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We evaluated the predictive value of dynamic blood flow scintigraphy with 99m Tc-HDP (hydroxymethylene diphosphonate) for therapeutic response in patients with Raynaud’s phenomenon (RP). Eighty patients who underwent dynamic blood flow scintigraphy using the one-hand chilling method were enrolled. We analyzed the quantitative variables as the ratio of chilled fingers to ambient fingers (CA finger ), that of the chilled hand to ambient hand (CA hand ), and that of chilled fingers to ambient palm (FPR) (CA FPR ) at 15 and 30 s after 99m Tc-HDP bolus injection. Total cumulative radioactivity counts for 180 s were obtained. We evaluated the clinical utility of these quantitative parameters with other clinical variables, including RP severity, therapeutic compliance, types of RP, and scintigraphic interpretation of findings in patients with RP. Fifty-two patients showed poor therapeutic response. There were significant differences between good- and poor-therapeutic responder groups in RP intensity (p = 0.003), CA finger15s (p = 0.008), CA finger30s (p = 0.002), CA finger180s (p = 0.011), CA hand15s (p = 0.008), CA hand30s (p = 0.007), CA hand180s (p = 0.017), CA FPR30s (p = 0.004), and CA FPR180s (p = 0.002). After multivariate logistic regression analysis, only CA finger30s (p = 0.002) had an independent predictive value of the therapeutic response. 99m Tc-HDP dynamic blood flow scintigraphy could be helpful in predicting the therapeutic response in patients with RP.

Warthin’s tumor is a benign salivary gland neoplasm that can exhibit intense FDG uptake, potentially mimicking malignant lesions on oncologic imaging. We report a case of a 78-year-old man undergoing staging for suspected lung cancer, in whom a hypermetabolic lesion was incidentally detected in the left parotid gland on [18F]FDG PET/CT. Correlation with prior salivary scintigraphy, MRI, and CT supported the likelihood of Warthin’s tumor, which was subsequently confirmed by fine-needle aspiration cytology. This case illustrates how multimodality imaging can provide complementary diagnostic information that helps characterize the parotid lesion, but not replace cytologic confirmation. Recognition of characteristic imaging features, an understanding of each modality’s diagnostic strengths and limitations, and cytologic confirmation when indicated are essential to avoid misinterpretation and optimize patient management.

Toxocariasis is an uncommon cause of multiple cavitary lung lesions and an ill-defined liver lesion. We herein report a patient with lung and liver toxocariasis, which mimicked metastatic lesions of colon cancer on 18F-FDG PET–CT and chest and abdominal CT performed for cancer staging after diagnosis of colon cancer. The patient was diagnosed with lung and liver toxocariasis by a positive enzyme-linked immunosorbent assay. Lung toxocariasis may occur as multiple cavitary lung lesions, and liver toxocariasis may appear as a solitary ill-defined nodule, which may be misdiagnosed as metastatic tumors. Clinicians should consider toxocariasis when multiple cavitary lung lesions and a solitary ill-defined focal liver lesion are detected, especially in a patient with cancer.

We describe a case of 18F-FDG PET/CT detecting septic pulmonary emboli in a patient with Staphylococcus aureus catheter-related bloodstream infection (CRBSI). The patient, who had an implantable venous access port for chemotherapy, underwent 18F-FDG PET/CT to diagnose unsuspected infectious foci. The PET/CT examination made it possible to offer a suggestive diagnosis and yielded metastatic infectious foci.

Objectives We aimed to find the best machine learning (ML) model using 18 F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) for evaluating metastatic mediastinal lymph nodes (MedLNs) in non-small cell lung cancer, and compare the diagnostic results with those of nuclear medicine physicians. Methods A total of 1329 MedLNs were reviewed. Boosted decision tree, logistic regression, support vector machine, neural network, and decision forest models were compared. The diagnostic performance of the best ML model was compared with that of physicians. The ML method was divided into ML with quantitative variables only (MLq) and adding clinical information (MLc). We performed an analysis based on the 18 F-FDG-avidity of the MedLNs. Results The boosted decision tree model obtained higher sensitivity and negative predictive values but lower specificity and positive predictive values than the physicians. There was no significant difference between the accuracy of the physicians and MLq (79.8% vs. 76.8%, p = 0.067). The accuracy of MLc was significantly higher than that of the physicians (81.0% vs. 76.8%, p = 0.009). In MedLNs with low 18 F-FDG-avidity, ML had significantly higher accuracy than the physicians (70.0% vs. 63.3%, p = 0.018). Conclusion Although there was no significant difference in accuracy between the MLq and physicians, the diagnostic performance of MLc was better than that of MLq or of the physicians. The ML method appeared to be useful for evaluating low metabolic MedLNs. Therefore, adding clinical information to the quantitative variables from 18 F-FDG PET/CT can improve the diagnostic results of ML. Key Points • Machine learning using two-class boosted decision tree model revealed the highest value of area under curve, and it showed higher sensitivity and negative predictive values but lower specificity and positive predictive values than nuclear medicine physicians. • The diagnostic results from machine learning method after adding clinical information to the quantitative variables improved accuracy significantly than nuclear medicine physicians. • Machine learning could improve the diagnostic significance of metastatic mediastinal lymph nodes, especially in mediastinal lymph nodes with low 18F-FDG-avidity.

This is a case report of a gluteal hematoma detected on 99mTc-methylene diphosphonate (MDP) whole-body bone scan in a 77-year-old male who had experienced a road traffic accident.This is a case report of a gluteal hematoma detected on 99mTc-methylene diphosphonate (MDP) whole-body bone scan in a 77-year-old male who had experienced a road traffic accident.

We report a case of dialysis-related amyloid arthropathy in a patient with end-stage renal disease. It presented in our patient as moderately increased FDG uptake in the amyloid deposition in the periarticular tissues and eroding into adjacent bones.

Background/Objectives: Quantitative analysis of amyloid PET imaging plays a crucial role in diagnosing Alzheimer’s disease (AD), particularly in cases where visual interpretation is equivocal. Multiple commercial software tools are available for this purpose, yet differences in their quantification and diagnostic performance remain understudied, especially for Neurophet SCALE PET. Methods: We retrospectively analyzed 18F-florbetaben PET/CT scans from 129 patients with cognitive impairment, comprising 39 patients with AD and 90 with non-AD diagnoses, using three software tools: MIMneuro, CortexID Suite, and Neurophet SCALE PET. Standardized uptake value ratios (SUVRs) were obtained for six brain regions known for amyloid accumulation. Diagnostic accuracy was evaluated using ROC curve analysis, while inter-software correlations and reliability were assessed via Pearson correlation coefficients and intraclass correlation coefficients (ICC). Results: All three software programs significantly distinguished AD from non-AD patients in most brain regions. MIMneuro and Neurophet SCALE PET demonstrated the highest diagnostic performance, with MIMneuro achieving an AUC of 1.000 in the anterior cingulate gyrus. While MIMneuro and Neurophet SCALE PET showed moderate-to-strong SUVR correlations (r = 0.715–0.865), CortexID Suite showed limited correlation with the other tools. Inter-software reliability was moderate only in selected regions (ICC ≈ 0.5), indicating potential variability in SUVR measurements across platforms. Conclusions: MIMneuro, CortexID Suite, and Neurophet SCALE PET are effective for the semi-quantitative analysis of amyloid PET and can aid in the diagnosis of AD. However, clinicians should be cautious when interpreting SUVRs across different software tools due to limited inter-software consistency. Standardization efforts or consistent use of a single platform are recommended to avoid diagnostic discrepancies.

Metastatic calcification relates to abnormal calcification resulting from hypercalcemia and can affect soft tissues, skeletal muscle, myocardium, lungs, stomach, kidneys, and blood vessels. We describe a case of metastatic pulmonary calcification in a 71-year-old male, images with 18F-fluorodeoxyglucose (FDG) PET/CT and 99mTc- methylene diphosphonate (MDP) bone scan.

Gorlin–Goltz syndrome (basal cell nevus syndromes) is an uncommon, autosomal dominant inherited disorder characterized by developing basal cell carcinomas from a young age. Other distinct clinical features include keratocystic odontogenic tumors, dyskeratotic palmar and plantar pitting, and skeletal abnormalities. Clinicopathological findings of the syndrome are very diverse, and many symptoms manifest during a certain period of life. We present the compelling whole-body bone scan and 18F-FDG PET/CT findings in a 32-year-old man with odontogenic keratocyst, early-onset basal cell carcinoma, multiple ectopic calcifications in extremities, calcified falx cerebri, spinal scoliosis, macrocephaly, and ocular hypertelorism.