CT Perfusion of Head and Neck Tumors: How We Do It - AJR

N e u r o r a d i o l o g y / H e a d a n d N e c k I m a g i n g • C l i n i c a l Pe r s p e c t i ve Faggioni et al. CT Perfusion of Head and Neck Tumors

FOCUS ON:

Neuroradiology/Head and Neck Imaging Clinical Perspective

Lorenzo Faggioni1 Emanuele Neri Carlo Bartolozzi Faggioni L, Neri E, Bartolozzi C

CT Perfusion of Head and Neck Tumors: How We Do It OBJECTIVE. Our purpose is to illustrate the pathophysiologic, physical, and technical principles of MDCT perfusion imaging of head and neck tumors. The rationale for data acquisition and the interpretation of perfusion parameters will be discussed in the context of results recently published in the literature. CONCLUSION. MDCT perfusion imaging of primary and recurrent head and neck tumors is feasible and can yield functional information that is useful for tumor grading and assessment of treatment response.

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Keywords: CT, CT perfusion, head and neck cancer DOI:10.2214/AJR.09.3187 Received June 12, 2009; accepted after revision July 23, 2009. 1

All authors: Diagnostic and Interventional Radiology, University of Pisa, Via Paradisa 2, Pisa 56100, Italy. Address correspondence to E. Neri ([email protected]).

AJR 2010; 194:62–69 0361–803X/10/1941–62 © American Roentgen Ray Society

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DCT facilitates the evaluation of functional parameters in oncologic patients, such as tissue perfusion, which can integrate the morphologic information derived from conventional CT techniques. CT perfusion imaging is a dynamic contrast-enhanced technique for quantitative assessment of tissue microcirculation [1]; it was developed almost 30 years ago, primarily for quantification of cerebral blood perfusion in patients with acute stroke [2], and it recently has been rediscovered as a promising noninvasive tool for evaluation of the microcirculatory changes associated with several neoplasms, including hepatocellular carcinoma [3, 4] and cancers of the pancreas [5], lung [6], rectum [7], and head and neck [8–15]. The renewed interest in oncologic applications of CT perfusion imaging has been fueled even further by the recent availability of MDCT scanners with a high number of detector rows (64 and more), which provides greater anatomic coverage without table motion and higher temporal resolution compared with previous CT technology [16, 17]. In particular, CT perfusion imaging of head and neck tumors has been shown to be feasible with 8-row [14, 15, 18] and 16-row [8–10] MDCT equipment, and although, to our knowledge, no reports have been published about the performance of MDCT scanners with more than 16 channels, it is likely that such a technical advancement would enable more extensive and accurate evaluation of primary and recurrent head and neck tumors and of local lymph

node metastases. Other potential advantages of the wider longitudinal coverage afforded by MDCT scanners with more than 16 detector rows over previous-generation MDCT equipment include more extensive data sampling of large lesions (which enables the evaluation of areas with different perfusion patterns, such as viable versus necrotic tissue) and a larger safety margin in case of patient motion in the z-axis. In this article, we illustrate the physical and technical background of CT perfusion analysis and discuss its application to head and neck tumors. The 64-MDCT perfusion acquisition protocol used at our institution will also be described in detail. Definition and Rationale of Contrast Bolus Kinetics CT perfusion analysis is based on continuous recording of x-ray attenuation by a small fast bolus of iodinated contrast medium over a fixed target region. The dynamic acquisition lasts for a time covering the first pass of iodinated contrast medium in the regional vascular bed, during which it has an intravascular distribution [1, 19, 20]. The theoretic principles of dynamic CT for the evaluation of acute ischemic stroke were first illustrated by Axel [2] as early as 1980. Image acquisition was performed sequentially at a single anatomic level after bolus IV administration of an iodinated contrast medium, resulting in registration of time–attenuation curves of the brain tissue. Since then, the technologic evolution of CT scanners has

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CT Perfusion of Head and Neck Tumors led to a progressive improvement in acquisition speed, volumetric coverage, and spatial resolution, but the principle of dynamic imaging of a fixed target region after bolus injection of an iodinated contrast medium has remained unchanged. The key to classic CT perfusion analysis is the fact that the vascular space of the tissue under investigation is assumed to be comparable, from a hemodynamic standpoint, to a single compartment with one input and one output, corresponding to the feeding arteries and draining veins, respectively. The single compartment model is suitable if it can be assumed that interstitial dispersion of iodinated contrast medium is negligible during the first pass [19, 20]. If interstitial extravasation of the iodinated contrast medium is to be considered (such as in oncologic CT perfusion studies, where iodinated contrast medium is expected to leak through highly permeable neovessels), a dual compartment model must be used, provided that data acquisition is prolonged beyond the duration of the first pass of iodinated contrast medium, to encompass at least the initial part of the interstitial passage of iodinated contrast medium [19, 20], as described more thoroughly in the following sections. CT Technique Image Acquisition Protocol In the study of head and neck tumors, acquisition of CT perfusion data is preceded by a standard contrast-enhanced helical scan for morphologic evaluation and oncologic staging. However, if diagnosis of the lesion or related regional lymphadenopathies has already been established by either CT or other imaging techniques, it is possible to obtain a low-dose unenhanced CT scan for selection of the anatomic levels for the subsequent CT perfusion acquisition, thus reducing radiation exposure and iodinated contrast medium dose compared with a preliminary multiphase helical scan. A scheme of the CT perfusion acquisition protocol used at our institution for head and neck tumors is provided in Table 1. CT perfusion data are acquired in the cine mode (i.e., axial acquisition with continuous tube rotation without table motion), with the patient breathing quietly without swallowing, using a beam collimation as wide as possible to maximize anatomic coverage on the z-axis; we use 40 mm at our institution—that is, 0.625-mm detector width × 64 detector rows. In addition, a wide beam collimation


TABLE 1: CT Perfusion Acquisition Protocol for Our 64-MDCT Scannera Parameter Acquisition mode

Value

Notes

Cine

Best temporal resolution

Beam collimation

40 mm (0.625 mm × 64)

Widest z-axis coverage

Tube rotation time

1,000 ms

500-ms effective temporal resolution

Temporal interpolation

180°

Tube voltage

80 kVp

Reduced radiation dose; higher contrast resolution

Tube current

20–100 mA

Angular and z-axis modulation; noise index 20

Sampling FOV

20 cm (head filter)

Reduced x-ray scattering

Slice thickness

2.5 mm

Good spatial resolution and SNR; not too many images

Reconstruction filter

Low frequency (soft)

Reduced image noise

Start of scan

10 s after start of iodinated contrast medium injection

Reduced radiation dose

End of scan

50 s after start of scan

Sampling of first pass and initial interstitial phase of iodinated contrast medium

Note—FOV = field of view, SNR = signal-to-noise ratio. aLightSpeed VCT, GE Healthcare.

can compensate for undesired patient motion between the preliminary CT study and the CT perfusion study, thereby avoiding potential data loss. At our institution, a 1-second tube rotation time and a 180˚ data reconstruction algorithm are chosen, leading to an effective temporal resolution of 500 milliseconds between consecutive frames. The choice of a 1-second rotation time allows us to simplify programming of CT perfusion data acquisition in cine mode on our 64-MDCT scanner (LightSpeed VCT, GE Healthcare); of course, other rotation time values may be set on different scanners. Independent from the CT equipment being used, high temporal resolution is essential for accurate frame-by-frame measurements of contrast enhancement values, which are obtained by reproducing the various phases of the first pass of iodinated contrast medium (with particular reference to peak enhancement) by approximating its continuous distribution over time as closely as possible. A low tube voltage setting can be beneficial for maximizing contrast resolution and reducing both radiation and contrast material dose [18, 21]. At our institution, a tube voltage of 80 kV is used for CT perfusion imaging of head and neck tumors. In this way, contrast resolution is increased by delivering beam energies close to the k-edge of iodine (33.2 keV), a level at which x-ray attenuation occurs almost exclusively by photoelectric effect. Indeed, iodine attenuation and the contrast-to-noise ratio (CNR) at 80 kV are about twice as much as they are at a tube

voltage of 140 kV [21]. In addition, operation at 80 kV enables a substantial radiation exposure reduction of 2.8 times, compared with 120 kV at the same tube current [22]. Tube current must be set at a level as low as possible to minimize radiation exposure. Several investigators [8, 9, 11, 14] have delivered fixed relatively low (? 60–120 mAs) tube current–time product values at 120 kV. However, there is evidence that substantial dose savings with no significant loss in image quality can be obtained using tube current modulation techniques, which also allows more homogeneous distribution of image noise [23]. For these reasons, at our institution, we use both angular and z-axis tube current modulation within a 20–100 mA range, with a noise index of 20 for 2.5-mm slice thickness. Such relatively high image noise is compensated for by the high CNR resulting from 80-kV scanning and the high iodine delivery rate of the iodinated contrast medium [21, 22]; we will discuss this latter point in the next section. The use of a sampling field of view (FOV) as narrow as possible should also aid in reducing the radiation dose and yielding better image quality, owing to reduced x-ray scattering, higher spatial resolution on the transverse plane, and more efficient utilization of x-ray attenuation data over the entire FOV. For CT perfusion imaging of head and neck tumors, we routinely use a head sampling FOV (20-cm diameter). Slice thickness should be chosen as a compromise between radiation dose (because

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Faggioni et al. thinner sections imply a higher radiation dose for a given signal-to-noise ratio) and spatial resolution on the longitudinal axis. In our experience, a slice thickness of 2.5 mm is usually sufficient for the accurate evaluation of suspected head and neck tumors (with particular reference to recurrent head and neck tumors), leading to a reasonable compromise between spatial resolution, image noise, and total image number. The use of a low-frequency (soft) reconstruction kernel is advisable to reduce image noise, except when small lesions with low lesion-to-tissue contrast on the preliminary scan are to be investigated. In the latter case, we prefer to reconstruct the CT perfusion data set a second time with a mediumfrequency (standard) kernel to preserve finer image details.

TABLE 2: Contrast Material Injection Protocol for CT Perfusion of Head and Neck Tumors at Our Institution Parameter

Value

Notes

Iodinated contrast medium

Iodixanol

Isosmolar dimeric iodinated contrast medium

Iodine concentration

320 mg I/mL

Highest concentrated isosmolar dimeric iodinated contrast medium [24]

Volume

40 mL

Compact bolus with steep up-slope, keeping up with intravascular first pass of iodinated contrast medium

Flow rate

5 mL/s

Saline flush

Yes

Same volume and flow rate as iodinated contrast medium for bolus compaction

Contrast Material Injection Protocol The contrast bolus must be as tight as possible to keep up with the fast duration of the first pass of iodinated contrast medium, which is characterized by a rapid up-slope and a contrast enhancement peak, followed by a more gradual decrease resulting from progressive washout of the iodinated contrast medium from arterial input vessels. Moreover, the use of a contrast bolus that is as compact as possible is necessary to achieve the best possible separation among the various phases of contrast kinetics, thus maximally exploiting temporal resolution of the acquisition procedure. At our institution (Table 2), a fixed volume of 40 mL of 320 mg I/mL nonionic isosmolar iodinated contrast medium (iodixanol, 320 mg I/mL [Visipaque 320, GE Healthcare]) is ad-

ministered IV at a flow rate of 5 mL/s, to reach both a steep up-slope and high peak of the time–contrast enhancement curve [24] with good phase separation (Fig. 1). Subsequent administration of 40-mL saline (0.9% NaCl) flush at the same flow rate is recommended to compact the bolus and to minimize its retention in the venous input line. To this aim and to ensure accuracy of the bolus injection, the use of a dual-syringe automatic power injector is mandatory. In theory, an iodine concentration as high as possible would be recommended for better contrast enhancement, which would lead to improved CNR on perfusion images [25]. Silvennoinen et al. [26] and König et al. [27] have addressed this issue for CT perfusion imaging of the brain for ischemic stroke assessment, suggesting that an iodine concentration as high as 400 mgI/mL can provide better sensitivity for the evaluation of low perfusion areas. However, to our knowledge, no dedicated works exist in the literature about the best iodine concentration for body CT perfusion studies, with many authors having used iodine

concentrations between 300 and 350 mg I/mL [3, 11, 15, 18, 28]. For CT perfusion studies of head and neck tumors, Bisdas et al. [8–10] have used highly concentrated iodinated contrast medium (400 mg I/mL), whereas others have used a lower concentration of iodinated contrast medium with equally successful results [12, 15, 18]. A partial explanation for the noncritical nature of iodine concentration alone may be that the high iodine delivery rate and CNR of CT perfusion protocols allow reliable data acquisition along with the use of a moderate concentration iodinated contrast medium [29].

A

B

C

Timing of Contrast-Enhanced CT Perfusion Scanning and Radiation Dose Issues A head and neck tumor–seeking CT perfusion acquisition must include the entire period of the first pass of iodinated contrast medium through tissular microcirculation. For example, the CT perfusion protocol devised by Bisdas et al. [8, 9] starts 6 seconds after IV administration of 40 mL of iodinated contrast medium at 5–6 mL/s flow rate and lasts for 55

Fig. 1—55-year-old woman with previous diagnosis of right vocal cord carcinoma that had been treated with chemoradiation therapy. Patient presented for follow-up imaging 1 year after treatment. A, Preliminary CT scan shows thickening and mild contrast enhancement of right vocal cord (arrow), corresponding to thickening and faint signal alteration on MRI examination performed 2 weeks earlier (not shown). B, Fat-suppressed T2-weighted image shows vocal cord (arrow). C, Diffusion-weighted image (b = 500 s/mm2). (Fig. 1 continues on next page)

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CT Perfusion of Head and Neck Tumors

D

E

F

Fig. 1 (continued)—55-year-old woman with previous diagnosis of right vocal cord carcinoma that had been treated with chemoradiation therapy. Patient presented for follow-up imaging 1 year after treatment. D, Fat-suppressed gadolinium-enhanced T1-weighted image. E, For calculation of perfusion parameters (CT perfusion 3, GE Healthcare), region of interest (green square) is traced on CT perfusion series over nearby right common carotid artery as major feeding vessel. F, Typical shape of time–contrast enhancement curve is shown. First pass of iodinated contrast medium (left part of curve with steep up-slope, high peak enhancement, and quick decay) is followed by recirculation phase. Note very high density of peak enhancement, about 900 HU.

seconds, followed by administration of a 20mL saline flush at the same flow rate. At our institution, scanning starts 10 seconds after the beginning of iodinated contrast medium injection and ends 50 seconds thereafter. A time delay of 10 seconds has been established empirically to avoid unnecessary radiation exposure and collection of useless data before the arrival of iodinated contrast medium in the area under investigation. On the other hand, a 50-second scanning duration ensures data sampling over the entire first pass of iodinated contrast medium plus the initial phase of iodinated contrast medium recirculation, thus allowing measurement of vascular permeability (permeability–surface area product). The radiation dose delivered in the study by Bisdas et al. [9] using a 16-MDCT scanner (scanning parameters: 16 × 1.5 mm collimation, 120 kV, and 100 mAs) amounts to a volume CT dose index of 795 mGy and a dose–length product (DLP) of 1,905 mGy × cm, which corresponds to an equivalent dose of 10.3 mSv. Such a dose is relatively high, although it may be acceptable for patients with head and neck tumors who have received or are candidates for head and neck tumor radiation therapy. However, by using low tube voltages and tube current modulation techniques, it is possible to lower the radiation dose substantially; for instance, at our institution, DLP values between 205 and 554 mGy × cm have been obtained for CT perfusion imaging of head and neck tumors with the acquisition protocol described.


Pitfalls Because data acquisition takes a relatively long time and is performed over a fixed target volume, it is of utmost importance that patients stay as still as possible during scanning. At our institution, the patient is instructed before lying on the CT table and immediately before scanning to breathe quietly without swallowing; this latter point is crucial especially when oropharyngeal or laryngeal masses are being investigated. Bisdas et al. [8, 9] also ask patients to use cushioning and warn them to avoid taking deep breaths when they experience heat resulting from the fast iodinated contrast medium injection; however, in our experience, rapid IV administration of isosmolar iodinated contrast medium has caused no substantial patient motion or discomfort. Motion artifacts also tend to occur during the late phase of the acquisition because of patient intolerance, which carries the risk of spatial or temporal slice misalignment. However, some perfusion software lets the user select a restricted frame set for parameter computation with the possibility of cutting away the last motion-stricken frames of the perfusion data set or, more generally, any other undesired frames. Severe beam-hardening artifacts are often generated by dental prostheses and may corrupt perfusion data, especially when a lowkilovoltage, low-current scanning technique is used. A reasonable approach to minimize artifact impact on image quality is to tilt the CT gantry to keep prostheses out of the FOV

as much as possible [8]. However, if the image quality of substantial portions of the areas under investigation is degraded by artifacts in the preliminary scan, we advise against performing CT perfusion scanning. Computation of Perfusion Parameters CT perfusion data are exported in DICOM format to a workstation equipped with dedicated software for perfusion analysis. The most diffuse implementations of CT perfusion analysis software are based on the maximum slope or the deconvolution algorithm. A detailed description of the mathematic details of these algorithms is beyond the scope of this article. In brief, the maximum slope method is conceptually simpler and does not require tracing an arterial region of interest (ROI), whereas the deconvolution approach, despite being more complex and requiring that one ROI be taken on a feeding arterial vessel, allows absolute quantitative evaluation of perfusion parameters [19, 20, 25]. Although some authors have found a correlation between CT perfusion values obtained by placing an ROI in the internal and the external carotid artery [30], others have detected a mismatch between the same values derived with the arterial ROI being traced over the external carotid artery ipsilateral or contralateral to the tumor, respectively [31]. Because, to our knowledge, no agreement has been reached about the most appropriate location of the arterial ROI, we believe that it is reasonable to draw it on the common or

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Faggioni et al.

A

B

C Fig. 2—55-year-old woman with previous diagnosis of right vocal cord carcinoma that had been treated with chemoradiation therapy. Patient presented for follow-up imaging 1 year after treatment (same patient as described in Fig. 1). A, Regions of interest (ROIs) are taken over target lesion (green circle) and ipsilateral prethyroid muscle as reference (magenta circle). B–E, Perfusion maps of blood flow (BF) (B), blood volume (BV) (C), mean transit time (MTT) (D), and permeability–surface area product (PS) (E) show no altered perfusion values between two ROIs, supporting the diagnosis of postradiotherapy sequelae. Arrows indicate ROI on perfusion CT maps for better image clarity. Ref = reference ROI (prethyroid muscle).

D

E

external carotid artery ipsilateral to the neoplasm as close as possible to the latter, because it is likely to be more representative of the blood input to the neoplasm. Regardless of the kind of algorithm used, it is possible to derive the following quantitative perfusion parameters describing the status of microcirculation on a given user-defined ROI (Fig. 2): • blood flow (BF), which is the blood flow transiting from the arterial input through the tissue; • blood volume (BV), which is the blood volume contained in the tissue during the first pass, or, in other words, the volume of moving blood within the tissue microvasculature; and • mean transit time (MTT), which is the mean time needed for the iodinated contrast medium to pass from the input artery through the tissue microcirculation and which can be calculated as the ratio of BV by BF (central volume theorem) [19, 20]. Finally, by using the deconvolution approach, it is possible to calculate a fourth parameter: the permeability–surface area product, which reflects vascular permeability, or, in pathophysiologic terms, the rate of iodinated contrast medium leakage through the

newly formed microvessel wall [19, 20]. The calculation of the permeability–surface area product can be relevant for the evaluation of cancer neoangiogenesis because tumor vessels are expected to be more leaky than normal ones as a result of their wall being formed by neoendothelium only [20], which allows a fraction of the injected iodinated contrast medium to backflow from the interstitial into the intravascular space. For this reason, the computation of the permeability–surface area product requires prolonging CT perfusion data acquisition beyond the end of the first pass of iodinated contrast medium, to include partial sampling of the interstitial phase of contrast enhancement [8, 16, 25]. It is worth mentioning that CT perfusion parameters obtained with different computational models are not directly interchangeable [32, 33], suggesting that the same model should be used for parameter calculation in comparison studies.

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Pathophysiologic Correlation of CT Perfusion Data Although relatively few works have been produced to date describing the CT perfusion behavior of head and neck tumors, results appear to be very interesting in view of their potential applications as markers for both prog-

nostic and posttreatment evaluation purposes. MTT has been suggested to correlate with the malignant nature of head and neck tumors, with malignant lesions having an MTT faster than 3.5 seconds and nonmalignant ones having an MTT slower than 5.5 seconds [13]. The reduction of MTT in malignant lesions, which has been detected in hypervascular tumors other than head and neck tumors (e.g., hepatocellular [3] and pancreatic endocrine [5] carcinomas), has been attributed to the development of tumoral neoangiogenesis, with increased perfusion pressure and capillary leakiness. Moreover, in a recent article by Ash et al. [18], a statistically significant correlation was found between BF and tumor microvessel density, as determined after mouse antihuman CD31 antibody immuno staining; a correlation (albeit not statistically significant) was also detected between BV and tumor microvessel density. In line with the above results, Gandhi et al. [15] have found a significant reduction in MTT in malignant head and neck tumors, compared with adjacent normal tissues, together with a significant increase in BF, BV, and permeability–surface area product (Figs. 3 and 4). However, Ash et al. [18] did not find any cor relation between immunostaining-determined


CT Perfusion of Head and Neck Tumors

A

B

C

D

E

F

Fig. 3—45-year-old man with laryngeal carcinoma and two subcentimeter laterocervical lymph nodes. A, CT scan shows two subcentimeter laterocervical lymph nodes (circles). B, Regions of interest are placed on laryngeal carcinoma (green circle), on right and left lymph nodes (small magenta circles), and on right sternocleidomastoid muscle (large magenta circle) as reference. C–F, Perfusion maps of blood flow (BF) (C), blood volume (BV) (D), mean transit time (MTT) (E), and permeability–surface area product (PS) (F) show altered perfusion values (i.e., high BF, BV, and permeability–surface area product and reduced MTT) in laryngeal carcinoma (T) and right lymph node (RL) compared with left lymph node (LL) and right sternocleidomastoid muscle (M). Arrows point to ROIs. These findings indicate pathologic right and normal left lymph nodes, as was later confirmed by histopathologic analysis of surgical specimens.

tumor microvessel density and permeability–surface area product, whereas such a correlation was detected in colorectal adenocarcinoma between microvessel density, as determined with CD34 antibody immuno staining, and both permeability–surface area product and BV [28]. Although those results are not directly comparable with each other and because of the little information available, it seems that the interpretation of permeability–surface area product as a general marker of neoangiogenesis currently needs further investigation. Work by Bisdas et al. [8] has confirmed the findings of increased BF and BV in parotid tumors compared with normal tissue; in addition, the BV ratio between neoplastic and healthy parotid tissue has been found to be statistically lower in malignant than in benign lesions, suggesting that the presence of


necrosis in malignant neoplasms may be responsible for a reduction in overall lesion perfusion, although the latter is still higher than in normal parotid tissue. On the other hand, benign parotid tumors showed increased BF and BV values resulting from their highercellularity stromal grade compared with malignant lesions. In any case, MTT in parotid neoplasms is lower than that in normal tissue because of the faster intravascular transit time of iodinated contrast medium in the neoplastic neovasculature and its distorted vessel epithelial wall [8]. Furthermore, the permeability–surface area product was found to be higher in parotid tumors with a high-cellularity stroma grade (such as Warthin tumors) than malignant ones, because the former have many microvessels and hypercellular stromata (in contrast with malignant neoplasms, which have many microve-

ssels but hypocellular stromata); however, this difference was not statistically significant [8]. This apparently heterogeneous scenario reflects the histopathologic differences of several parotid neoplasms, revealing a tight connection between tumor perfusion changes and pathophysiology. There is evidence [14] that squamous cell carcinomas of the upper aerodigestive tract with increased BV or BF are more chemosensitive than are other lesions with relatively decreased perfusion parameters, likely because of their increased oxygenation and metabolism. In particular, Zima et al. [14] have found that elevated values of BV and BF were significantly correlated with an endoscopically determined > 50% reduction of tumor volume after chemotherapy. Gandhi et al. [11] also showed that BV before therapy and a 20% reduction of BV after induction

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B

C Fig. 4—61-year-old man with history of oropharyngeal carcinoma treated with surgery and radiation therapy. A, CT scan shows regions of interest (ROIs) (circles). B–E, ROIs are placed over centimetric contrastenhancing right laterocervical lymph node (RL) and left nuchal lymph node (LL). Perfusion maps of blood flow (BF) (B), blood volume (BV) (C), mean transit time (MTT) (D), and permeability–surface area product (PS) (E) show no substantial differences between two lymph nodes, revealing hyperplastic inflammatory nature of right one.

D

E

chemotherapy are significantly correlated with endoscopic response in advanced squamous cell carcinomas of the upper aerodigestive tract. In addition, Hermans et al. [12] have reported that CT-determined tumor perfusion rate can be an independent predictor of local failure in irradiated head and neck tumors, supporting the hypothesis that less-perfused tumors tend to respond poorly to radiation therapy as a result of their lower oxygen tension. Finally, Bisdas et al. [10] have compared the information provided by whole-tumor perfusion CT parameters and those derived by 18FDG PET–based glucose metabolism measurements, showing that tissue perfusion– metabolic coupling is evident in squamous cell head and neck tumors and may yield additional diagnostic information in patients undergoing PET/CT studies. However, these results conflict with those of Hirasawa et al. [34], who found an inverse relationship between arterial perfusion and glucose uptake of malignant head and neck tumors, suggesting that malignant tumors may depend on anaerobic glycolysis. Such findings indicate that the matter of a relationship between CT perfusion parameters and PET/CT metabolic information needs further investigation.

Application of CT Perfusion Imaging of Head and Neck Tumors: Our Experience To our knowledge, at present there are no studies providing evidence for the clinical validation of MDCT perfusion imaging for routine evaluation of head and neck tumors, in part because of the technique’s relative novelty. At our institution, CT perfusion imaging of head and neck tumors has been performed to date as a research tool in selected patients who gave written informed consent to undergo this additional procedure as a diagnostic complement to a conventional CT examination for cancer staging purposes. Our preliminary analysis of CT perfusion data has confirmed the potential benefits of such technique in head and neck tumor diagnosis, especially for the assessment of disease recurrence after radiation therapy and for characterization of lymph nodes. In fact, in the former case, postirradiation sequelae (e.g., tissular thickening and contrast enhancement due to inflammation or fibrosis) may hide or mimic the presence of subtle focal pathologic abnormalities (Fig. 2), whereas in the latter case, conventional CT may fail to detect metastatic disease, especially if the affected lymph nodes are not enlarged (Fig.

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3). As a part of our institutional research program, we are also investigating the role of CT perfusion imaging in patients with adenocarcinoma of the head and neck territory, including maxillary sinuses, pharynx, tongue, and larynx, to determine variations of CT perfusion parameters. Preliminary data show that BV, BF, and permeability–surface area product are significantly higher, whereas MTT is significantly reduced in head and neck tumor (both primary neoplasms and lymph node metastases, whenever present) compared with normal tissue and with muscle taken as a reference (p < 0.01); moreover, the alteration of CT perfusion parameters correlates with histopathologic diagnosis of adenocarcinoma in all cases (Faggioni L, et al., presented at the 2009 annual meeting of the Radiological Society of North America). Future Directions The current widespread availability of 64MDCT scanners is beneficial for CT perfusion imaging, ensuring a wider z-axis coverage, compared with previous-generation CT equipment, and allowing potentially fewer patient motion-related misregistration artifacts and higher diagnostic sensitivity. Further improvements will likely be brought by


CT Perfusion of Head and Neck Tumors the gradual diffusion of CT scanners with more than 64 detector rows with even wider z-axis coverage (up to 16 cm), enabling whole-organ CT perfusion imaging within a single tube rotation [35, 36]. In conclusion, we expect that the continuous evolution of MDCT scanners will contribute to promote the use of CT as a tool for the functional analysis of head and neck tumors. This field is likely to particularly benefit from such evolution because of its anatomic and pathologic complexity, which often makes accurate diagnosis of malignancy a challenging task. References 1. Miles KA. Tumour angiogenesis and its relation to contrast enhancement on computed tomography: a review. Eur J Radiol 1999; 30:198–205 2. Axel L. Cerebral blood flow determination by rapid-sequence computed tomography: theoretical analysis. Radiology 1980; 137:679–686 3. Sahani DV, Holalkere NS, Mueller PR, Zhu AX. Advanced hepatocellular carcinoma: CT perfusion of liver and tumor tissue—initial experience. Radiology 2007; 243:736–743 4. Zhu AX, Holalkere NS, Muzikansky A, Horgan K, Sahani DV. Early antiangiogenic activity of bevacizumab evaluated by computed tomography perfusion scan in patients with advanced hepatocellular carcinoma. Oncologist 2008; 13:120–125 5. Park MS, Klotz E, Kim MJ, et al. Perfusion CT: noninvasive surrogate marker for stratification of pancreatic cancer response to concurrent chemo- and radiation therapy. Radiology 2009; 250:110–117 6. Li Y, Yang ZG, Chen TW, Chen HJ, Sun JY, Lu YR. Peripheral lung carcinoma: correlation of angiogenesis and first-pass perfusion parameters of 64-detector row CT. Lung Cancer 2008; 61:44–53 7. Bellomi M, Petralia G, Sonzogni A, Zampino MG, Rocca A. CT perfusion for the monitoring of neoadjuvant chemotherapy and radiation therapy in rectal carcinoma: initial experience. Radiology 2007; 244:486–493 8. Bisdas S, Baghi M, Wagenblast J, et al. Differentiation of benign and malignant parotid tumors using deconvolution-based perfusion CT imaging: feasibility of the method and initial results. Eur J Radiol 2007; 64:258–265 9. Bisdas S, Medov L, Baghi M, et al. A comparison of tumour perfusion assessed by deconvolutionbased analysis of dynamic contrast-enhanced CT and MR imaging in patients with squamous cell carcinoma of the upper aerodigestive tract. Eur Radiol 2008; 18:843–850 10. Bisdas S, Spicer K, Rumboldt Z. Whole-tumor perfusion CT parameters and glucose metabolism measurements in head and neck squamous cell


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