Hematocrit and lactate trends help predict outcomes in trauma independent of CT and other clinical parameters.

Background: Hematocrit and lactate have an established role in trauma as indicators of bleeding and cell death, respectively. The wide availability of CT imaging and clinical data poses the question of how these can be used in combination to predict outcomes. Purpose: To assess the utility of hematocrit or lactate trends in predicting intensive care unit (ICU) admission and hospital length of stay (LOS) in patients with torso trauma combined with clinical parameters and injury findings on CT. Materials and Methods: This was a single-center retrospective study of adults with torso trauma in one year. Trends were defined as a unit change per hour. CT findings and clinical parameters were explanatory variables. Outcomes were ICU admission and hospital LOS. Multivariate logistic and negative binomial regression models were used to calculate the odds ratio (OR) and incident rate ratio (IRR). Results: Among 840 patients, 561 (72% males, age 39 ± 18) were included, and 168 patients (30%) were admitted to the ICU. Decreasing hematocrit trend [OR 2.54 (1.41-4.58), p = 0.002] and increasing lactate trend [OR 3.85 (1.35-11.01), p = 0.012] were associated with increased odds of ICU admission. LOS median was 2 (IQR: 1-5) days. Decreasing hematocrit trend [IRR 1.37 (1.13-1.66), p = 0.002] and increasing lactate trend [2.02 (1.43-2.85), p < 0.001] were associated with longer hospital LOS. Conclusion: Hematocrit and lactate trends may be helpful in predicting ICU admission and LOS in torso trauma independent of organ injuries on CT, age, or admission clinical parameters.

Identification of an APOE ε4-specific blood-based molecular pathway for Alzheimer's disease risk.

INTRODUCTION: The precise apolipoprotein E (APOE) ε4-specific molecular pathway(s) for Alzheimer's disease (AD) risk are unclear. METHODS: Plasma protein modules/cascades were analyzed using weighted gene co-expression network analysis (WGCNA) in the Alzheimer's Disease Neuroimaging Initiative study. Multivariable regression analyses were used to examine the associations among protein modules, AD diagnoses, cerebrospinal fluid (CSF) phosphorylated tau (p-tau), and brain glucose metabolism, stratified by APOE genotype. RESULTS: The Green Module was associated with AD diagnosis in APOE ε4 homozygotes. Three proteins from this module, C-reactive protein (CRP), complement C3, and complement factor H (CFH), had dose-dependent associations with CSF p-tau and cognitive impairment only in APOE ε4 homozygotes. The link among these three proteins and glucose hypometabolism was observed in brain regions of the default mode network (DMN) in APOE ε4 homozygotes. A Framingham Heart Study validation study supported the findings for AD. DISCUSSION: The study identifies the APOE ε4-specific CRP-C3-CFH inflammation pathway for AD, suggesting potential drug targets for the disease.Highlights: Identification of an APOE ε4 specific molecular pathway involving blood CRP, C3, and CFH for the risk of AD.CRP, C3, and CFH had dose-dependent associations with CSF p-Tau and brain glucose hypometabolism as well as with cognitive impairment only in APOE ε4 homozygotes.Targeting CRP, C3, and CFH may be protective and therapeutic for AD onset in APOE ε4 carriers.

Annualized changes in rate of amyloid deposition and neurodegeneration are greater in participants who become amyloid positive than those who remain amyloid negative.

This study longitudinally examined participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) who underwent a conversion in amyloid-beta (Aß) status in comparison to a group of ADNI participants who did not show a change in amyloid status over the same follow-up period. Participants included 136 ADNI dementia-free participants with 2 florbetapir positron emission tomography (PET) scans. Of these participants, 68 showed amyloid conversion as measured on florbetapir PET, and the other 68 did not. Amyloid converters and non-converters were chosen to have representative demographic data (age, education, sex, diagnostic status, and race). The amyloid converter group showed increased prevalence of APOE ε4 (p < 0.001), greater annualized percent volume loss in selected magnetic resonance imaging (MRI) regions (p < 0.05), lower cerebrospinal fluid Aß1-42 (p < 0.001), and greater amyloid retention (as measured by standard uptake value ratios) on florbetapir PET scans (p < 0.001) in comparison to the non-converter group. These results provide compelling evidence that important neuropathological changes are occurring alongside amyloid conversion.

Prediction of the local treatment outcome in patients with oropharyngeal squamous cell carcinoma using deep learning analysis of pretreatment FDG-PET images.

BACKGROUND: This study aimed to assess the utility of deep learning analysis using pretreatment FDG-PET images to predict local treatment outcome in oropharyngeal squamous cell carcinoma (OPSCC) patients. METHODS: One hundred fifty-four OPSCC patients who received pretreatment FDG-PET were included and divided into training (n = 102) and test (n = 52) sets. The diagnosis of local failure and local progression-free survival (PFS) rates were obtained from patient medical records. In deep learning analyses, axial and coronal images were assessed by three different architectures (AlexNet, GoogLeNET, and ResNet). In the training set, FDG-PET images were analyzed after the data augmentation process for the diagnostic model creation. A multivariate clinical model was also created using a binomial logistic regression model from a patient's clinical characteristics. The test data set was subsequently analyzed for confirmation of diagnostic accuracy. Assessment of local PFS rates was also performed. RESULTS: Training sessions were successfully performed with an accuracy of 74-89%. ROC curve analyses revealed an AUC of 0.61-0.85 by the deep learning model in the test set, whereas it was 0.62 by T-stage, 0.59 by clinical stage, and 0.74 by a multivariate clinical model. The highest AUC (0.85) was obtained with deep learning analysis of ResNet architecture. Cox proportional hazards regression analysis revealed deep learning-based classification by a multivariate clinical model (P < .05), and ResNet (P < .001) was a significant predictor of the treatment outcome. In the Kaplan-Meier analysis, the deep learning-based classification divided the patient's local PFS rate better than the T-stage, clinical stage, and a multivariate clinical model. CONCLUSIONS: Deep learning-based diagnostic model with FDG-PET images indicated its possibility to predict local treatment outcomes in OPSCCs.

Deep learning analysis using FDG-PET to predict treatment outcome in patients with oral cavity squamous cell carcinoma.

OBJECTIVE: To assess the utility of deep learning analysis using 18F-fluorodeoxyglucose (FDG) uptake by positron emission tomography (PET/CT) to predict disease-free survival (DFS) in patients with oral cavity squamous cell carcinoma (OCSCC). METHODS: One hundred thirteen patients with OCSCC who received pretreatment FDG-PET/CT were included. They were divided into training (83 patients) and test (30 patients) sets. The diagnosis of treatment control/failure and the DFS rate were obtained from patients' medical records. In deep learning analyses, three planes of axial, coronal, and sagittal FDG-PET images were assessed by ResNet-101 architecture. In the training set, image analysis was performed for the diagnostic model creation. The test data set was subsequently analyzed for confirmation of diagnostic accuracy. T-stage, clinical stage, and conventional FDG-PET parameters (the maximum and mean standardized uptake value (SUVmax and SUVmean), heterogeneity index, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were also assessed with determining the optimal cutoff from training dataset and then validated their diagnostic ability from test dataset. RESULTS: In dividing into patients with treatment control and failure, the highest diagnostic accuracy of 0.8 was obtained using deep learning classification, with a sensitivity of 0.8, specificity of 0.8, positive predictive value of 0.89, and negative predictive value of 0.67. In the Kaplan-Meier analysis, the DFS rate was significantly different only with the analysis of deep learning-based classification (p < .01). CONCLUSIONS: Deep learning-based diagnosis with FDG-PET images may predict treatment outcome in patients with OCSCC. KEY POINTS: • Deep learning-based diagnosis of FDG-PET images showed the highest diagnostic accuracy to predict the treatment outcome in patients with oral cavity squamous cell carcinoma. • Deep learning-based diagnosis was shown to differentiate patients between good and poor disease-free survival more clearly than conventional T-stage, clinical stage, and conventional FDG-PET-based parameters.

Prediction of the human papillomavirus status in patients with oropharyngeal squamous cell carcinoma by FDG-PET imaging dataset using deep learning analysis: A hypothesis-generating study.

PURPOSE: To assess the diagnostic accuracy of imaging-based deep learning analysis to differentiate between human papillomavirus (HPV) positive and negative oropharyngeal squamous cell carcinomas (OPSCCs) using FDG-PET images. METHODS: One hundred and twenty patients with OPSCC who underwent pretreatment FDG-PET/CT were included and divided into the training 90 patients and validation 30 patients cohorts. In the training session, 2160 FDG-PET images were analyzed after data augmentation process by a deep learning technique to create a diagnostic model to discriminate between HPV-positive and HPV-negative OPSCCs. Validation cohort data were subsequently analyzed for confirmation of diagnostic accuracy in determining HPV status by the deep learning-based diagnosis model. In addition, two radiologists evaluated the validation cohort image-data to determine the HPV status based on each tumor's imaging findings. RESULTS: In deep learning analysis with training session, the diagnostic model using training dataset was successfully created. In the validation session, the deep learning diagnostic model revealed sensitivity of 0.83, specificity of 0.83, positive predictive value of 0.88, negative predictive value of 0.77, and diagnostic accuracy of 0.83, while the visual assessment by two radiologists revealed 0.78, 0.5, 0.7, 0.6, and 0.67 (reader 1), and 0.56, 0.67, 0.71, 0.5, and 0.6 (reader 2), respectively. Chi square test showed a significant difference between deep learning- and radiologist-based diagnostic accuracy (reader 1: P = 0.016, reader 2: P = 0.008). CONCLUSIONS: Deep learning diagnostic model with FDG-PET imaging data can be useful as one of supportive tools to determine the HPV status in patients with OPSCC.

FDG-PET/CT activity leads to the diagnosis of unsuspected TB: a retrospective study.

OBJECTIVE: Mycobacterium tuberculosis infection leads to latent or active tuberculosis (TB). Increased uptake on 18F-fluoro-2-deoxy-glucose-positron emission tomography/computed tomography (FDG-PET/CT) has been reported in the lungs and lymph nodes of individuals with recent infection and active TB, but not in individuals without known recent exposure or suggestive symptoms. We describe five patients with lung nodules not suspected to be due to TB in whom abnormalities on FDG-PET/CT scans ultimately were attributed to TB infection. RESULTS: Patient records were searched using the words "positron emission tomography/computed tomography" and 24 codes for TB between 2004 and 2013. Patients with a diagnosis of TB and a PET/CT scan were included. Clinical and radiographic data were retrieved. PET/CT images were reviewed by an experienced radiologist. FDG-PET/CT scans revealed elevated FDG-uptake in lungs of five patients subsequently diagnosed with active (n = 3) or clinically inactive (n = 2) tuberculosis. Uptake magnitude was unrelated to disease activity. These findings suggest that tuberculosis latency may include periods of percolating inflammation of uncertain relationship to future disease risk.

ACR-ACNM Practice Parameter for the Performance of Dopamine Transporter (DaT) Single Photon Emission Computed Tomography (SPECT) Imaging for Movement Disorders.

This American College of Radiology and American College of Nuclear Medicine joint clinical practice parameter is for performance of dopamine transporter single photon emission computed tomography (SPECT) imaging, for patients with movement disorders. Parkinsonian syndrome (PS) consists of a group of neurodegenerative diseases including Parkinson disease (PD), progressive supranuclear palsy (PSP), multiple system atrophy (MSA), corticobasal degeneration (CBD), and dementia with Lewy bodies (DLB). Accurate diagnosis of PS is critical for clinical management. An important diagnostic dilemma is the differentiation of PS and non-neurodegenerative disorders, such as essential tremor (ET) or drug-induced tremor, due to the overlap of clinical symptoms. The management approach to these conditions is distinctly different. An abnormal iodine-123 ioflupane SPECT scan suggests a decreased amount of dopamine transporter in the striatum, that is, a diagnosis of nigrostriatal neurodegenerative PS, whereas a normal scan suggests ET or other nondegenerative parkinsonism (drug-induced, vascular, or psychogenic).

An amylin analog used as a challenge test for Alzheimer's disease.

INTRODUCTION: Preclinical studies demonstrate the potential of amylin in the diagnosis of Alzheimer's disease (AD). We aimed to lay the foundation for repurposing the amylin analog and a diabetes drug, pramlintide, for AD in humans. METHODS: We administered a single subcutaneous injection of 60 µg of pramlintide to nondiabetic subjects under fasting conditions. RESULTS: None of the participants developed hypoglycemia after the injection of pramlintide. The pramlintide challenge induced a significant surge of amyloid-ß peptide and a decrease in total tau in the plasma of AD subjects but not in control participants. The pramlintide injection provoked an increase in interleukin 1 receptor antagonist and a decrease in retinol-binding protein 4, which separates AD subjects from control subjects. DISCUSSION: Pramlintide use appeared to be safe in the absence of diabetes. The biomarker changes as a result of the pramlintide challenge, which distinguished AD from control subjects and mild cognitive impairment.

Imaging characteristics of metastatic nodes and outcomes by HPV status in head and neck cancers.

OBJECTIVES/HYPOTHESIS: Although several imaging characteristics of human papillomavirus (HPV)-related head and neck squamous cell carcinoma (HNSCC) have been reported, imaging features of nodal metastasis and influence to outcomes have not been well studied thus far. The purpose of the study was to investigate the imaging characteristics of nodal metastasis by HPV status in HNSCC and to clarify whether those findings influence the outcomes. STUDY DESIGN: Retrospective review. METHODS: Computed tomography and magnetic resonance imaging for initial staging on 139 patients of HNSCC with known HPV status were retrospectively reviewed. We investigated imaging characteristics of the nodal metastasis including the presence of extracapsular spread (ECS), and also investigated the influence of nodal metastasis characteristics to outcomes by HPV status. Two-year actuarial control and survival rates were estimated using the Kaplan-Meier product-limit method (P < 0.05). RESULTS: Eighty-eight patients with nodal metastasis were identified and outcome information was available for 78 patients. Nodal metastasis was significantly more common in HPV-positive patients compared to HPV-negative patients (75% vs. 54%, P = 0.009). HPV-positive patients showed a higher prevalence of ECS compared to HPV-negative patients (77% vs. 56%, P = 0.041). The prevalence of disease recurrence was more common in HPV-negative patients (67% vs. 13%, P < 0.0001), and it was independent of the presence of ECS in nodal metastasis. CONCLUSIONS: Nodal metastases were significantly more common in HPV-positive HNSCC, whereas the prevalence of disease recurrence was greater in HPV-negative HNSCC. Although ECS was noted in the majority of the HPV-positive patients with nodal metastasis, rates of recurrence were lower compared to HPV-negative patients. LEVEL OF EVIDENCE: 4.

The utility of CT for predicting bile leaks in hepatic trauma.

The purpose of this study was to determine the efficacy of CT to predict the development of bile leaks in hepatic trauma. This HIPAA-compliant retrospective study was IRB approved and consent was waived. All patients who sustained hepatic trauma between January 1, 2006, and January 31, 2012, and who underwent CT and hepatobiliary scans during the same hospital admission were included. One hundred and thirty-two patients met the inclusion criteria. Comparison between the presence of biliary injury relative to American Association for the Surgery of Trauma (AAST) hepatic injury grade and mean distance of the hepatic laceration to the inferior vena cava (IVC) was made. The ability of free fluid to predict bile injury was analyzed. Forty-one (31 %) of the 132 patients had positive hepatobiliary scans. Of these 41 patients, seven (17 %) sustained low-grade and 34 (83 %) sustained high-grade hepatic injury compared with the 37 (41 %) low-grade and 54 (59 %) high-grade hepatic injuries in the negative hepatobiliary scan group. The mean distance to the IVC was 2.4 cm (SD 2.9 cm) and 3.6 cm (SD 3.3 cm) in patients with and without bile leaks, respectively. A statistically significant difference in the proportion of high-grade injuries and the mean distance from the IVC between the two groups was identified. The presence of free fluid on CT is sensitive, but not specific, for detecting a bile leak. CT findings, including AAST liver injury grade and location of the liver laceration, are able to predict which patients are at risk for developing bile leaks as seen on hepatobiliary scintigraphy, whereas the presence of free fluid is not.

Quantitative interpretation of FDG PET/CT with myocardial perfusion imaging increases diagnostic information in the evaluation of cardiac sarcoidosis.

BACKGROUND: FDG PET/CT with myocardial perfusion imaging is a useful method for evaluating cardiac sarcoidosis (CS), but interpretation is not standardized. We developed a method for quantification of cardiac FDG PET/CT and evaluated its relationship to conventional interpretation, perfusion defects, clinical events, and immunosuppressive treatment. METHODS AND RESULTS: FDG PET/CT with MPI studies performed for CS (n = 38) were retrospectively compared to negative control studies acquired for oncologic indications (n = 10). Quantitative measures of FDG volume-intensity (Cardiac Metabolic Activity, CMA) was performed using standardized uptake values (SUVs). CMA (477.7 ± 909 vs 0.55 ± 2.1 vs 0.3 ± 0.3 g glucose, P = .02) was significantly greater in visually FDG-positive studies compared to visually negative and oncologic negative studies. Among patients with CS, CMA was greater in studies with an EF < 50% (760.3 ± 1,148 vs 87.4 ± 161 g glucose, P = .03) and preceding an adverse clinical event (1,095 ± 1,253 vs 73 ± 144 g glucose, P = .006). CMA was the only independent predictor of events by multivariate analysis. In patients with repeat examinations (n = 7), CMA decreased with prednisone treatment in 5 of 6 patients. CONCLUSIONS: Quantification of FDG uptake in CS correlates with lower EFs, clinical events, and immunosuppression treatment.

FDG PET metabolic tumor volume segmentation and pathologic volume of primary human solid tumors.

OBJECTIVE: The purpose of this study was to establish the correlation and reliability among the pathologic tumor volume and gradient and fixed threshold segmentations of (18)F-FDG PET metabolic tumor volume of human solid tumors. MATERIALS AND METHODS: There were 52 patients included in the study who had undergone baseline PET/CT with subsequent resection of head and neck, lung, and colorectal tumors. The pathologic volume was calculated from three dimensions of the gross tumor specimen as a reference standard. The primary tumor metabolic tumor volume was segmented using gradient and 30%, 40%, and 50% maximum standardized uptake value (SUVmax) threshold methods. Pearson correlation coefficient, intraclass correlation coefficient, and Bland-Altman analyses were performed to establish the correlation and reliability among the pathologic volume and segmented metabolic tumor volume. RESULTS: The mean pathologic volume; gradient-based metabolic tumor volume; and 30%, 40%, and 50% SUVmax threshold metabolic tumor volumes were 13.46, 13.75, 15.47, 10.63, and 7.57 mL, respectively. The intraclass correlation coefficients among the pathologic volume and the gradient-based and 30%, 40%, and 50% SUVmax threshold metabolic tumor volumes were 0.95, 0.85, 0.80, and 0.76, respectively. The Bland-Altman biases were -0.3, -2.0, 2.82, and 5.9 mL, respectively. Of the small tumors (< 10 mL), 23 of the 35 patients had PET segmented volume outside 50% of the pathologic volume, and among the large tumors (≥ 10 mL) three of the 17 patients had PET segmented volumes that were outside 50% of pathologic volume. CONCLUSION: FDG PET metabolic tumor volume estimated using gradient segmentation had superior correlation and reliability with the estimated ellipsoid pathologic volume of the tumors compared with threshold method segmentation.

Head and neck squamous cell cancer (stages III and IV) induction chemotherapy assessment: value of FDG volumetric imaging parameters.

INTRODUCTION: To evaluate whether the change in the metabolic tumour volume (MTV) or total lesion glycolysis (TLG) of the primary tumour, before and after induction chemotherapy, predicts outcome for patients with advanced head and neck squamous cell cancer (SCC). METHODS: Twenty-eight patients with advanced (American Joint Committee on Cancer stage III and IV) head and neck SCC who underwent positron emission tomography (PET)/CT were included in this retrospective study. Primary tumour MTV and TLG were measured using gradient and fixed percentage threshold segmentations. Outcome endpoint was disease progression or mortality. Pearson correlation, Bland-Altman and receiver operator characteristic analysis were performed. RESULTS: The Pearson's correlation coefficients between percentage changes (pre- and post-induction chemotherapy) from gradient MTV (MTVG) and the 38% SUVmax threshold MTV (MTV38) was 0.96 and between MTVG and the 50% threshold MTV (MTV50) was 0.95 (P < 0.0001). The corresponding Pearson r between TLGG and TLG38 was 0.94 and between TLGG and TLG50 was 0.96 (P < 0.0001). The least bias was 1.89% (standard deviation = 25.30%) between the percentage changes of MTVG and MTV50. The areas under the curve for predicting progression or mortality were 0.76 (P = 0.03) for MTVG and 0.82 for TLGG (P = 0.009). Optimum cut points of a 42% reduction in MTVG and a 55% reduction in the TLGG predict event-free survival with a sensitivity of 62.5% and a specificity of 90% and a hazards ratio of 6.25. CONCLUSION: A reduction in primary tumour MTV of at least 42% or in TLG of at least 55% after induction chemotherapy may predict event-free survival in patients with advanced head and neck SCC.

Interreader agreement and variability of FDG PET volumetric parameters in human solid tumors.

OBJECTIVE: The purpose of this article is to evaluate the interreader agreement and variability of two (18)F-FDG PET parameters, metabolic tumor volume and total lesion glycolysis, in human solid tumors. MATERIALS AND METHODS: One hundred eleven patients (mean [± SD] age, 61.9 ± 12.5 years) with baseline staging FDG PET/CT scans were included. Two readers independently read the scans and segmented metabolic tumor volume and total lesion glycolysis using two fixed thresholds, 40% and 50% of the lesion's maximum standardized uptake value (SUVmax). The impact of the lesion's FDG avidity and location on reader agreement and variability was established. Intraclass correlation coefficient (ICC), precision, and Bland-Altman analysis were used to evaluate agreement and variability. RESULTS: The ICCs for 40% and 50% SUVmax segmentations of metabolic tumor volume between the readers were 0.987 and 0.995, and the corresponding values for 40% and 50% SUVmax segmentations of total lesion glycolysis were 0.987 and 0.986, respectively (p = 0.0001). The corresponding precisions were 0.5%, 0.2%, 0.5%, and 0.5%, respectively. The mean biases between the readers for 40% and 50% SUVmax segmentations of metabolic tumor volume were -1.78 ± 8.42 mL and -0.46 ± 2.1 mL and for 40% and 50% SUVmax segmentations of total lesion glycolysis were -7.3 ± 31.6 g and -2.97 ± 12.86 g, respectively. Subgroup analysis showed better precision and lesser variability for 50% SUVmax segmentations of metabolic tumor volume and total lesion glycolysis in patients with the highest and lowest FDG-avid primary tumors. The precision was highest and variability was lowest for lung tumors. CONCLUSION: There is excellent interreader agreement for measurement of metabolic tumor volume and total lesion glycolysis with 40% and 50% SUVmax threshold segmentations in human solid tumors.

Impact of concurrent diagnostic level CT with PET/CT on the utilization of stand-alone CT and MRI in the management of head and neck cancer patients.

PURPOSE OF THE REPORT: This study aims to determine if the expansion of a PET/CT service to include simultaneous contrast-enhanced CT with PET (PET/DCT) leads to a reduction of supplemental diagnostic CT (sCT) performed within a 6-month period centered around PET/CT for initial treatment planning of patients with head and neck cancers. PATIENTS AND METHODS: There were 91 patients with head and neck cancers who had a non-contrast-enhanced PET/CT with CT (PET/aCT), and 153 patients had a PET/DCT. We compared the utilization of sCT before and after PET/aCT or PET/DCT. Logistic regression analysis, unpaired t test, and analysis of variance were performed. RESULTS: Among the 75 patients who had sCT scans in the 3 months before their PET/CT, 44 (58.7%) scans were performed in patients who had a PET/aCT and 31 (41.3%) scans were performed in patients who had a PET/DCT (P < 0.001). Among the 36 patients who had a CT in the 3 months after their baseline PET/CT, 23 (63.9%) were performed in patients who had a baseline PET/aCT and 13 (36.1%) were performed in patients who had a baseline PET/DCT (P < 0.001). The adjusted odds ratio for performing an sCT within 3 months before and after baseline PET/DCT scan as opposed to a PET/aCT scan was 0.24 (P < 0.001) and 0.31 (P < 0.01), respectively. CONCLUSIONS: The opportunity to order simultaneous diagnostic CT imaging with PET/CT (PET/DCT) reduced the referrals for stand-alone CT neck imaging in the initial treatment plan of head and neck cancer patients when compared to a service that only offered the PET/CT scan with CT for attenuation correction (PET/aCT).

The role of PET/CT in the management of cervical cancer.

OBJECTIVE. Cervical cancer is the second most common malignancy in women worldwide and the third most common cause of cancer mortality in the United States. The aim of this article is to describe cervical cancer and outline the value of (18)F-FDG PET/CT in the management of cervical malignancy. CONCLUSION. The value of PET/CT has been found in staging and treatment strategy for cervical cancer. FDG PET/CT facilitates decision-making and radiation treatment planning and provides important information about treatment response, disease recurrence, and long-term survival.

FDG PET/CT in the management of primary pleural tumors and pleural metastases.

OBJECTIVE. FDG PET/CT is emerging as an important modality in the evaluation of pleural tumors. PET/CT has an established role in the diagnosis and staging and shows promise in therapy planning, therapy response assessment, and providing prognostic information in patients with malignant pleural mesothelioma. This modality has distinct advantages in characterizing other primary pleural tumors and pleural metastases. CONCLUSION. FDG PET/CT is a useful imaging modality in the management of patients with primary pleural tumors and pleural metastases.

PET/CT mediastinal and liver FDG uptake: effects of biological and procedural factors.

INTRODUCTION: To establish the effects of biological and procedural factors on mediastinal and liver [(18) F]-fluorodeoxyglucose (FDG) uptake in oncological FDG positron emission tomography/computed tomography (PET/CT). METHODS: This retrospective study included 557 patients who had a baseline FDG PET/CT scan in 2008 and 2009. Mediastinal and liver standardised uptake values mean normalised to lean body mass (SUVlbm mean) were measured in each patient. Univariate and multivariate regression models were established. Study population was then dichotomised into low and high body mass index (BMI) groups, and linear regression models were established for the effects of age, incubation period and blood glucose levels. RESULTS: BMI had the highest adjusted effect (standardised beta coefficient, b = 0.43) (P < 0.001) and partial correlation, adjusting for covariates included in the final model (r = 0.45; P < 0.001) on mediastinal FDG uptake. Partial correlations (r) were 0.22 for age, -0.17 for male gender, -0.25 for incubation period and 0.14 for blood glucose (P < 0.001). The linear regression models showed significant differences in mediastinal FDG uptake between the low and high BMI groups and the effects of age, incubation period and basal blood glucose levels (P < 0.001). Similar results were observed for liver FDG uptake except the partial correlation for incubation period was r = -0.09 (P = 0.02). CONCLUSION: BMI has the highest effect and correlation on mediastinal and liver FDG uptake. FDG uptake time has a greater effect on mediastinal than liver SUVlbm mean.

PET-based primary tumor volumetric parameters and survival of patients with non-small cell lung carcinoma.

OBJECTIVE: The purpose of the study was to assess metabolic tumor volume and total glycolytic activity of the primary tumor as prognostic parameters for outcome in patients with non-small cell lung carcinoma (NSCLC). MATERIALS AND METHODS: Thirty-nine patients who had undergone a baseline staging PET/CT examination at our institution for the diagnosis of NSCLC were retrospectively identified. The maximum standardized uptake value (SUV(max)), metabolic tumor volume, and total glycolytic activity were segmented from PET using the gradient method; 12-month survival and overall survival at the end of follow-up were used as outcome measures. Multivariate logistic regression, receiver operating characteristic curve analysis, and Kaplan-Meier curves for survival analysis were generated and compared using the Mantel-Cox log-rank test. RESULTS: The mean gradient-based metabolic tumor volume and gradient-based total glycolytic activity were significantly greater in the patients who died (93.3 mL and 597.5 g) than in those who survived (19.3 mL and 193.9 g, respectively) (p < 0.003 and p < 0.031). There was no statistically significant difference in the mean SUV(max) between the patients who survived (12.7) at 12 months and those who had died (13.1) (p = 0.85). On multivariate analysis, gradient-based metabolic tumor volume was the only variable associated with 12-month mortality when adjusted for all other factors.(.) The area under the curve (AUC) for gradient-based metabolic tumor volume was 0.77 (p < 0.006). A significant difference in the time to survival was observed between high and low gradient-based metabolic tumor volume (log-rank p < 0.05) cohorts using the median gradient-based metabolic tumor volume (9.7 mL) as the cut point. CONCLUSION: PET-based volumetric imaging parameters are potential prognostic markers of outcome in patients with NSCLC.