Impact of the Definition of Peak Standardized Uptake Value on Quantification of Treatment Response

Abstract

PET-based treatment response assessment typically measures the change in maximum standardized uptake value (SUV_max), which is adversely affected by noise. Peak SUV (SUV_peak) has been recommended as a more robust alternative, but its associated region of interest (ROI_peak) is not uniquely defined. We investigated the impact of different ROI_peak definitions on quantification of SUV_peak and tumor response.

Methods

Seventeen patients with solid malignancies were treated with a multitargeted receptor tyrosine kinase inhibitor resulting in a variety of responses. Using the cellular proliferation marker 3′-deoxy-3′-¹⁸F-fluorothymidine (¹⁸F-FLT), whole-body PET/CT scans were acquired at baseline and during treatment. ¹⁸F-FLT–avid lesions (~2/patient) were segmented on PET images, and tumor response was assessed via the relative change in SUV_peak. For each tumor, 24 different SUV_peaks were determined by changing ROI_peak shape (circles vs. spheres), size (7.5–20 mm), and location (centered on SUV_max vs. placed in highest-uptake region), encompassing different definitions from the literature. Within each tumor, variations in the 24 SUV_peaks and tumor responses were measured using coefficient of variation (CV), standardized deviation (SD), and range. For each ROI_peak definition, a population average SUV_peak and tumor response were determined over all tumors.

Results

A substantial variation in both SUV_peak and tumor response resulted from changing the ROI_peak definition. The variable ROI_peak definition led to an intratumor SUV_peak variation ranging from 49% above to 46% below the mean (CV, 17%) and an intratumor SUV_peak response variation ranging from 49% above to 35% below the mean (SD, 9%). The variable ROI_peak definition led to a population average SUV_peak variation ranging from 24% above to 28% below the mean (CV, 14%) and a population average SUV_peak response variation ranging from only 3% above to 3% below the mean (SD, 2%). The size of ROI_peak caused more variation in intratumor response than did the location or shape of ROI_peak. Population average tumor response was independent of size, shape, and location of ROI_peak.

Conclusion

Quantification of individual tumor response using SUV_peak is highly sensitive to the ROI_peak definition, which can significantly affect the use of SUV_peak for assessment of treatment response. Clinical trials are necessary to compare the efficacy of SUV_peak and SUV_max for quantification of response to therapy.

PET continues to gain importance as a tool to assess response to therapy. Typically, the change in standardized uptake value (SUV) is measured to quantify treatment response (1). Patients are then classified into different response categories based on the relative change in SUV. These categories include complete response, partial response, stable disease, and progressive disease. Such response classifications are often used to guide subsequent treatment decisions and can be predictive of clinical out-come (2-4).

Most response assessment studies measure the change in maximum SUV (SUV_max), a single-pixel value that is adversely affected by noise (5-8), which leads to uncertainty in the quantification of treatment response. Consequently, peak SUV (SUV_peak) has been suggested as a more robust alternative (9), defined as the average SUV within a small, fixed-size region of interest (ROI_peak) centered on a high-uptake part of the tumor (9). SUV_peak is illustrated in Figure 1. Because of its larger volume, SUV_peak is less affected by image noise than SUV_max (6,7,10) and therefore is expected to reduce uncertainties in the quantification of response to therapy.

FIGURE 1.

Multiple definitions of ROI_peak. In this schematic PET image of radiotracer uptake in tumor (purple outline), ROI_peaks of different sizes and in different locations are shown. Shape of ROI_peak can vary too (only circles are shown).

There is a wide variety of SUV_peak definitions in the literature, and they differ in the shape, size, and location of the ROI_peak (Fig. 1). Shapes and sizes include square and cuboidal regions with side lengths ranging from 7 to 15 mm (5,8,11-13), as well as circular, cylindric, and spheric regions with diameters ranging from 9 to 17 mm (6,7,9,14-16). Locations include the tumor region with the highest radiotracer uptake, the tumor region yielding the greatest SUV_peak, and the tumor region containing the voxel of maximum uptake.

The definition of SUV_peak could significantly affect the quantification of treatment response. Altering the size, shape, or location of ROI_peak may affect the relative change in SUV_peak and ultimately the classification of response. Uncertainties in the quantification of response could have significant implications regarding treatment decisions and clinical prognoses. Furthermore, these uncertainties could influence the recommendation to use SUV_peak rather than SUV_max for response assessment. Consequently, we investigated the impact of different ROI_peak definitions on the quantification of SUV_peak and tumor response to therapy.

MATERIALS AND METHODS

Treatment and Imaging

Seventeen patients with advanced solid malignancies were treated with a multitargeted receptor tyrosine kinase inhibitor with antiproliferative and antiangiogenic effects. Malignancies included a diverse range of tumor types: renal cell carcinoma (n = 7), esophagus (n = 2), hepatocellular (n = 2), prostate (n = 1), sarcoma (n = 1), small cell lung (n = 2), thymus (n = 1), and uterine carcinosarcoma (n = 1). Response to therapy was measured using the PET radiotracer 3′-deoxy-3′-¹⁸F-fluorothymidine (¹⁸F-FLT). As a surrogate of cellular proliferation, ¹⁸F-FLT is emerging as a promising candidate for chemotherapy response assessment as demonstrated in patients with lymphoma, breast cancer, and glioma (17-23). Patients were injected intravenously with 240 MBq (6.5 mCi) of ¹⁸F-FLT and underwent whole-body PET/CT at baseline (pretreatment) and during treatment using a Discovery LS PET/CT scanner (GE Healthcare). ¹⁸F-FLT was synthesized following the method described by Martin et al. with slight modifications (24). PET/CT began 47 ± 4 min after injection and extended inferiorly from the base of the skull to the distal femora. Acquisition time was 10 min per bed position. PET images were reconstructed on a 128 × 128 grid over a 50-cm field of view using the ordered-subset expectation maximization algorithm with 2 iterations, 28 subsets, a 5-mm gaussian loop (interiteration) filter, a 3-mm gaussian postprocessing filter, and CT attenuation correction. On average, patient weight changed only 1.5% between the 2 PET scans.

The study protocol was approved by the University of Wisconsin Health Sciences Institutional Review Board, the Scientific Review Board of the University of Wisconsin Carbone Comprehensive Cancer Center, and the University of Wisconsin Radiation Drug Research Committee. Written informed consent was obtained from each patient before enrollment in the study.

Quantification of SUV_peak and Tumor Response

PET activity concentrations (MBq/cm³) were converted to standardized uptake values by dividing by the injected activity per patient mass. ¹⁸F-FLT-avid lesions (~2/patient) were segmented on PET images by an experienced nuclear medicine physician. The location and number of lesions were as follows: lung, 14; mediastinum, 5; liver, 4; abdomen, 3; adrenal, 2; gastrointestinal tract, 2; pelvis, 1; gluteus, 1; uterus, 1; arm, 1; bone, 1. Tumor volumes ranged from 1 cm³ to 530 cm³, with an average of 66 cm³.

For each tumor, 24 different SUV_peaks were determined by changing the region of interest (ROI_peak) used to measure SUV_peak (Fig. 2). The shape, size, and location of ROI_peak were varied as follows: for shape, circular (2-dimensional) or spheric (3-dimensional) ROIs were used; for size, ROI diameters of 7.5, 10, 12.5, 15, 17.5, or 20 mm, encompassing the range of fixed ROI lengths in the literature, were used; for location, the ROI was centered on SUV_max or was placed in the highest-uptake region. An example ROI is shown in Supplemental Figure 1, where a 12.5-mm-diameter circular ROI was placed in the highest-uptake region of a lung lesion (supplemental materials are available online only at http://jnm.snmjournals.org).

FIGURE 2.

Varying ROI_peak. Shape, location, and size of ROI_peak were varied as shown to yield 24 different SUV_peaks for each tumor.

SUV_peak was determined automatically. First, an ROI (circular or spheric) was centered on each tumor voxel and the average SUV within the ROI was determined by weighting each voxel uptake value by the percentage of its volume contained within the ROI. The ROI location yielding the greatest average SUV was defined as the highest-uptake region of the tumor (Supplemental Fig. 1). In addition, an ROI (circular or spheric) was centered on SUV_max and the average SUV within the ROI was determined.

For each tumor, the 24 SUV_peaks were normalized to the mean intratumor SUV_peak (Eq. 1) and their variation was measured using the coefficient of variation (CV) and range.

$$\overline{{\text{SUV}}_{\text{peak}}^n}=\frac{\sum _{i=1}^{i=24}{\left({\text{SUV}}_{\text{peak}}^n\right)}_i}{24}$$ Eq. 1

Here, $\overline{{\text{SUV}}_{\text{peak}}^n}$ is the mean intratumor SUV_peak for an individual tumor n, and ${\left({\text{SUV}}_{\text{peak}}^n\right)}_i$ corresponds to an SUV_peak determined using 1 of the 24 ROI_peak definitions (the ith definition, e.g., 12.5-mm-diameter spheric ROI placed in the highest-uptake region).

For each ROI_peak definition, a population average SUV_peak (Eq. 2) was determined over all tumors.

$$\overline{{\left({\text{SUV}}_{\text{peak}}\right)}_i}=\frac{\sum _{n=1}^N{\left({\text{SUV}}_{\text{peak}}^n\right)}_i}{N}.$$ Eq. 2

Here, $\overline{{\left({\text{SUV}}_{\text{peak}}\right)}_i}$ SUV_peak is the population average SUV_peak using the ith ROI_peak definition, n is an individual tumor, N is the total number of tumors, and ${\left({\text{SUV}}_{\text{peak}}^n\right)}_i$ corresponds to an SUV_peak of an individual tumor determined using 1 of the 24 ROI_peak definitions (the ith definition). The variation of the 24 population average SUV_peak was measured using coefficient of variation and range.

Tumor response (R) during treatment was defined as the relative change in SUV_peak normalized to the baseline SUV_peak (Eq. 3).

$$R_i^n=\frac{{\left({\text{SUV}}_{\text{peak}}^{n,\text{during}\text{tx}}\right)}_i-{\left({\text{SUV}}_{\text{peak}}^{n,\text{baseline}}\right)}_i}{{\left({\text{SUV}}_{\text{peak}}^{n,\text{baseline}}\right)}_i}\times 100\%.$$ Eq. 3

Here, $R_i^n$ is the response of an individual tumor (n) using 1 of the 24 ROI_peak definition (the ith definition).

For each tumor, the 24 different SUV_peaks gave rise to 24 different responses whose variation was measured using the standardized deviation (SD) and range. For each ROI_peak definition, a population average response (Eq. 4) was determined over all tumors.

$$\overline{R_i}=\frac{\sum _{n=1}^N{R}_i^n}{N}.$$ Eq. 4

Here, $\overline{R_i}$ is the population average response using the ith ROI_peak definition, n is an individual tumor, and N is the total number of tumors. The variation of the 24 population average responses was measured using SD and range.

Tumor response was also determined using SUV_max for comparison with response measured using SUV_peak. SUV_max can be considered as a special case of SUV_peak in the limit of a very small ROI_peak (single-voxel ROI_peak). For SUV_max, an equivalent diameter of 5 mm was derived by calculating the diameter of a sphere whose volume equaled the volume of the single voxel (65 mm³) represented by SUV_max.

One-way ANOVA was used to test whether the ROI_peak definition resulted in statistically significant differences in SUV_peak and tumor response. The Levene test for equal variance was used, and means were compared with the Bonferroni test. Differences were considered statistically significant at an a-level of less than 0.05/24. Correlations between the variation in SUV_peak and tumor response and other tumor characteristics were tested using the Pearson correlation coefficient (r) and considered statistically significant at an a-level of less than 0.05.

RESULTS

Individual Tumors

SUV_peak

Within individual tumors, considerable variation in SUV_peak resulted from changing the ROI_peak definition. The variable ROI_peak definition led to an intratumor SUV_peak variation ranging from 49% above to 46% below the mean, resulting in a 17% CV. These intratumor variations in SUV_peak are highlighted for a retroperitoneal lesion in Supplemental Figure 2 and for all lesions in Supplemental Figure 3.

The size of ROI_peak caused more variation in intratumor SUV_peak than did the location or shape of ROI_peak (Supplemental Fig. 3). Within individual tumors, varying ROI_peak diameter resulted on average in a 14% CV associated with SUV_peak, compared with a CV of 9% and 5% when the location or shape, respectively, of ROI_peak was varied. In general, intratumor SUV_peak tended to decrease, but its variation tended to increase as the size of ROI_peak increased (Supplemental Fig. 2).

There was no significant correlation between tumor size and the variation in intratumor SUV_peak (Supplemental Fig. 3, tumors ordered by size). Furthermore, there was no significant correlation between intratumor uptake heterogeneity (measured by CV of tumor uptake) and the variation in intratumor SUV_peak.

Tumor Response

Within individual tumors, a substantial variation in tumor response resulted from changing the ROI_peak definition. Intratumor response ranged from 49% above to 35% below the mean, resulting in a 9% SD. These intratumor variations in response are highlighted for a retroperitoneal lesion in Figure 3 and for all lesions in Figure 4. Responses determined using SUV_max were within the range of responses quantified with SUV_peak in almost 70% of all tumors (Fig. 4).

FIGURE 3.

Variation in tumor response for retroperitoneal lesion (lesion 11). (Left) 24 different SUV_peak tumor responses (mean response, dashed line) arising from 24 different ROI_peak definitions. Response was ambiguously classified as either stable disease (above −30%, green line) or partial response (below −30%). SUV_max response is also shown. (Right) Box represents SD, whiskers show range, and solid line depicts median of SUV_peak response.

FIGURE 4.

Intratumor variation in SUV_peak responses. (Left) Responses of 31 tumors (ordered from smallest to largest) arising from different ROI_peak definitions. Responses of 12 tumors (in blue) were ambiguously classified as either progressive disease/stable disease (130%, solid red line) or stable disease/partial response (-30%, solid green line). SUV_max response and SUV_peak PERCIST response (1.25-cm-diameter sphere in highest-uptake region) are also shown. (Right) Overall variation in intratumor response and variation associated with changing size, location, and shape of ROI_peak. Boxes represent SD, whiskers show range, and solid line depicts median of response values.

Variation in intratumor response resulted in the ambiguous classification of individual tumors into multiple response categories (Table 1; Figs. 3 and 4). Different response thresholds were applied to classify tumors into response categories (e.g., +30% and −30% for progressive disease/stable disease and stable disease/partial response thresholds, respectively, as recommended by PET Response Criteria in Solid Tumors [PERCIST]). When response thresholds of ±20%, ±30%, and ±40% were applied, 55%, 42%, and 32%, respectively, of all tumors suffered from an ambiguous response classification. In addition, response classifications using SUV_peak and SUV_max were compared (Table 1; Figs. 3 and 4).

TABLE 1.

Tumor Response Classification Using Different Response Thresholds

Response thresholds	Response metric	Total tumors	Partial-response tumors	Stable-disease tumors	Progressive- disease tumors	Partial- response/ stable-disease tumors	Stable-disease/ progressive- disease tumors	Partial-response/ stable-disease/ progressive-disease tumors	Ambiguous response (%)
±20%	SUVpeak	31	12	1	1	10	6	1	55
	SUVmax	31	18	9	4	NA	NA	NA	NA
±30%	SUVpeak	31	9	8	1	9	4	0	42
	SUVmax	31	13	15	3	NA	NA	NA	NA
±40%	SUVpeak	31	7	14	0	7	3	0	32
	SUVmax	31	9	20	2	NA	NA	NA	NA

NA = not applicable.

The size, location, and shape of ROI_peak all caused similar variations in intratumor response (Fig. 4). Within individual tumors, varying ROI_peak size, location, and shape resulted on average in respective SDs of 5%, 7%, and 5% associated with tumor response.

In general, the magnitude of intratumor response was independent of the size of ROI_peak. However, the variation in intratumor response tended to increase as the size of ROI_peak increased (Fig. 3). The magnitude and variation of intratumor response were independent of ROI_peak shape and location.

A strong correlation was exhibited between tumor response (average of all 24 SUV_peak responses for each tumor) and variation in intratumor response (r = 0.81, P < 0.001, Figs. 4-6). Variation in intratumor response tended to increase as response increased (i.e., as response worsened from partial response to stable disease to progressive disease). There was no significant correlation between tumor size and variation in intratumor response (Fig. 4, tumors ordered by size). Furthermore, there was no significant correlation between intratumor uptake heterogeneity (measured by CV of tumor uptake) and variation in intratumor response.

FIGURE 6.

Small vs. large variation in intratumor SUV_peak response. ¹⁸F-FLT PET/CT images of periaortic lesion (left, lesion 24) and pelvic tumor (right, lesion 30) at baseline (top) and during treatment (bottom). Lesions are indicated by white circles. Periaortic lesion responded well, exhibiting fairly uniform reduction of ¹⁸F-FLT uptake in higher-uptake regions. Consequently, there was little variation in SUV_peak response. In contrast, pelvic tumor responded poorly, with heterogeneous response in higher-uptake regions, resulting in large variation in SUV_peak response.

Population Average

SUV_peak

Quantification of the population average SUV_peak was substantially affected by changing the ROI_peak definition. For different ROI_peak definitions, the population average SUV_peak ranged from 24% above to 28% below the mean, resulting in a 14% CV (Supplemental Fig. 4). Differences in SUV_peak (associated with the ROI_peak definitions) between the populations were statistically significant (P < 0.001).

The size of ROI_peak caused more variation in the population average SUV_peak than did the location or shape of ROI_peak (Supplemental Fig. 4). Varying ROI_peak diameter resulted in a 13% CV associated with the population average SUV_peak, compared with a CV of 7% and 4%, respectively, when ROI_peak location or shape was varied. Trends observed in the population average SUV_peak reflected trends associated with intratumor SUV_peak. As the size of ROI_peak increased, the population average SUV_peak tended to decrease and its variation increased (Supplemental Fig. 4).

Tumor Response

Tumor response during treatment averaged −21% but ranged as high as +116% and as low as 280% (Fig. 4). However, population average tumor response was not significantly affected by changing the ROI_peak definition. For different ROI_peak definitions, the population average tumor response ranged from only 3% above to 3% below the mean, resulting in a 2% SD (Fig. 7). Differences in response (associated with the ROI_peak definitions) between the populations were not statistically significant (P = 1.00).

FIGURE 7.

Variation in average tumor response in population. (Left and middle) For each ROI_peak definition, tumor response was averaged over all tumors, resulting in population average response (mean response, dashed line). SUV_max response is also shown. (Right) Overall variation in population average response and variation associated with changing size, location, and shape of ROI_peak. Boxes represent SD, whiskers show range, and solid line depicts median. Variation in population average response is extremely small (~2%).

Size, location, and shape of ROI_peak all caused minimal variations in population average tumor response (Fig. 7), as all SDs were less than 2%. The magnitude and variation of population average tumor response were independent of the size, shape, and location of ROI_peak (Fig. 7).

Tumor Subgroup Analysis

Variation in SUV_peak and tumor response was determined using all 35 tumors assessed in this study. In addition, the results were recalculated on 2 different tumor subgroups. The first subgroup, in which lesions were in regions without significant background activity (n = 23), was studied in order to reduce the chance that elevated background activity was incorrectly included in ROI_peak. Consequently, abdominal, hepatic, renal, and bone lesions were excluded from this group. The second subgroup was one in which lesions were larger than 20 mL (n = 12), which is approximately 5 times larger than the largest ROI_peak (4.2 mL, 20-mm diameter). Studying this subgroup ensured that ROI_peak was completely inside the tumor boundaries and that no background activity was incorrectly included in ROI_peak. Results for the 2 tumor subgroups were almost identical to results determined using all tumors (Table 2).

TABLE 2.

Comparison of All Tumors with Different Tumor Subgroups

		Individual tumors				Population average
		SUVpeak		Response		SUVpeak		Response
Tumor group	n	Range	Average CV	Range	Average SD	Range	CV	Range	SD
All tumors	35	−46% to +49%	17%	−35% to +49%	9%	−28% to +24%	14%	−3% to +3%	2%
Tumors in regions  without significant  background activity*	23	−46% to +49%	17%	−35% to +49%	9%	−29% to +26%	15%	−4% to 13%	2%
Tumors > 20 cm3	12	−43% to +49%	16%	−18% to +36%	8%	−27% to +22%	14%	−4% to +7%	3%

^*Tumors in abdominal, hepatic, renal, and bone regions were excluded because normal, elevated ¹⁸F-FLT uptake was present in these areas.

DISCUSSION

Individual Tumor Response Versus Population Average Response

The region of interest used to determine SUV_peak can have a profound effect on its quantification and on the response of individual tumors. On average, different ROI_peak definitions resulted in intratumor variations of approximately 17% and 9% for SUV_peak and tumor response, respectively, and these variations ranged as high as 50%. This degree of variation can lead to different categorizations of response (Figs. 3 and 4) using criteria such as PERCIST (9). With PERCIST, such ambiguous response categorizations arose in over 40% of the tumor responses assessed in this study (Fig. 4; Table 1). Ambiguous response categorization of tumors increased with narrower response criteria (e.g., ±20%) but was reduced using broader response criteria (e.g., ±40%), similar to that of the MUNICON phase II trial (Table 1) (23). The sensitivity of response quantification to the ROI_peak definition reveals the need to optimize PET metrics (such as SUV_peak) for quantitative response assessment in individual patients. An ambiguous response classification underscores the necessity for a unique, consistent, standard region of interest with associated criteria that can accurately assess response.

Unlike individual tumor responses, population average response was relatively insensitive to the definition of ROI_peak used to measure response (Fig. 7), as is consistent with the findings of Krak et al. (6). The small variation (only 2%) in population average response occurred because the magnitude of individual tumor responses was independent of the ROI_peak definition. Therefore, because of an averaging effect, variation was reduced when determining population average response and might be reduced even further as more tumors are included in the population average. This robustness of population average response points to the strength of PET for accurate quantification of the average response to therapy.

Effects of Different Factors on Variation in Intratumor Response

The variation in intratumor response correlated strongly with tumor response (Fig. 5). Tumors that responded well (i.e., partial response, tumor response < −30%) exhibited significantly less variation in intratumor SUV_peak response than did tumors that responded poorly (i.e., stable disease or progressive disease, tumor response > −30%). Well-responding tumors seemed to exhibit a response more uniform than the heterogeneous response of poorly responding tumors (Fig. 6). Thus, SUV_peak–based response was considerably more sensitive to the ROI_peak definition for poorly responding tumors than for well-responding tumors.

FIGURE 5.

Variation in intratumor response vs. response. Variation in intratumor response tended to increase as response increased (i.e., as response worsened from partial response to stable disease to progressive disease).

Surprisingly, neither tumor size nor tumor uptake heterogeneity had a significant effect on the variation in either intratumor response or SUV_peak. This finding suggests that the characteristics (size, heterogeneity, etc.) of only the high-uptake regions encompassed by ROI_peak, not those of the entire tumor, directly affect the variation in tumor response and SUV_peak. Though not investigated, partial-volume effects tend to reduce uptake heterogeneity and therefore are expected to reduce the variation in both SUV_peak and response. Thus, a greater variation in both SUV_peak and response should result from partial-volume correction of the PET data.

The variable ROI_peak definition led to a variation in intratumor response that was about half that of SUV_peak. Tumor response was determined via normalization by baseline SUV_peak, in effect canceling out some of the variation in SUV_peak, which may explain the reduced variation in intratumor response. Most of the variation in SUV_peak was due to the size of ROI_peak, as is consistent with the findings of Boellaard et al. (5). As expected, variation in both intratumor response and SUV_peak increased as the size of ROI_peak increased.

For each ROI_peak definition, population average SUV_peak preserved the trends caused by the size, shape, and location of ROI_peak. Consequently, the variation in population average SUV_peak was approximately equal to the variation in intratumor SUV_peak. This result is in contrast to tumor response, in which the variation in intratumor response for different ROI_peak definitions (9%) was much larger than the variation in population average response (2%). For tumor response, there were no significant trends caused by size, shape, or location of ROI_peak, resulting in very little variation in population average response due to an averaging effect.

The wide variation in both intratumor response and SUV_peak stemmed from changes to the size, shape, and location of ROI_peak, reflecting the range of different ROI_peak definitions found in the literature. Therefore, a wide variation in intratumor response is expected under normal, realistic conditions. It is likely that an even greater variation would occur because of errors during image analysis for response assessment. For example, improper localization of ROI_peak in an average- or low-uptake region of a tumor at baseline would result in a measured tumor response that is artificially large, leading to a more extreme variation in intratumor response.

¹⁸F-FLT, rather than ¹⁸F-FDG, was selected as a radio-tracer in this study because of the antiproliferative nature of the molecular targeted therapy. Furthermore, ¹⁸F-FLT may be more effective for assessment of treatment response than is ¹⁸F-FDG (21,25,26). However, imaging of tumors using both ¹⁸F-FLT and ¹⁸F-FDG has revealed a somewhat higher SUV and broader SUV range with ¹⁸F-FDG than with ¹⁸F-FLT (17,27,28). Thus, compared with ¹⁸F-FLT, ¹⁸F-FDG is expected to result in a greater variation in both SUV_peak and tumor response due to different ROI_peaks.

SUV_peak was determined using body weight (${\text{SUV}}_{\text{peak}}^{\text{BW}}$) and not lean body mass (${\text{SUV}}_{\text{peak}}^{\text{LBM}}$, as recommended by PERCIST). However, on average, patient weight changed only 1.5% between the 2 PET scans, and this weight change would result in an approximate difference of only 0.6% between response determined using ${\text{SUV}}_{\text{peak}}^{\text{BW}}$ and ${\text{SUV}}_{\text{peak}}^{\text{LBM}}$. Consequently, in this study, approximately the same variation in SUV_peak and tumor response is expected using either ${\text{SUV}}_{\text{peak}}^{\text{BW}}$ or ${\text{SUV}}_{\text{peak}}^{\text{LBM}}$.

Implications for Treatment Response Assessment

Currently, most response assessment studies use SUV_max, although recently SUV_peak has been recommended as a more robust alternative (9). Patient-specific response quantification is subject to significant uncertainty because of the different ROI_peak definitions, and therefore SUV_peak requires further study to optimize its use for quantification of response in individual patients. Though stemming from different causes, the uncertainties associated with SUV_peak and SUV_max are comparable (6). Moreover, the noise uncertainty associated with SUV_max continues to be reduced because of the increased counts with 3-dimensional PET acquisition, the current standard on most scanners. A correlation between SUV_max and SUV_peak responses has been demonstrated (6,29), and in this study, SUV_max response was within the range of responses quantified with SUV_peak in almost 70% of all tumors (Fig. 4). Nevertheless, despite this correlation, there can be substantial differences between SUV_max and SUV_peak responses in individual tumors. For example, response quantification using the PERCIST-recommended SUV_peak (1.25-cm-diameter sphere in highest-uptake region) was 45% smaller than that of SUV_max in tumor 9 (Fig. 4), resulting in different response categorizations. Such differences underscore the need to establish the relative predictive power of SUV_peak versus SUV_max for response assessment. Consequently, the recent recommendation in favor of SUV_peak over SUV_max should be approached with caution (9). It must first be determined whether SUV_peak or SUV_max is best suited for treatment response assessment.

Clinical trials are necessary to establish the superiority of SUV_peak or SUV_max for quantification of response to therapy. These trials should investigate the sensitivities of SUV_peak and SUV_max to a variety of factors, including image noise, scan acquisition and image reconstruction parameters, partial-volume effects, tumor motion, and others. Furthermore, the clinical utility of either SUV_peak or SUV_max for response quantification will strongly depend on its correlation with patients’ clinical outcomes. Ultimately, the most robust and predictive SUV measure should be selected for quantification of treatment response.

It is probably not feasible to compare all definitions of SUV_peak with SUV_max, within the context of a larger clinical trial. Rather, a standard ROI_peak should be carefully selected to determine SUV_peak. ROI_peak should be large enough to prevent SUV_peak from suffering from noise, partial-volume effects, and other sensitivities that plague SUV_max. However, ROI_peak should not be so large that it includes substantial uptake heterogeneity and voxels that lie outside the tumor. These considerations lend support to the 1.2-cm-diameter sphere recommended by PERCIST as a standard definition of ROI_peak (for 2-cm or larger diameter tumors). This size is in the middle of the range of ROI_peak definitions found in the literature.

Identification of a suitable SUV measure for response quantification requires clinical trials. After these trials, thresholds for the different response categories (complete response, partial response, stable disease, and progressive disease) can be established using population average response data in which the uncertainties are small. Unique thresholds may be established for specific diseases and their associated therapies. The size of the thresholds will need to exceed the overall uncertainty associated with the selected SUV measure (SUV_peak or SUV_max). Subsequently, the SUV measure could be quantified in individual patients to gauge their response to therapy using the established response thresholds as a guide.

CONCLUSION

Quantification of individual tumor response with SUV_peak is sensitive to the region of interest used to determine SUV_peak. Changes to the size, shape, and location of ROI_peak result in substantial variation (≤50%) in both SUV_peak and tumor response for individual tumors. These considerable uncertainties in SUV_peak and tumor response call into question recommendations favoring SUV_peak over SUV_max for quantification of treatment response. Clinical trials are necessary to compare the efficacy of SUV_peak and SUV_max for quantification of response to therapy.