Giant cell arteritis is a form of large vessel vasculitis which can present with nonspecific symptoms, and if left untreated can cause significant morbidity and/or death. Early diagnosis and management are therefore paramount. The use of [18F]FDG PET/CT in the evaluation of giant cell arteritis has increased in recent years, with newer generation PET scanners capturing the historically elusive cranial vessel inflammation in active vasculitis. We present a case of giant cell arteritis which was suspected on conventional imaging modalities, and subsequently evaluated with [18F]FDG PET/CT which revealed marked vascular inflammation involving both cranial and other large vessels.

BACKGROUND: Serum bone turnover markers offer limited insight into metabolic activity at the individual vertebra level in osteoporosis. This study introduces a novel image-derived bone turnover marker for individual vertebrae to address this limitation, utilizing volumetric density-adjusted quantitative bone single-photon emission computed tomography/computed tomography (SPECT/CT) with [99mTc]Tc-DPD. This retrospective study included 177 lumbar vertebrae from 55 postmenopausal South Korean women. The mean standardized uptake value (SUVmean, g/cm3) and volumetric bone mineral density (vBMD, mg/cm3) were determined within a 2-cm³ volume of interest in the trabecular portion of each vertebra using quantitative SPECT and CT. The density-adjusted mean standardized uptake value (dSUVmean) was calculated by dividing the SUVmean by the vBMD and multiplying by 1,000.
RESULTS: SUVmean correlated positively with vBMD (r = 0.60, p < 0.001). Conversely, dSUVmean correlated negatively with vBMD (ρ = -0.66, p < 0.001), highlighting the inverse relationship between bone mass and turnover after density adjustment of SUVmean. Patients with major osteoporotic fractures had lower vBMD (62.5 ± 29.4 vs. 92.3 ± 27.4 mg/cm³, p = 0.001) but higher dSUVmean (100.8 ± 60.7 vs. 62.6 ± 17.5, p = 0.001) compared to those without fractures, reinforcing the association between fracture prevalence, low bone mass, and high bone turnover.
CONCLUSIONS: Volumetric density-adjusted quantitative bone SPECT/CT offers a novel image-derived bone turnover marker for assessing bone turnover in osteoporosis. This method provides a precise assessment of fragility at the individual vertebra level, which may enhance personalized osteoporosis management.

OBJECTIVE: This study aimed to identify a relatively robust SUV for guiding clinical practice through quantitative measurement and comparison of various normalization methods based on the SUV of 99mTc-MDP in the normal spine and pelvis using an integrated SPECT/CT scanner.
METHODS: Between June 2017 and September 2019, a total of 500 oncology patients (mean age, 60.9; men, 66.0%) who underwent bone SPECT/CT scans with 99mTc-MDP were enrolled in this retrospective study. The mean SUV (SUVmean) of 4962 spinal and pelvic bones was calculated based on the patients\' body weight (BW), lean body mass (LBM), bone mineral content (BMC), body surface area (BSA), and body mass index (BMI), defined as SUVbw, SUVlbm, SUVbmc, SUVbsa, and SUVbmi, respectively. The coefficients of variation (CoVs) of the aforementioned parameters were compared, and the correlation and multiple linear regression analyses were used to compare the extent to which these parameters were affected by sex, age, height, weight, BMI, and CT values.
RESULTS: The average SUVs in the normal spine and pelvis displayed a relatively wide variability: 4.573 ± 1.972 for SUVbw, 3.555 ± 1.517 for SUVlbm, 0.163 ± 0.071 for SUVbmc, 0.124 ± 0.052 for SUVbsa, and 1.668 ± 0.732 for SUVbmi. In general, SUVbsa had relatively lowest CoV (42.1%) in all vertebrae and pelvis compared with other SUVs. For correlation analyses, all SUVs displayed weak but significant correlations with age and CT values. For regression analyses, SUVbsa was influenced only by age, BMI, and CT values independently. The effects of these variables on SUVbsa were all smaller than those on conventional SUVbw.
CONCLUSIONS: The SUVs of 99mTc-MDP in normal bone derived from quantitative bone SPECT/CT could serve as a reference for evaluating tumor bone metastasis, but it should be assessed on a site-specific basis. SUVbsa exhibited superior robustness among all the SUV normalization variations, indicating potential clinical applications.

UNASSIGNED: Tissue radiotracer activity measured from positron emission tomography (PET) images is an important biomarker that is clinically utilized for diagnosis, staging, prognostication, and treatment response assessment in patients with cancer and other clinical disorders. Using PET image values to define a normal range of metabolic activity for quantification purposes is challenging due to variations in patient-related factors and technical factors. Although the formulation of standardized uptake value (SUV) has compensated for some of these variabilities, significant non-standardness still persists. We propose an image processing method to substantially mitigate these variabilities.
UNASSIGNED: The standardization method is similar for activity concentration (AC) PET and SUV PET images with some differences and consists of two steps. The calibration step is performed only once for each of AC PET or SUV PET, employs a set of images of normal subjects, and requires a reference object, while the transformation step is executed for each patient image to be standardized. In the calibration step, a standardized scale is determined along with 3 key image intensity landmarks defined on it including the minimum percentile intensity s min , median intensity s m , and high percentile intensity s max . s min and s m are estimated based on image intensities within the body region in the normal calibration image set. The optimal value of the maximum percentile β corresponding to the intensity s max is estimated via an optimization process by using the reference object to optimally separate the highly variable high uptake values from the normal uptake intensities. In the transformation step, the first two landmarks-the minimum percentile intensity p α ( I ) , and the median intensity p m ( I ) -are found for the given image I for the body region, and the high percentile intensity p β ( I ) is determined corresponding to the optimally estimated high percentile value β . Subsequently, intensities of I are mapped to the standard scale piecewise linearly for different segments. We employ three strategies for evaluation and comparison with other standardization methods: (i) comparing coefficient of variation C V O of mean intensity within test objects O across different normal test subjects before and after standardization; (ii) comparing mean absolute difference ( MD O ) of mean intensity within test objects O across different subjects in repeat scans before and after standardization; (iii) comparing C V O of mean intensity across different normal subjects before and after standardization where the scans came from different brands of scanners.
UNASSIGNED: Our data set consisted of 84 FDG-PET/CT scans of the body torso including 38 normal subjects and two repeat-scans of 23 patients. We utilized one of two objects-liver and spleen-as a reference object and the other for testing. The proposed standardization method reduced C V O and MD O by a factor of 3-8 in comparison to other standardization methods and no standardization. Upon standardization by our method, the image intensities (both for AC and SUV) from two different brands of scanners become statistically indistinguishable, while without standardization, they differ significantly and by a factor of 3-9.
UNASSIGNED: The proposed method is automatic, outperforms current standardization methods, and effectively overcomes the residual variation left over in SUV and inter-scanner variations.

In 67Ga-citrate scintigraphy (Ga-S), visual assessment is used by evaluating renal-uptake comparison with liver and spine and is simple and objective. We adopted the standardized uptake value (SUV) for 67Ga-citrate and proposed two quantitative indices, active nephritis volume (ANV) and total nephritis uptake (TNU). This study clarified the utility of new Ga-S-based quantitative indices in nephritis management. Before SUV measurement, the Becquerel calibration factor of 67Ga-citrate was obtained using a phantom experiment. Seventy patients who underwent SPECT/CT imaging were studied. SUV, ANV, and TNU were calculated using a quantitative analysis software for bone SPECT. SUVmean, ANV, and TNU were analyzed using the (1) threshold method (set 40%) and constant-value method for (2) vertebral SUVmax, and (3) vertebral SUVmean. ROC analysis was used to evaluate SUV, ANV, and TNU diagnostic abilities to distinguish nephritis presence and absence as well as interstitial nephritis (IN) and non-IN. The area under the curve (AUC) for nephritis presence or absence had a good value (0.80) for SUVmean (1), ANV (3), and TNU (3). The AUC for differentiation between IN and non-IN groups had a good value (0.80) for SUVmean (1). Thus, the new Ga-S-based quantitative indices were useful to evaluate nephritis and distinguish IN and non-IN.

UNASSIGNED: Positron emission tomography with computed tomography (PET-CT) using fluorine 18-fluorodeoxyglucose (F-18 FDG) is increasingly used to stage patients with locally advanced breast cancer and for assessing treatment response after neoadjuvant chemotherapy (NACT).
UNASSIGNED: The aim of the study was to assess the correlation between PET-CT parameters and pathologic response of breast primary after NACT in breast cancer patients and to devise a grading system called NIMS grading system for response assessment using PET quantitative parameters.
UNASSIGNED: 55 patients who underwent F-18 FDG PET-CT before starting the therapy and again after completion of therapy were identified and included in the study. The clinical data and the histopathologic findings were recorded. All the patients received chemotherapy followed by surgery with axillary lymph node dissection. The PET-CT results were interpreted both qualitatively by visual analysis and quantitatively by estimating maximum Standardized uptake values(SUVmax) and other parameters - SUVmean, SUL, SUVBSA, Metabolic tumor volume (MTV) and Total lesion glycolysis (TLG).
UNASSIGNED: The sensitivity and specificity of F-18 FDG PET-CT to detect the residual disease after neoadjuvant chemotherapy was 75.6% & 92.8% respectively. Differences between complete response and residual disease were significant for ΔSUVmax(p=0.005), ΔSUVmean(p=0.006), ΔSUL (0.005) and ΔSUVBSA(0.004), while ΔMTV and ΔTLG were not significantly different between the two groups. The new NIMS grading system included scoring of ΔSUVmax, ΔSUVBSA, ΔTLG and ΔMTV on scale of 1 to 4 and correlated well with PERCIST criteria.
UNASSIGNED: F-18 FDG PET-CT had a good accuracy in the detection of residual disease after completion of NACT. Pre chemotherapy PET-CT is not adequate to predict the response of primary tumour to chemotherapy. However, changes in the values of various PET-CT parameters are a sensitive tool to assess the response to chemotherapy. The new grading system is easy to use and showed good correlation to PERCIST.

OBJECTIVE: The ability of [123I]metaiodobenzylguanidine (MIBG) sympathetic nerve imaging with three-dimensional (3D) quantitation to clinically diagnose neurological disorders has not been evaluated. This study compared absolute heart counts calculated as mean standardized uptake values (SUVmean) using conventional planar imaging and assessed the contribution of [123I]MIBG single-photon emission computed tomography (SPECT)-CT to the diagnosis of neurological diseases.
METHODS: Seventy-two patients with neurological diseases were consecutively assessed using early and delayed [123I]MIBG SPECT-CT and planar imaging. Left ventricles were manually segmented in early and delayed SPECT-CT images, then the SUVmean and washout rates (WRs) were calculated. Heart-to-mediastinum ratios (HMRs) and WRs on planar images were conventionally computed. We investigated correlations between planar HMRs and SPECT-CT SUVmeans and between WRs obtained from planar and SPECT-CT images. The cutoff for SPECT-CT WRs defined by linear regression and that of normal planar WRs derived from a database were compared with neurological diagnoses of the patients. We assigned the patients to groups according to clinical diagnoses as controls (n = 6), multiple system atrophy (MSA, n = 7), progressive supranuclear palsy (PSP, n = 17), and Parkinson\'s disease or dementia with Lewy bodies (PD/DLB, n = 19), then compared SPECT-CT and planar image parameters.
RESULTS: We found significant correlations between SPECT-CT SUVmean and planar HMR on early and delayed images (R2 = 0.69 and 0.82, p < 0.0001) and between SPECT-CT and planar WRs (R2 = 0.79, p < 0.0001). A threshold of 31% for SPECT-CT WR based on linear regression resulted in agreement between planar and SPECT-CT WR in 67 (93.1%) of 72 patients. Compared with controls, early and delayed SUVmean in patients with PSP and MSA tended more towards significance than planar HMR. This trend was similar for SPECT-CT WRs in patients with PSP.
CONCLUSIONS: Absolute heart counts and SUVmean determined using [123I]MIBG SPECT-CT correlated with findings of conventional planar images in patients with neurological diseases. Three-dimensional quantitation with [123I]MIBG SPECT-CT imaging might differentiate patients with PSP and MSA from controls.

BACKGROUND: Research on the relationship between neuron-specific enolase (NSE) levels and normal organs, particularly the central nervous system, in small cell lung cancer is limited. Therefore, this study aimed to investigate the relationship between positron emission tomography-computed tomography (PET-CT) accumulation at hypothalamic/pituitary regions, tumor activity, and NSE level in limited-stage small cell lung cancer. We retrospectively analyzed patients who were diagnosed with limited-stage small cell lung cancer at Tokyo Medical University Hospital between July 1, 2019, and May 31, 2023, and were treated with chemoradiotherapy or radiotherapy. Leukocytes, erythrocytes, hemoglobin, platelets, total protein, albumin, NSE, and carcinoembryonic antigen were measured in blood samples obtained before treatment initiation. The maximum standardized uptake value (SUVmax), volume, and total lesion glycolysis (TLG) of each hypothalamic /pituitary region, primary tumor, and lymph node metastases were extracted from PET-CT images. The total tumor volume (primary tumor volume plus lymph node metastases volume) and total TLG (primary tumor TLG plus lymph node metastases TLG) were calculated.
RESULTS: This study included 19 patients (mean age, 70.1 ± 8.8 years; 13 men and 6 women); the pathology in all patients was small cell lung cancer. Patients were classified into two groups according to the NSE reference value (16.3 ng/mL): six patients having NSE level below the reference value and 13 having NSE level above the reference value. The SUVmax in the hypothalamic/pituitary region was 2.95 in the NSE < 16.3 ng/mL group and 4.10 in the NSE > 16.3 ng/mL group, with a statistically significant difference (p = 0.03). The total tumor volume was 17.8 mL in the NSE < 16.3 ng/mL group and 98.9 mL in the NSE > 16.3 ng/mL group, with a statistically significant difference (p < 0.01). A correlation coefficient of r = 0.458 (p = 0.0486) was observed between SUVmax in the hypothalamus/pituitary and NSE level. A correlation coefficient of r = 0.647 (p < 0.01) was also observed between total tumor volume and NSE level. Finally, a correlation coefficient of r = 0.53 (p = 0.01) was observed between hypothalamic/pituitary TLG and primary tumor TLG.
CONCLUSIONS: The findings demonstrated a correlation between hypothalamic/pituitary activity and tumor activity, suggesting the prognostic significance of NSE.

UNASSIGNED: Controversy surrounds the efficacy of adjuvant chemotherapy (ACT) in the treatment of stage I lung adenocarcinoma (LUAD). The objective of this study was to examine the impact of the maximum standardized uptake value (SUVmax) as measured by 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) on the efficacy of ACT in patients diagnosed with stage I LUAD.
UNASSIGNED: We scrutinized the medical records of 928 consecutive patients who underwent complete surgical resection for pathological stage I LUAD at our institution. The ideal cut-off value for primary tumor SUVmax in terms of disease-free survival (DFS) and overall survival (OS) was determined using the X-tile software. The Kaplan-Meier method and Cox regression analysis were used for survival analysis.
UNASSIGNED: Based on the SUVmax algorithm, the ideal cutoff values were determined to be 4.9 for DFS and 5.0 for OS. We selected 5.0 as the threshold because OS is the more widely accepted predictive endpoint. In a multivariate Cox regression analysis, SUVmax ≥ 5.0, problematic IB stage, and sublobectomy were identified as independent risk factors for poor DFS and OS. It is noteworthy that patients who were administered ACT had significantly longer DFS and OS than what was observed in the subgroup of patients with pathological stage IB LUAD and SUVmax ≥ 5.0 (p < 0.035 and p ≤ 0.046, respectively). However, there was no observed survival advantage for patients in stages IA or IB who had an SUVmax < 5.0.
UNASSIGNED: The preoperative SUVmax of tumors served as an indicator of the impact of ACT in the context of completely resected pathological stage I LUAD. Notably, patients within the Stage IB category exhibiting elevated SUVmax levels emerged as a subgroup experiencing substantial benefits from postoperative ACT.

OBJECTIVE: Although lung cancer screening trials have showed the efficacy of computed tomography to decrease mortality compared with chest radiography, the two are widely taken as different kinds of clinical practices. Artificial intelligence can improve outcomes by detecting lung tumors in chest radiographs. Currently, artificial intelligence is used as an aid for physicians to interpret radiograms, but with the future evolution of artificial intelligence, it may become a modality that replaces physicians. Therefore, in this study, we investigated the current situation of lung cancer diagnosis by artificial intelligence.
METHODS: In total, we recruited 174 consecutive patients with malignant pulmonary tumors who underwent surgery after chest radiography that was checked by artificial intelligence before surgery. Artificial intelligence diagnoses were performed using the medical image analysis software EIRL X-ray Lung Nodule version 1.12, (LPIXEL Inc., Tokyo, Japan).
RESULTS: The artificial intelligence determined pulmonary tumors in 90 cases (51.7% for all patients and 57.7% excluding 18 patients with adenocarcinoma in situ). There was no significant difference in the detection rate by the artificial intelligence among histological types. All eighteen cases of adenocarcinoma in situ were not detected by either the artificial intelligence or the physicians. In a univariate analysis, the artificial intelligence could detect cases with larger histopathological tumor size (p < 0.0001), larger histopathological invasion size (p < 0.0001), and higher maximum standardized uptake values of positron emission tomography-computed tomography (p < 0.0001). In a multivariate analysis, detection by AI was significantly higher in cases with a large histopathological invasive size (p = 0.006). In 156 cases excluding adenocarcinoma in situ, we examined the rate of artificial intelligence detection based on the tumor site. Tumors in the lower lung field area were less frequently detected (p = 0.019) and tumors in the middle lung field area were more frequently detected (p = 0.014) compared with tumors in the upper lung field area.
CONCLUSIONS: Our study showed that using artificial intelligence, the diagnosis of tumor-associated findings and the diagnosis of areas that overlap with anatomical structures is not satisfactory. While the current standing of artificial intelligence diagnostics is to assist physicians in making diagnoses, there is the possibility that artificial intelligence can substitute for humans in the future. However, artificial intelligence should be used in the future as an enhancement, to aid physicians in the role of a radiologist in the workflow.