Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review.

PURPOSE: This paper reviews recent applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging. Recent advances in Deep Learning (DL) and GANs catalysed the research of their applications in medical imaging modalities. As a result, several unique GAN topologies have emerged and been assessed in an experimental environment over the last two years. METHODS: The present work extensively describes GAN architectures and their applications in PET imaging. The identification of relevant publications was performed via approved publication indexing websites and repositories. Web of Science, Scopus, and Google Scholar were the major sources of information. RESULTS: The research identified a hundred articles that address PET imaging applications such as attenuation correction, de-noising, scatter correction, removal of artefacts, image fusion, high-dose image estimation, super-resolution, segmentation, and cross-modality synthesis. These applications are presented and accompanied by the corresponding research works. CONCLUSION: GANs are rapidly employed in PET imaging tasks. However, specific limitations must be eliminated to reach their full potential and gain the medical community's trust in everyday clinical practice.

Automatic characterization of myocardial perfusion imaging polar maps employing deep learning and data augmentation.

OBJECTIVE: To investigate a deep learning technique, more specifically state-of-the-art convolutional neural networks (CNN), for automatic characterization of polar maps derived from myocardial perfusion imaging (MPI) studies for the diagnosis of coronary artery disease. SUBJECTS AND METHODS: Stress and rest polar maps corresponding to 216 patient cases from the database of the department of Nuclear Medicine of our institution were analyzed. Both attenuation-corrected (AC) and non-corrected (NAC) images were included. All patients were subjected to invasive coronary angiography within 60 days from MPI. As the initial dataset of this study was small to train a deep learning model from scratch, two strategies were followed. The first is called transfer learning. For this, we employed the state-of-the-art CNN called VGG16, which has been broadly exploited in medical imaging classification tasks. The second strategy involves data augmentation, which is achieved by the rotation of the polar maps, to expand the training set. We evaluated VGG16 with 10-fold cross-validation on the original set of images performing separate experiments for AC and NAC polar maps, as well as for their combination. The results were compared to the standard semi-quantitative polar map analysis based on summed stress and summed difference scores, as well as to the medical experts' diagnostic yield. RESULTS: With reference to the findings of coronary angiography, VGG16 achieved an accuracy of 74.53%, sensitivity 75.00% and specificity 73.43% when the AC and NAC polar maps were incorporated into one single image set. Respective figures of MPI interpretation by experienced Nuclear Medicine physicians were 75.00%, 76.97% and 70.31%. The accuracy of semi-quantitative polar map analysis was lower, 66.20% and 64.81% for AC and NAC technique, respectively. CONCLUSION: The proposed deep learning model with data augmentation techniques performed better than the conventional semi-quantitative polar map analysis and competed with doctor's expertise in this particular patient cohort and image set. The model could potentially serve as an assisting tool to support interpretation of MPI studies or could be used for teaching purposes.

90Y-microsphere radioembolization: The method, clinical evidence and perspective.

The current review unfolds the procedural steps and the clinical evidence for yttrium-90 (90Y)-microspheres radioembolization. Radioembolization is part of the loco-regional therapeutic spectrum for liver malignancy and involves the invasive, intra-arterial delivery of microspheres carrying ß-emitter isotopes in order to destroy cancerous tissue via ionizing radiation. The main steps of the therapeutic process are selection of eligible patients, angiographic workup, simulation scintigraphy, pre-treatment dosimetry, actual treatment and post-treatment imaging/dosimetry. Radioembolization is routinely applied in advanced stage hepatocellular carcinoma (HCC), yet its role is being investigated even in earlier stages. Prospective, randomized controlled trials did not verify increased overall survival of radioembolization over systemic treatment with sorafenib in HCC; however, it showed survival benefit in certain sub-groups and a favorable toxicity profile with fewer adverse events. Radioembolization is also applied in metastatic colon cancer showing tumoral liver responses, which however did not translate into an overall survival benefit. Data regarding applications of this method in other neoplasms, such as neuroendocrine tumors, breast cancer and melanoma are also presented. There are ongoing clinical trials to define the role of radioembolization within recent treatments algorithms, to determine optimal combinations of this treatment with systemic and targeted therapies and to decide the patients' sub-groups, who will benefit the most.

The impact of transmission-emission misregistration on the interpretation of SPET/CT myocardial perfusion studies and the value of misregistration correction.

OBJECTIVE: Previous studies indicate that the quality of single photon emission tomography/computed tomography (SPET/CT) myocardial perfusion imaging (MPI) is degraded by even mild transmission-emission misregistrations. The purpose of the current study was to investigate the impact of SPET/CT misalignment on the interpretation of MPI and examine the value of a commercial software application for registration correction. SUBJECTS AND METHODS: A total of 255 technetium-99m ((99m)Tc)-tetrofosmin stress/rest MPI examinations in 150 patients were reviewed for SPET/CT misalignment. After registration correction by the software, images were reassessed for interpretation differences from the misregistered study. The diagnostic benefit of reregistration was determined by taking into account the non-attenuation compensated image pattern, combined stress-rest evaluation, gated-SPET data and patient's history. In a phantom experiment and in 3 representative clinical cases, SPET/CT misalignment was purposely created by the software by sequential slice shifts and its effect was evaluated quantitatively. RESULTS: Misregistration ≥1 pixel in at least one direction was observed in 24% of studies. Interpretation of MPI changed after registration correction in 11% of cases with misalignment <1 pixel, in 18% with 1-2 and in 73% with ≥2 pixels. The diagnostic information seemed to improve after registration correction in 58% of studies irrespective of the degree of misregistration. Software-simulated misregistration had dissimilar effects in the phantom and the 3 selected clinical cases. CONCLUSIONS: The impact of SPET/CT misregistration on MPI interpretation although influenced by the degree and direction of slice misplacement, it is also case-specific and hardly predictable. Registration restoration by the software seems worthwhile regardless of misregistration magnitude.

CT-based attenuation correction in Tl-201 myocardial perfusion scintigraphy is less effective than non-corrected SPECT for risk stratification.

BACKGROUND: Previous studies advocate the use of attenuation correction in myocardial perfusion scintigraphy (MPS) for patient risk stratification. METHODS: Six-hundred and thirty-seven unselected patients underwent Tl-201 MPS by a hybrid SPECT/CT system. Attenuation-corrected (AC) and non-corrected (NAC) images were interpreted blindly and summed stress scores (SSS) were calculated. Study endpoints were all-cause mortality and the composites of death/non-fatal acute myocardial infarction (AMI) and death/AMI/late revascularization. RESULTS: During a follow-up of 42.3 ± 12.8 months 24 deaths, 13 AMIs and 28 revascularizations were recorded. SSS groups formed according to event rate distribution across SSS values were: 0-4, 5-13, >13 for NAC and 0-2, 3-9, >9 for AC. Kaplan-Meier functions were statistically significant between NAC SSS groups for all study endpoints. AC discriminated only between SSS 0-2 and >9 for death/AMI and between 0-2 and 3-9 for death/AMI/revascularization. In the univariate Cox regression abnormal NAC (SSS > 4) was accompanied with much higher hazards ratios than abnormal AC (SSS > 2). In the multivariate model abnormal AC yielded no significance for either endpoint whereas abnormal NAC proved independent from other covariates for the composite endpoints. CONCLUSION: Our results challenge the effectiveness of CT-based AC for risk stratification of patients referred for MPS.

Bone scintigraphy depicts bilateral atypical femoral stress fractures with metachronous presentation, long before a complete fracture occurs.

Atypical femoral fractures (AFF), although rare, are recognized more often during the last decade. They are located in the subtrochanteric region or the femoral shaft, may be bilateral, can evolve to complete fractures after bone overload or minimal trauma and have specific radiological features. The complete fractures have horizontal or slightly oblique configuration accompanied by a medial spike, are non-comminuted, and extend to both cortices. There is also generalized cortical thickening of femoral shaft. Newer evidence suggests that AFF are stress or insufficiency fractures, possibly associated with long-term use of bisphoshonates (BP). AFF can also occur in oncologic patients referred for bone scintigraphy and, in such a case, they should be differentiated from bone metastases. We present here a case with bilateral AFF with metachronous appearance in a female patient with a history of breast cancer and osteoporosis. The first AFF had been depicted on bone scintigraphy 3 years before a complete fracture occurred at this site, but the finding was overlooked. A second bone scan performed shortly after the fracture in order to exclude underlying bone metastases disclosed an additional unsuspected incomplete AFF in the contralateral femur, which was confirmed by radiography. In conclusion, oncologists should consider other causes of bone pain besides bone metastatic disease, and physicians interpreting whole body bone scans of oncologic patients should be aware of the entity of AFF, in order to avoid false positive results and provide early information about an impending complete AFF.

Integrating Machine Learning in Clinical Practice for Characterizing the Malignancy of Solitary Pulmonary Nodules in PET/CT Screening.

The study investigates the efficiency of integrating Machine Learning (ML) in clinical practice for diagnosing solitary pulmonary nodules' (SPN) malignancy. Patient data had been recorded in the Department of Nuclear Medicine, University Hospital of Patras, in Greece. A dataset comprising 456 SPN characteristics extracted from CT scans, the SUVmax score from the PET examination, and the ultimate outcome (benign/malignant), determined by patient follow-up or biopsy, was used to build the ML classifier. Two medical experts provided their malignancy likelihood scores, taking into account the patient's clinical condition and without prior knowledge of the true label of the SPN. Incorporating human assessments into ML model training improved diagnostic efficiency by approximately 3%, highlighting the synergistic role of human judgment alongside ML. Under the latter setup, the ML model had an accuracy score of 95.39% (CI 95%: 95.29-95.49%). While ML exhibited swings in probability scores, human readers excelled in discerning ambiguous cases. ML outperformed the best human reader in challenging instances, particularly in SPNs with ambiguous probability grades, showcasing its utility in diagnostic grey zones. The best human reader reached an accuracy of 80% in the grey zone, whilst ML exhibited 89%. The findings underline the collaborative potential of ML and human expertise in enhancing SPN characterization accuracy and confidence, especially in cases where diagnostic certainty is elusive. This study contributes to understanding how integrating ML and human judgement can optimize SPN diagnostic outcomes, ultimately advancing clinical decision-making in PET/CT screenings.

Is there a role for Nuclear Medicine in diagnosis and management of patients with primary aldosteronism?

Primary aldosteronism (PA) is the most common cause of secondary hypertension. The diagnosis of PA is of clinical importance for choosing the appropriate treatment, meaning, surgery for the unilateral disease, and inclusion of aldosterone antagonists in the antihypertensive treatment for the bilateral disease. Current diagnostic approaches showed that the prevalence of PA is much higher than previously estimated. There is still controversy regarding the true prevalence of PA in hypertensive patients. The gold standard for differentiating between unilateral and bilateral disease is the adrenal vein sampling (AVS), a method that is invasive and is performed accurately in only few dedicated centers. Non invasive methods (imaging) for discriminating the two entities are: the CT scan, MRI and iodocholesterol (NP-59) scintigraphy performed under dexamethasone suppression. But the accuracy of imaging compared to AVS is suboptimal and can result in wrong therapeutic decisions. NP-59 scintigraphy is a non-invasive functional imaging technique that reveals the adrenal cortical autonomic function and could have of incremental value over anatomical imaging. In conclusion, in previous years NP-59 scintigraphy was used infrequently, but recently with the advent of hybrid single photon emission tomography (SPET/CT) systems the interest in NP-59 scintigraphy has been renewed. Studies comparing NP-59 SPET/CT imaging with AVS are warranted in order to establish its diagnostic accuracy.

ST-segment depression during vasodilator stress is of minor clinical importance in women with normal myocardial perfusion imaging and low or intermediate risk of coronary artery disease.

PURPOSE: The prognostic value of electrocardiographic (ECG) ST-segment depression during vasodilator stress testing in patients with normal myocardial perfusion scintigraphy (MPS) is based on retrospective studies with controversial results. Moreover, the true incidence of obstructive coronary artery disease (CAD) in these patients is unknown. METHODS: During a 33-month period, all consecutive patients referred for MPS were prospectively evaluated for interpretable ST-segment depression ≥ 1 mm during vasodilator stress testing. Of 1,687 patients with normal MPS and without known CAD, 109 (100 women) aged 65.2 ± 9.2 years demonstrated ST-segment shifts and formed the ECG-positive group. The pretest probability of CAD was low in 56%, intermediate in 39% and high in 5%. They were advised to proceed to coronary angiography. An equal number of patients with normal MPS and no ECG abnormalities matched for CAD predisposing factors comprised the control group. Follow-up of both groups was accomplished through a telephone interview. RESULTS: Fifty-two patients from the ECG-positive group (48%) consented to coronary angiography. Six (11.5%) had obstructive CAD (≥50% lumen stenosis), one with left main artery disease, while three required revascularization. Follow-up was complete in 99 ECG-positive patients for a period of 20.6 ± 8.9 months. One hard event (non-fatal myocardial infarction) and one soft event (revascularization) were observed. No event was recorded in the control group. CONCLUSION: In patients with low-intermediate risk of CAD, "ischaemic" ECG changes during vasodilator stress combined with normal MPS are encountered mostly in women and are associated with a low prevalence of significant CAD and a low cardiac event rate.

A Deep Learning Methodology for the Detection of Abnormal Parathyroid Glands via Scintigraphy with 99mTc-Sestamibi.

BACKGROUND: Parathyroid proliferative disorder encompasses a wide spectrum of diseases, including parathyroid adenoma (PTA), parathyroid hyperplasia, and parathyroid carcinoma. Imaging modalities that deliver their results preoperatively help in the localisation of parathyroid glands (PGs) and assist in surgery. Artificial intelligence and, more specifically, image detection methods, can assist medical experts and reduce the workload in their everyday routine. METHODS: The present study employs an innovative CNN topology called ParaNet, to analyse early MIBI, late MIBI, and TcO4 thyroid scan images simultaneously to perform first-level discrimination between patients with abnormal PGs (aPG) and patients with normal PGs (nPG). The study includes 632 parathyroid scans. RESULTS: ParaNet exhibits a top performance, reaching an accuracy of 96.56% in distinguishing between aPG and nPG scans. Its sensitivity and specificity are 96.38% and 97.02%, respectively. PPV and NPV values are 98.76% and 91.57%, respectively. CONCLUSIONS: The proposed network is the first to introduce the automatic discrimination of PG and nPG scans acquired by scintigraphy with 99mTc-sestamibi (MIBI). This methodology could be applied to the everyday routine of medics for real-time evaluation or educational purposes.

Deep learning exploration for SPECT MPI polar map images classification in coronary artery disease.

OBJECTIVE: The exploration and the implementation of a deep learning method using a state-of-the-art convolutional neural network for the classification of polar maps represent myocardial perfusion for the detection of coronary artery disease. SUBJECTS AND METHODS: In the proposed research, the dataset includes stress and rest polar maps in attenuation-corrected (AC) and non-corrected (NAC) format, counting specifically 144 normal and 170 pathological cases. Due to the small number of the dataset, the following methods were implemented: First, transfer learning was conducted using VGG16, which is applied broadly in medical industry. Furthermore, data augmentation was utilized, wherein the images are rotated and flipped for expanding the dataset. Secondly, we evaluated a custom convolutional neural network called RGB CNN, which utilizes fewer parameters and is more lightweight. In addition, we utilized the k-fold validation for evaluating variability and overall performance of the examined model. RESULTS: Our RGB CNN model achieved an agreement rating of 92.07% with a loss of 0.2519. The transfer learning technique (VGG16) attained 95.83% accuracy. CONCLUSIONS: The proposed model could be an effective tool for medical classification problems, in the case of polar map data acquired from myocardial perfusion images.

Parametric images via dynamic 18F-fluorodeoxyglucose positron emission tomographic data acquisition in predicting midterm outcome of liver metastases secondary to gastrointestinal stromal tumours.

PURPOSE: (18)F-Fluorodeoxyglucose positron emission tomography (FDG PET) may underestimate viable tumour tissue in patients with gastrointestinal stromal tumours (GIST) treated with molecular targeted agents. The aim of the present study was to investigate the value of parametric images generated after dynamic data acquisition for the detection of active liver metastases. METHODS: The analysis included 65 dynamic FDG PET studies in 34 patients with liver metastases from GIST who were treated with imatinib or sunitinib. Parametric images of intercept and slope were calculated by dedicated software using a voxel-based linear regression of time-activity data. Intercept images represent the tracer's distribution volume and the slope its overall metabolic turnover. All images were assessed visually and semi-quantitatively. Liver disease status was established 12 months after each PET study. Dichotomous variables of visual interpretation and various quantitative parameters were entered in a statistical model of linear discriminant analysis. RESULTS: Visual analysis of slope images was more sensitive than the standard 1-h FDG uptake evaluation (70.6 vs 51.0%, p = 0.016) in detecting cases with liver disease progression (n = 51). Specificity did not differ. Combination of all variables in the discriminant analysis model correctly classified 87.7% of cases as progressive or non-progressive disease. Sensitivity was raised to 88.2%. CONCLUSION: Parametric images of intercept and slope add a new dimension to the interpretation of FDG PET studies, by isolating visually and quantifying the perfusion and phosphorylation-dependent part of tracer uptake. In treated GIST patients, integration of this information with the 1-h uptake data achieves better characterization of hepatic lesions with respect to disease activity.

Imaging myocardial inflammation of various etiologies with 99mTc-depreotide SPET/CT.

Previous reports suggested the accumulation of technetium-99m-depreotide trifluoroacetate ((99m)Tc-D) at the sites of active infection or inflammation. Binding of depreotide to over-expressed somatostatin receptors in activated lymphocytes and macrophages probably accounts for the depiction of inflammation. We speculated that myocardial inflammation could also be illustrated by (99m)Tc-D scintigraphy. We report on 3 patients with the clinical diagnosis of myocarditis of various etiologies, in which (99m)Tc-D SPET/CT demonstrated obvious tracer uptake in the myocardium of the left ventricle. In conclusion, we suggest that depreotide imaging can depict myocardial inflammation, thus supporting clinical diagnosis.

Advanced fuzzy cognitive maps: state-space and rule-based methodology for coronary artery disease detection.

According to the World Health Organization, 50% of deaths in European Union are caused by Cardiovascular Diseases (CVD), while 80% of premature heart diseases and strokes can be prevented. In this study, a Computer-Aided Diagnostic model for a precise diagnosis of Coronary Artery Disease (CAD) is proposed. The methodology is based on State Space Advanced Fuzzy Cognitive Maps (AFCMs), an evolution of the traditional Fuzzy Cognitive Maps. Also, a rule-based mechanism is incorporated, to further increase the knowledge of the proposed system and the interpretability of the decision mechanism. The proposed method is evaluated utilizing a CAD dataset from the Department of Nuclear Medicine of the University Hospital of Patras, in Greece. Several experiments are conducted to define the optimal parameters of the proposed AFCM. Furthermore, the proposed AFCM is compared with the traditional FCM approach and the literature. The experiments highlight the effectiveness of the AFCM approach, obtaining 85.47% accuracy in CAD diagnosis, showing an improvement of +7% over the traditional approach. It is demonstrated that the AFCM approach in developing Fuzzy Cognitive Maps outperforms the conventional approach, while it constitutes a reliable method for the diagnosis of Coronary Artery Disease.

Automatic classification of solitary pulmonary nodules in PET/CT imaging employing transfer learning techniques.

Early and automatic diagnosis of Solitary Pulmonary Nodules (SPN) in Computed Tomography (CT) chest scans can provide early treatment for patients with lung cancer, as well as doctor liberation from time-consuming procedures. The purpose of this study is the automatic and reliable characterization of SPNs in CT scans extracted from Positron Emission Tomography and Computer Tomography (PET/CT) system. To achieve the aforementioned task, Deep Learning with Convolutional Neural Networks (CNN) is applied. The strategy of training specific CNN architectures from scratch and the strategy of transfer learning, by utilizing state-of-the-art pre-trained CNNs, are compared and evaluated. To enhance the training sets, data augmentation is performed. The publicly available database of CT scans, named as Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), is also utilized to further expand the training set and is added to the PET/CT dataset. The results highlight the effectiveness of transfer learning and data augmentation for the classification task of small datasets. The best accuracy obtained on the PET/CT dataset reached 94%, utilizing a modification proposal of a state-of-the-art CNN, called VGG16, and enhancing the training set with LIDC-IDRI dataset. Besides, the proposed modification outperforms in terms of sensitivity several similar researches, which exploit the benefits of transfer learning. Overview of the experiment setup. The two datasets containing nodule representations are combined to evaluate the effectiveness of transfer learning over the traditional approach of training Convolutional Neural Networks from scratch.

Comparison between 180 degrees and 360 degrees acquisition arcs with and without correction by CT-based attenuation maps in normal hearts at rest.

OBJECTIVE: To investigate the effect of acquisition arc (180 degrees or 360 degrees ) and attenuation correction (AC), in artifact occurrence and image uniformity of myocardial perfusion SPECT studies in normal hearts. METHODS: Twenty male and 44 female patients with primary hyperparathyroidism and low probability of resting perfusion abnormalities were analysed. Tc-sestamibi myocardial perfusion studies were performed at rest with a hybrid SPECT/CT system. An anthropomorphic phantom was also imaged. RESULTS: Without AC, a 360 degrees orbit resulted in significantly lower artifact rates compared to the standard 180 degrees in both gender groups. Differences persisted (P<0.001) even after adjusting reconstruction filter settings to compensate for disproportionate count statistics between the two arcs. However, gender-related variation was not considerably decreased and sub-diaphragmatic activity was augmented with a 360 degrees arc. After AC with either arc, substantially lower defect scores and minimal gender-related differences were obtained compared to the standard technique. A 360 degrees arc yielded lower defect rates and count variability than did the 180 degrees arc (P<0.05). These differences were small and were eliminated after weighting for dissimilar count statistics. Sub-diaphragmatic signal was amplified, particularly with 360 degrees ; severe bowel-myocardial activity overlap complicated image interpretation in 14% of cases with 360 degrees versus 8% with 180 degrees . In certain aspects, phantom imaging findings diverged from patient studies. CONCLUSION: Without AC there is significant disparity between 180 degrees and 360 degrees concerning artifact occurrence. After CT-based AC differences between arcs in defect rate and image uniformity seem less critical. However, 180 degrees is favoured by less intensification of intestinal activity.

Two cases of synovitis, acne, pustulosis, osteitis--SAPHO syndrome.

Synovitis, acne, pustulosis, osteitis (SAPHO) syndrome is rare with yet unknown prevalence. The difficulty in recognizing the syndrome is due to the very wide diversity of its signs and symptoms, the lack of skin manifestations in many cases and to confusion in medical terminology in describing this syndrome. In this paper, we present two cases with characteristic bone lesions in bone scan and in radiology images that are considered to be SAPHO syndrome. In the first case the characteristic bone single photon emission tomography scan findings in a patient with spine involvement supposed by bone biopsy but were not followed by characteristic skin manifestations. The point of interest of this case lies on the significant improvement of both symptoms and scintigraphic findings after treatment with biphosphonates. In the second case the diagnosis was also based on the characteristic bone scan findings, although the patient referred to us for staging of prostate cancer. Detailed history and clinical examination revealed skin manifestations of the syndrome.

Assessment of absolute Tc-99m tetrofosmin retention in the myocardium as an index of myocardial blood flow and coronary flow reserve by gated-SPECT/CT: a feasibility study.

OBJECTIVE: Estimation of myocardial blood flow (MBF) and coronary flow reserve (CFR) by SPECT myocardial perfusion imaging (MPI) remains challenging. Our aim was to approximate MBF and CFR by quantifying the absolute Tc-99m tetrofosmin retention in the myocardium via gated-SPECT/CT MPI. METHODS: Tracer retention was calculated on the basis of the microsphere kinetic model and served as an index of MBF at stress and rest (sMBFi, rMBFi). CFR was given by the sMBFi/rMBFi ratio. A planar first-pass acquisition during dipyridamole stress and at rest provided the data for tracer input determination. The input was represented by the integral of a gamma variate fitted on the time-activity curve of the left ventricle. Gated-SPECT/CT was performed 1 h post tracer injection and myocardial activity was measured in attenuation-corrected transaxial slices by a threshold VOI. The input was also compensated for tissue attenuation by measuring the distance from the centre of the left ventricle to the body surface on fused SPECT/CT slices. Input and uptake results were adjusted for planar-SPECT counting geometry differences by the aid of a phantom experiment. Thirty-nine subjects with low probability of coronary artery disease (CAD), age lower than 75 years and normal MPI (control group) were compared with 57 patients with documented CAD (CAD group). RESULTS: CFR and sMBFi values of CAD patients (1.39 ± 0.37 and 1.42 ± 0.35 ml/min/g) were considerably lower (p < 0.0001) than controls (1.68 ± 0.25 and 1.72 ± 0.37 ml/min/g). Significant difference in CFR (p = 0.03) was also noted between CAD patients with normal MPI (1.48 ± 0.38) and controls. However, sMBFi managed to discriminate certain CAD subgroups (normal MPI/ischemia/scar/scar and ischemia) more efficiently than CFR. Maximum heart rate-blood pressure product (RPP) during stress was an independent predictor of sMBFi and CFR. The other independent CFR correlates were resting RPP and diabetes mellitus, while sMBFi was associated with age, sex, smoking, and stress perfusion defects. CONCLUSIONS: Despite the low myocardial extraction fraction of Tc-99m tetrofosmin, an approximation of MBF and CFR is feasible with gated-SPECT/CT MPI. These flow indices together were able to discriminate CAD patients from controls and stratify different patient subgroups.

Tc-99m depreotide SPECT/CT for lymph node staging of non-small-cell lung cancer.

OBJECTIVE: To investigate the potential role of Tc-99m depreotide (Tc-DEPR) in the preoperative lymph node (N) staging of non-small-cell lung cancer (NSCLC). METHODS: Sixty-one patients with NSCLC at the potentially operable stage were enrolled and underwent scintigraphy before surgery (n=56) or mediastinoscopy (n=5). Imaging was performed with a hybrid single photon emission computed tomography/computed tomography (SPECT/CT) system. Depreotide uptake in N stations was evaluated visually and semi-quantitatively and compared to histology. Quantification was carried out in attenuation-corrected SPECT slices. Different sites of normal uptake were used as a reference for comparison with lesional uptake. Receiver operating characteristic analysis was employed to identify the most preferable reference area and the cut-off best discriminating disease-free from disease-involved lymph nodes. RESULTS: With reference to 53 Ν1 hilar and 147 Ν2/Ν3 sampled stations, sensitivity of scintigraphy by visual interpretation was 100 and 94%, specificity 43 and 59% and accuracy 55 and 67%, respectively. No patient was down-staged, but 52% were incorrectly up-staged and 44% were misclassified as inoperable. Compared to scintigraphy, preoperative contrast-enhanced diagnostic CT demonstrated lower sensitivity (36% for hilar and 73% for N2/N3 stations), higher specificity (79 and 75%) and similar accuracy (70 and 75%). Regarding the ultimate N-stage and the prediction of surgical disease, diagnostic CT was wrong in 51 and 34% of cases. Dichotomy of quantitative scintigraphic data by the use of certain N-to-spine ratio cut-offs resulted in a significant increase of specificity (76% for hilar and 89% for N2/N3 stations), while sensitivity remained high (82% in both circumstances) and accuracy for Ν2/Ν3 stations was substantially improved (88%). By this quantitative approach, misclassifications as to the N-stage and patient operability (25 and 16%) were considerably less than that of visual Tc-DEPR and diagnostic CT interpretations. CONCLUSION: Tc-99m depreotide SPECT/CT seems to have a role in the N-staging of NSCLC, mainly because of its high sensitivity and negative predictive value. Quantification of uptake can improve specificity, at a low cost of sensitivity. If F-18 fluoro-deoxyglucose positron emission tomography is not available, this method may be used as a surrogate to conventional staging modalities.