Granulomatous disease: is it a nuisance or an asset during PET/computed tomography evaluation of lung cancers?

OBJECTIVES: To evaluate combined PET-computed tomography (CT) criteria for differentiating between granulomatous disease (GD) and malignancy (CA) in oncologic PET-CT studies. METHODS: Sixty-two patients who were referred for fluoro-2-deoxyglucose (FDG) PET-CT evaluation of pulmonary lesion(s) without a history of concurrent infection were studied. PET-CT was performed 1.5 h after intravenous administration of 555 MBq 18F-FDG in the fasting state with oral contrast. Combined PET-CT criteria including (i) calcifications (Ca2+) within lymph nodes, (ii) Ca2+ in lung nodules, (iii) liver and/or spleen Ca2+, (iv) locations of lung lesion(s), (v) hilar FDG uptake, (vi) comparison of lung versus maximum mediastinal FDG uptake, (vii) lymph node uptake not in the most probable lymphatic drainage pathway from a particular lung lesion, and (viii) extra pulmonary abnormal FDG uptake were each assigned a numerical score (0-3) with progressively higher score and sum of scores toward the increasing likelihood of GD. These patients either had pathological confirmation by biopsy/resection or were followed radiographically for a period of 2 years (CA=13; GD=49). Discriminant analysis was performed on all the above criteria with this gold standard. Simple t-test and box plot analysis were also performed on the summation of the scores (from 0 in CA to 13 in GD). RESULTS: When all eight criteria were entered into discriminant analysis, the combined PET-CT criteria classified correctly 71% of patients with a sensitivity of 65% and specificity of 92% for GD. The most significant discriminating criterion was FDG uptake in the lung lesion(s) less than maximum mediastinal uptake (P=0.01). The sum scores in GD and CA were significantly different (4.9+/-2.4 vs. 3.2+/-1.5, respectively, P=0.014). Box plots showed a clear separation at a cut-off value of around 3.5. CONCLUSION: Results show that the set of combined PET-CT criteria are highly specific for GD, which is not necessarily a nuisance during oncologic evaluation. Knowledge of these criteria may attribute some of the abnormal PET findings to GD, which is a useful asset for quick recognition and clinical interpretation.

Investigating the existence of quantum metabolic values in non-Hodgkin's lymphoma by 2-deoxy-2-[F-18]fluoro-D-glucose positron emission tomography.

OBJECTIVES: To investigate the existence of quantum metabolic values in various subtypes of non-Hodgkin's lymphoma (NHL). METHODS: Fifty-eight patients with newly diagnosed NHL and positron emission tomography (PET) performed within three months of biopsy were included. The standardized uptake value (SUV) from PET over the area of biopsy and serum glucose [Glc] were recorded. The group glucose sensitivity(G) for indolent and aggressive NHL was obtained by linear regression with ln(SUV) = G x ln[Glc] + C, where C is a constant for the group. Finally, the individual's glucose sensitivity (g) was obtained by g = {ln(SUV)-C}/ln[Glc], along with their means in various subtypes of NHL. To further investigate the influence of extreme [Glc] conditions, the SUVs corrected by the individually calculated g at various glucose levels, [Glc'] using SUV' =SUV x {[Glc']/[Glc]}(g), were compared to the original SUVs for both indolent and aggressive NHL. RESULTS: The averaged g (=G) for aggressive was significant different from that for indolent NHL (-0.94 +/- 0.51 vs. +0.13 +/- 0.10, respectively, p < 0.00005). There were significant differences in SUV for [Glc] < 80 or >110 mg/dl for both types of NHL. Unlike overlap among SUVs between NHL subtypes, the g value clearly categorized them into two distinct groups with positive (near-zero) and negative g values (around -1) for the indolent and aggressive NHLs, respectively. CONCLUSIONS: Distinct quantum metabolic values of -1 and 0 were noted in NHL. Aggressive NHL has a more negative value (or higher glucose sensitivity) than that of indolent and, thus, is more susceptible to extreme glucose variation.

Addressing glucose sensitivity measured by F-18 FDG PET in lung cancers for radiation treatment planning and monitoring.

PURPOSE: To address glucose sensitivity in lung cancers before and after radiation treatment (Tx). METHODS AND MATERIALS: Twelve patients were each studied with two pre-Tx positron emission tomography (PET) scans and 3 patients each with one post-Tx PET scan, with glucose concentration [Glc] and maximum standard uptake value (SUV) recorded. The pre-Tx glucose sensitivity, g from SUV1/SUV2= {[Glc]1/[Glc]2}g and Tx index, tau from SUVpost-Tx/SUVpre-Tx = {[Glc]post-Tx/[Glc]pre-Tx}tau was calculated by linear regression. Pre-Tx SUVs were corrected to post-Tx Glc with g (SUV'pre-Tx) for a pure Tx effect, R = ln(SUVpost-Tx/SUV'pre-Tx). RESULTS: There were no significant differences in SUV but [Glc] were different (96.4 +/- 10.9 vs. 88.3 +/- 10.5, p = 0.015) between two pre-Tx PET scans. Linear regression yielded g = -0.79 and tau = -1.78 to -2.41 (p < 0.0005 in all). The %DeltaSUV after Tx for 3 patients without vs. with g correction were different by -12%, 0%, and + 7%, suggesting varying effects from glucose. R values were also different and mean R (-0.81 +/- 0.38) was significantly different from zero (p = 0.03), consistent with successful Tx as confirmed by clinico-radiologic follow-up. CONCLUSIONS: The extra dimension of glucose sensitivity, g besides SUV incorporated in the combined Tx-derived tau may be a useful global Tx evaluation index even with differing [Glc].

Glucose-normalized standardized uptake value from (18)F-FDG PET in classifying lymphomas.

UNLABELLED: Our objective was to derive the best glucose sensitivity factor (g-value) and the most discriminating standardized uptake value (SUV) normalized to glucose for classifying indolent and aggressive lymphomas. METHODS: The maximum SUV obtained from (18)F-FDG PET over the area of biopsy in 102 patients was normalized by serum glucose ([Glc]) to a standard of 100 mg/dL. Discriminant analysis was performed by using each SUV(100) (SUV x {100/[Glc]}(g), calculated using various g-values ranging from -3.0 to 0, one at a time) as a variable against the lymphoma grades, and plotting the percentage of correct classifications against g (g-plot) to search for the best g-value in normalizing SUV(100) for classifying grades. To address the influence of the extreme glucose conditions, we repeated the same analyses in 12 patients with [Glc] < or = 70 mg/dL or [Glc] > or = 110 mg/dL. RESULTS: SUV(100) correctly classified lymphoma grades ranging from 62% to 73% (P < 0.0005), depending on the g-value, with a maximum at a g-value of -0.5. For the subgroup with extreme glucose values, the g-plot also revealed higher and more optimal discrimination at a g-value of -0.5 (92%) than at a g-value of 0 (83%) (P = 0.03). The discrimination deteriorated at g < -1 in both analyses. The box plot for all cases using a g-value of -0.5 showed little overlap in classifying lymphoma grades. For a visually selected threshold SUV(100) of 7.25, the sensitivity, specificity, and accuracy of identifying aggressive grades were 82%, 79%, and 81%, respectively. CONCLUSION: The results suggest that metabolic discrimination between lymphoma grades using a glucose-normalized SUV from (18)F-FDG PET is improved by introducing g-value as an extra degree of freedom.

High predictive value of F-18 FDG PET patterns of the spine for metastases or benign lesions with good agreement between readers.

Two nuclear medicine physicians retrospectively evaluated fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) spine abnormalities in patients with cancer with the purpose of identifying straightforward criteria for benign versus malignant spine abnormalities. Four hundred seventy-five consecutive patients with colon, breast, and lung cancer were evaluated with FDG. Thirty-two patients (32) had spine abnormalities, 30 of 32 patients had adequate follow up for a final diagnosis, and 29 of 30 patients' studies were available to both PET readers for this retrospective review. The readers categorized the FDG PET abnormalities as benign, metastatic, or equivocal using a straightforward set of criteria. A final diagnosis was made using magnetic resonance imaging (MRI), computed tomography (CT), plain films, bone scans, previous studies, and clinical follow up. A single spinal focus of increased FDG activity had a relatively high probability of being a spinal metastasis (71%); and the more foci, the higher the probability. Segmental decreased activity of the spine after radiation therapy indicated benignity. The only discrepancies were with 3 abnormalities, each called metastasis by 1 reader and equivocal by the other, with a final diagnosis of metastasis in each case. Equivocal patterns required CT or MR correlation, because these could be either malignant or benign. However, abnormal patterns fulfilling either the benign or metastatic criteria described here resulted in the correct diagnoses of benign spinal changes or spinal metastases, respectively, in 100% of cases with low interobserver variation. No study was interpreted as benign by 1 reader and metastasis by the other. The 2 nuclear medicine readers agreed in their interpretations in 90% of cases.

Correlating metabolic and anatomic responses of primary lung cancers to radiotherapy by combined F-18 FDG PET-CT imaging.

BACKGROUND: To correlate the metabolic changes with size changes for tumor response by concomitant PET-CT evaluation of lung cancers after radiotherapy. METHODS: 36 patients were studied pre- and post-radiotherapy with18FDG PET-CT scans at a median interval of 71 days. All of the patients were followed clinically and radiographically after a mean period of 342 days for assessment of local control or failure rates. Change in size (sum of maximum orthogonal diameters) was correlated with that of maximum standard uptake value (SUV) of the primary lung cancer before and after conventional radiotherapy. RESULTS: There was a significant reduction in both SUV and size of the primary cancer after radiotherapy (p < 0.00005). Among the 20 surviving patients, the sensitivity, specificity, and accuracy using PET (SUV) were 94%, 50%, 90% respectively and the corresponding values using and CT (size criteria) were 67%, 50%, and 65% respectively. The metabolic change (SUV) was highly correlated with the change in size by a quadratic function. In addition, the mean percentage metabolic change was significantly larger than that of size change (62.3 +/- 32.7% vs 47.1 +/- 26.1% respectively, p = 0.03) CONCLUSION: Correlating and incorporating metabolic change by PET into size change by concomitant CT is more sensitive in assessing therapeutic response than CT alone.

A statistical investigation of normal regional intra-subject heterogeneity of brain metabolism and perfusion by F-18 FDG and O-15 H2O PET imaging.

BACKGROUND: The definite evaluation of the regional cerebral heterogeneity using perfusion and metabolism by a single modality of PET imaging has not been well addressed. Thus a statistical analysis of voxel variables from identical brain regions on metabolic and perfusion PET images was carried out to determine characteristics of the regional heterogeneity of F-18 FDG and O-15 H2O cerebral uptake in normal subjects. METHODS: Fourteen normal subjects with normal CT and/or MRI and physical examination including MMSE were scanned by both F-18 FDG and O-15 H2O PET within same day with head-holder and facemask. The images were co-registered and each individual voxel counts (Q) were normalized by the global maximal voxel counts (M) as R = Q/M. The voxel counts were also converted to z-score map by z = (Q - mean)/SD. Twelve pairs of ROIs (24 total) were systematically placed on the z-score map at cortical locations 15-degree apart and identically for metabolism and perfusion. Inter- and intra-subject correlation coefficients (r) were computed, both globally and hemispherically, from metabolism and perfusion: between regions for the same tracer and between tracers for the same region. Moments of means and histograms were computed globally along with asymmetric indices as their hemispherical differences. RESULTS: Statistical investigations verified with data showed that, for a given scan, correlation analyses are expectedly alike regardless of variables (Q, R, z) used. The varieties of correlation (r's) of normal subjects, showing symmetry, were mostly around 0.8 and with coefficient of variations near 10%. Analyses of histograms showed non-Gaussian behavior (skew = -0.3 and kurtosis = 0.4) of metabolism on average, in contrast to near Gaussian perfusion. CONCLUSION: The co-registered cerebral metabolism and perfusion z maps demonstrated regional heterogeneity but with attractively low coefficient of variations in the correlation markers.