma) and ve is the fractional volume of the EES per unit volume of tissue (Figure 3).

In this model, the concentration of the CM is derived from the EES and plasma:

Where ve is the fractional volume of plasma per unit volume of tissue.

If the plasma component is negligible, the second term in the right part of the equation is eliminated. Substituting Ct (t) and Cp (t) into the equation allows the variables (Ktrans, ve , and vp ) to be estimated.

Although T1 -weighted DCE-MRI researchers have employed T1 -weighted gradient-echo, saturation recovery/inversion recovery snapshot sequences (e.g., turbo FLASH) [67] and EPI sequences, most studies have used the T1 -weighted gradient-echo (3D-transverse spoiled gradient echo sequence (SPGR)) in the maxillofacial region.

There are two steps required to estimate the concentration of CM. The first step is to obtain the pre-contrast T1 map (T10 map). The relationship between the MR signal (SI) of a gradient echo and the relaxation time can be expressed as follows:

 

Where r is the proton density, α is the flip angle, TR is the repetition time, TE is the echo time and T1 is the tissue T1 value. By varying either the flip angle or the TR before the administration of CM, the T10 map can be obtained.

The second step is to obtain the T1 map after the injection of CM using both the SI ratio (SI/SIpre) and the T10 map. If the change in T2 * was assumed to be negligible due to full T1 weighting, the SI ratio can be expressed as follows:

The change of the relaxation rate (1/T1 ) is parallel to the concentration of CM:

 

Where R1 is a relaxation rate determined for each CM, and C is the concentration of CM during the dynamic sequence. These values substitute into the equation, and the variables (Ktrans, ve , and vp ) to be estimated.

The TK model analysis has several drawbacks based on the theory. The Ktrans is determined by:

 

Where F is the blood flow, ρ is the specific gravity, Hct is the hematocrit and PS is the permeability-surface area product. Therefore, it is impossible to discriminate the effect of BF and that of permeability [68]. In addition, the premised instant mixing of CM between two compartments (EES and plasma) does not occur [7].

From the technical aspects, the applied Arterial Input Function (AIF) and the methods used for the T1 measurements have a strong impact on these parameters. Although the estimation of the individual AIF is preferable [69], determining the AIF in the neck is challenging due to saturation due to the high concentration of CM and the inflow phenomenon due to the high velocity in the carotid artery. Recently, several attempted improvements of the scan method insensitive to flow (like turbo Flash) [67] and the utilization of phase images (phase AIF) [70- 72] have been made. However, many researchers have used the model AIF based on the previous reports [73,74]. Figure 4 shows a comparison of the population-based AIF derived from the work by Weinmann (drip infusion), Parkers (injection rate: 3 ml/s, temporal resolution of DCE-MRI: 4.97s) and our group (2 ml/s, 3.5s). We used the phase images to obtain the Ca (t).

If the T1 map was obtained by the SPGR method, the selection of the flip angles can lead to large differences in the T1 value and the kinetic parameter estimation [75,76] Especially for 3T MRI, the inhomogeneity of the local magnetic field (B1 ) has to be corrected, because the actual FA is quite different from the nominated FA [77,78]. Further research will be needed to perform a pharmacokinetic analysis.

Clinical application of the TK model analysis in the maxillofacial region: Lee et al. applied a pharmacokinetic analysis for 63 patients with 26 undifferentiated (UD) carcinomas, 28 squamous cell carcinoma (SCC) and eight malignant lymphomas (ML). They showed significant differences between UD/SCC and UD/lymphoma and suggested that their Ktrans results appear to correlate with the expression of vascular endothelial growth factor. The ve of the lymphoma was the smallest among the three types of tumors; however, the differences were not significant [79]. In our study, in which we evaluated 59 lesions, malignant lymphoma had the lowest ve ,and there were significant differences between malignant lymphoma and the other two malignant tumor types (SCC and malignant salivary gland tumor). Van Cann evaluated the mandibular invasion of SCC adjacent or fixed to the mandible (n=33), and demonstrated that SCC with medullary invasion showed a higher mean Ktrans compared with SCC without invasion (p < 0.001) [80].

The pharmacokinetic analyses have been widely applied for the pre-treatment prediction of the therapeutic efficacy and for monitoring the tumor response to cancer therapies [81-88].

Several studies demonstrated that CRT is more effective against tumors with a higher pre-treatment Ktrans than those with a lower Ktrans, and suggested that the elevated BF and permeable vasculature had higher oxygenation levels, thus resulting in better access to the chemotherapeutic drug and better radio sensitivity. Kim et al. enrolled 33 HNSCC patients treated with neoadjuvant CRT. The treatment included accelerated RT with 220 cGy per fraction for a total dose of 70.4Gy. They demonstrated that the average pre-treatment Ktrans of the CR group was significantly higher than that of the PR group [84]. Chawla et al. evaluated thirty-two patients with HNSCC who were treated by CRT; the radiation therapy regimen included a total dose of 70.4 Gy given in 32 fractions. They observed a higher Ktrans value in responders compared with nonresponders; however, the difference was not significant [39]. Shukla-Dave et al. demonstrated that an increased pre-treatment skewness Ktrans was associated with a poor overall survival and progression-free survival (n=74) [83].

Some HNSCC studies found that a large reduction of the permeability (Ktrans ) was linked to a better response to CRT [81,85]. However, with regard to the early changes in parameters, other studies demonstrated conflicting results, where an increase of permeability (Ktrans) or the BV after CRT suggested a favorable outcome [82,86,87]. Cao et al. performed a quantification of the BV and BF based on DCE-MRI taken before treatment and two weeks after the initiation of CRT (n = 14). They also evaluated the local and regional control, and concluded that an increase of the BV and BF suggested a good outcome [82].

We performed DCE-MRI on patients with oral SCC before and after preoperative CRT (n = 29). The histological evaluation of the effects of CRT was performed according to Ohboshi and Shimosato’s classification. The change in the Ktrans of the responders was significantly larger than that of the non-responders (P = 0. 018) [86]. We considered that an increase in the available primary tumor blood supply for oxygen extraction during RT was associated with an increased tumor response. RT causes a significant increase in the EES, and moreover, the degree of tumor response is correlated with the increase in the EES (Figure 5) [86].

Outside of tumors, a TK model analysis has been applied to evaluate the function of the parotid gland (PG) [89-91]. We evaluated whether age had an effect on the parameters (Ktrans, ve , vp and the volume of PGs) in 72 PGs. We found that age significantly and negatively correlated with the Ktrans (P<0.0001; ρ= –0.513) and vp (P=0.0031; ρ= –0.499), but not with either the ve (P=0.341) or the volume of the PG (P=0.104) (Figure 6). It seems natural that the decrease in both the permeability of the vessels and the BF associated with aging resulted in a decrease in the Ktrans. On the other hand, the age did not correlate with either the ve or volume of the PGs. Many previous reports have demonstrated that the CT value decreased with age because of the deposition of fat. We considered that, in spite of the loss of the acinar cells with age, the deposition of fat prevented an increase in the ve .

Roberts compared the microvascular characteristics of the parotid glands in patients with Sjögren syndrome with those in healthy volunteers. The distribution of the Ktrans, and the ve parameter values, were significantly different (P< 0.001) between the two subject groups, with group median parameters found to be elevated in the Sjögren syndrome group [89].

Houweling investigated radiation-induced changes in the salivary glands of patients with oropharynx cancer treated by primary RT (n=18). They showed a significant increase in the ve and a decrease in the kep. The Ktrans increased; however, the difference did not reach significance [90,91].

We evaluated thirty-six patients with oral cancer before and after preoperative CRT. In spite of the very low radiation dose administered in the PGs, both the ΔKtrans and Δve linearly correlated with the mean dose. We concluded that CRT caused a loss of the acinar cells, which then resulted in an increase in the percentage of the EES. The low radiation dose administered in this study may have caused an early vascular response, which typically involves a phase of vasodilatation and an increase in blood supply.

The early reports of DWI generally showed that the most malignant tumors have a lower ADC compared to benign lesions. A large increase in the ADC during treatment or in the early post-treatment period was suggestive of a good response to the treatment, and a small increase or decrease was suggestive of treatment failure. Care should be taken when translating these published data into clinical practice, because various artifacts are associated with DW-SS-EPI.

The TK model analysis has the potential to predict and monitoring the tumor response to treatment. It also has potential for evaluating the function of the salivary gland. However, the parameters reported in the literature vary considerably; therefore, it is difficult to compare the values of the parameters among research groups. The establishment of a method for the accurate AIF measurement and accurate T1 mapping, and a standardized pharmacokinetic model are needed for the wider application of this technique in clinical practice.

Both DWI and the pharmacokinetic analysis of the DCE-MRI have shown a wide range of potential benefits in the head and neck region, but more comparative studies with established scan techniques and the quantification of the data are required.

This work was supported by an MEXT (Ministry of Education, Culture, Sports, Science and Technology) Grant-in-Aid for Scientific Research (C) 2 4 5 9 2 8 3 4.

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