scholarly journals A Better Standard-Uptake-Value Body Habitus Normalizer for Fluorodeoxyglucose in Humans

2021 ◽  
Author(s):  
Bradley Jay Beattie ◽  
Tim J Akhurst ◽  
Finn Augensen ◽  
John L Humm
Keyword(s):  
Pediatric Patients ◽  
Standardized Uptake Value ◽  
Normal Liver ◽  
Standard Uptake Value ◽  
Patient Specific ◽  
Training Set ◽  
Test Set ◽  
Body Habitus ◽  
Fdg Uptake ◽  
Pet Tracer

Abstract Purpose To devise a new body-habitus normalizer to be used in the calculation of a standardized uptake value (SUV) that is specific to the PET tracer 18F-FDG. Methods After exclusions for type and extent of cancer and timing of the scan, a cohort of 481 patients was selected for analysis of 18F-FDG uptake into “normal” tissues (presumed to be unaffected by their disease). Among these, 65 patients had only brain concentrations measured and the remaining 416 were randomly divided into an 86-patient test set and a 330-patient training set. Within the test set, normal liver, spleen and blood measures were made. In the training set, only normal liver concentrations were measured. Using data from the training set, a simple polynomial function of height and weight was selected (following a subjective procedure) to predict each patient’s mean liver percent injected dose per milliliter. This function, when used to normalize measured %ID/ml concentrations, defines a new SUV metric (SUVfdg) which we compared to SUV metrics normalized by body weight (SUVbw), lean-body mass (SUVlbm) and body surface-area (SUVbsa) in a five-fold cross-validation. SUVfdg was also tested on the independent holdout sets utilizing the measurements of normal liver, blood, spleen and brain. Results For patients of all sizes including pediatric patients, the normal range of liver 18F-FDG uptake concentration at 60 minutes post injection in units of SUVfdg is 1.0 ± 0.16. Liver, blood and spleen SUVfdg in all comparisons had lower coefficients of variation (CoV) compared to SUVbw SUVlbm and SUVbsa. Blood had a mean SUVfdg value of 0.8 ± 0.11 and showed no correlation with age, height or weight. Brain SUVfdg measures were significantly higher (P < 0.01) in pediatric patients (4.7 ± 0.9) compared to adults (3.1 ± 0.6). Conclusion A new SUV metric, SUVfdg, is proposed. It is hoped that SUVfdg will prove to be better at classifying tumor lesions and other tissues compared to SUV metrics in current use and may be useful in predicting patient specific radiation dose. Other tracers may benefit from similarly tracer-specific body habitus normalizers.

scholarly journals A better Standard-Uptake-Value Body Habitus Normalizer for Fluorodeoxyglucose in Humans

2021 ◽  
Author(s):  
Bradley Jay Beattie ◽  
Tim J Akhurst ◽  
Finn Augensen ◽  
John L Humm
Keyword(s):  
Pediatric Patients ◽  
Standardized Uptake Value ◽  
Normal Liver ◽  
Standard Uptake Value ◽  
Patient Specific ◽  
Training Set ◽  
Test Set ◽  
Body Habitus ◽  
Fdg Uptake ◽  
Pet Tracer

Abstract PurposeTo devise a new body-habitus normalizer to be used in the calculation of a standardized uptake value (SUV) that is specific to the PET tracer 18 F-FDG. MethodsAfter exclusions for type and extent of cancer and timing of the scan, a cohort of 481 patients was selected for analysis of 18 F-FDG uptake into “normal” tissues (presumed to be unaffected by their disease). Among these, 65 patients had only brain concentrations measured and the remaining 416 were randomly divided into an 86-patient test set and a 330-patient training set. Within the test set, normal liver, spleen and blood measures were made. In the training set, only normal liver concentrations were measured. Using data from the training set, a simple polynomial function of height and weight was selected (following a subjective procedure) to predict each patient’s mean liver percent injected dose per milliliter. This function, when used to normalize measured %ID/ml concentrations, defines a new SUV metric (SUV fdg ) which we compared to SUV metrics normalized by body weight (SUV bw ), lean-body mass (SUV lbm ) and body surface-area (SUV bsa ) in a five-fold cross-validation. SUV fdg was also tested on the independent holdout sets utilizing the measurements of normal liver, blood, spleen and brain. ResultsFor patients of all sizes including pediatric patients, the normal range of liver 18 F-FDG uptake concentration at 60 minutes post injection in units of SUV fdg is 1.0 ± 0.16. Liver, blood and spleen SUV fdg in all comparisons had lower coefficients of variation (CoV) compared to SUV bw SUV lbm and SUV bsa . Blood had a mean SUV fdg value of 0.8 ± 0.11 and showed no correlation with age, height or weight. Brain SUV fdg measures were significantly higher (P<0.01) in pediatric patients (4.7 ± 0.9) compared to adults (3.1 ± 0.6). ConclusionA new SUV metric, SUV fdg , is proposed. It is hoped that SUV fdg will prove to be better at classifying tumor lesions and other tissues compared to SUV metrics in current use and may be useful in predicting patient specific radiation dose. Other tracers may benefit from similarly tracer-specific body habitus normalizers.

Limitations of dual time point FDG-PET imaging in the evaluation of focal abdominal lesions

2004 ◽  
Vol 43 (05) ◽  
pp. 143-149 ◽  
Author(s):  
N. Hamscho ◽  
C. Menzel ◽  
L. Neuss ◽  
A. F. Kovács ◽  
F. Grünwald ◽  
...  
Keyword(s):  
Pet Imaging ◽  
Malignant Tumors ◽  
Standardized Uptake Value ◽  
Delayed Imaging ◽  
Ct Guided ◽  
Fdg Uptake ◽  
Diagnostic Potential ◽  
Dual Time Point ◽  
Abdominal Lesions ◽  
Time Point

Summary:Aim: For the evaluation of the diagnostic potential of dual time point FDG positron emission tomography (PET) in patients with suspicious focal abdominal up-take, dual time point PET imaging was compared with clinical findings. Patients, methods: In a prospective study, 56 patients exhibiting a solitary suspicious, intense abdominal FDG uptake, underwent dual time point PET imaging for staging or restaging of different malignant tumors, maximal standardized uptake value (SUVmax) measurements included. The first acquisition was started 64.8 ± 19.5, the second 211.3 ± 52.5 min after FDG injection. The final diagnosis based on CT or MRT imaging and a follow-up period of 12.6 ± 2.8 months. Additionally, colonoscopy was done in 6 patients. In another 6 patients histopathology was obtained from CT guided biopsy. Results: Malignant focal abdominal lesions with a SUVmax <2.5 (n = 4) showed an uptake increase of ≥30%. In the remaining malignant cases with an uptake of ≥2.5 (n = 11), up-take increased in 64% and decreased in 36%. Malignant lesions showing FDG uptake decrease (n = 4) had an initial SUVmax value ≥2.5 and remained with a SUVmax ≥2.5 in the second imaging. In benign lesions with an initial SUVmax ≥2.5 (n = 31), the uptake increased in 17 patients (55%) and decreased in 14 patients (45%). All lesions which changed configuration (33%) were confirmed as benign (n = 5). Conclusion: Using dual time point PET abdominal lesions show a very hetergenous uptake pattern regardless of their dignity. Malignancy can only be reliably excluded in lesions which change their configuration and in lesions with an initial SUVmax value <2.5 combined with an SUV decrease in the delayed imaging. Particularly abdominal lesions which show an initial SUVmax ≥2.5 combined with a SUV increase in the delayed imaging are suspicious for malignancy and need further clarification.

PREDIKSI KUALITAS AIR SUNGAI CILIWUNG DENGAN MENGGUNAKAN ALGORITMA POHON KEPUTUSAN

2021 ◽  
Vol 12 (2) ◽  
Author(s):  
Mohammad Haekal ◽  
Henki Bayu Seta ◽  
Mayanda Mega Santoni
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Cross Validation ◽  
Online Monitoring ◽  
Training Set ◽  
Microsoft Excel ◽  
Test Set

Untuk memprediksi kualitas air sungai Ciliwung, telah dilakukan pengolahan data-data hasil pemantauan secara Online Monitoring dengan menggunakan Metode Data Mining. Pada metode ini, pertama-tama data-data hasil pemantauan dibuat dalam bentuk tabel Microsoft Excel, kemudian diolah menjadi bentuk Pohon Keputusan yang disebut Algoritma Pohon Keputusan (Decision Tree) mengunakan aplikasi WEKA. Metode Pohon Keputusan dipilih karena lebih sederhana, mudah dipahami dan mempunyai tingkat akurasi yang sangat tinggi. Jumlah data hasil pemantauan kualitas air sungai Ciliwung yang diolah sebanyak 5.476 data. Hasil klarifikasi dengan Pohon Keputusan, dari 5.476 data ini diperoleh jumlah data yang mengindikasikan sungai Ciliwung Tidak Tercemar sebanyak 1.059 data atau sebesar 19,3242%, dan yang mengindikasikan Tercemar sebanyak 4.417 data atau 80,6758%. Selanjutnya data-data hasil pemantauan ini dievaluasi menggunakan 4 Opsi Tes (Test Option) yaitu dengan Use Training Set, Supplied Test Set, Cross-Validation folds 10, dan Percentage Split 66%. Hasil evaluasi dengan 4 opsi tes yang digunakan ini, semuanya menunjukkan tingkat akurasi yang sangat tinggi, yaitu diatas 99%. Dari data-data hasil peneltian ini dapat diprediksi bahwa sungai Ciliwung terindikasi sebagai sungai tercemar bila mereferensi kepada Peraturan Pemerintah Republik Indonesia nomor 82 tahun 2001 dan diketahui pula bahwa penggunaan aplikasi WEKA dengan Algoritma Pohon Keputusan untuk mengolah data-data hasil pemantauan dengan mengambil tiga parameter (pH, DO dan Nitrat) adalah sangat akuran dan tepat. Kata Kunci : Kualitas air sungai, Data Mining, Algoritma Pohon Keputusan, Aplikasi WEKA.

scholarly journals QSPR modelling of the octanol/water partition coefficient of organometallic substances by optimal SMILES-based descriptors

2009 ◽  
Vol 7 (4) ◽  
pp. 846-856 ◽  
Author(s):  
Andrey Toropov ◽  
Alla Toropova ◽  
Emilio Benfenati
Keyword(s):  
Partition Coefficient ◽  
Organometallic Compounds ◽  
Applicability Domain ◽  
Training Set ◽  
Input Line ◽  
Test Set ◽  
Water Partition Coefficient ◽  
Definition Of

AbstractUsually, QSPR is not used to model organometallic compounds. We have modeled the octanol/water partition coefficient for organometallic compounds of Na, K, Ca, Cu, Fe, Zn, Ni, As, and Hg by optimal descriptors calculated with simplified molecular input line entry system (SMILES) notations. The best model is characterized by the following statistics: n=54, r2=0.9807, s=0.677, F=2636 (training set); n=26, r2=0.9693, s=0.969, F=759 (test set). Empirical criteria for the definition of the applicability domain for these models are discussed.

scholarly journals Prognostic significance of bone marrow FDG uptake in patients with gynecological cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kotaro Shimura ◽  
Seiji Mabuchi ◽  
Naoko Komura ◽  
Eriko Yokoi ◽  
Katsumi Kozasa ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Bone Marrow ◽  
Poor Prognosis ◽  
Gynecological Cancer ◽  
Prognostic Significance ◽  
Standardized Uptake Value ◽  
Suppressor Cells ◽  
Underlying Mechanism ◽  
Fdg Uptake

AbstractWe investigated the prognostic significance and the underlying mechanism of increased bone marrow (BM) 2-(18F) fluoro-2-deoxy-D-glucose as a tracer (FDG)-uptake in patients with gynecological cancer. A list of patients diagnosed with cervical, endometrial, and ovarian cancer from January 2008 to December 2014 were identified. Then, through chart reviews, 559 patients who underwent staging by FDG-positron emission tomography (PET)/computed tomography (CT) and subsequent surgical resection were identified, and their clinical data were reviewed retrospectively. BM FDG-uptake was evaluated using maximum standardized uptake value (SUVmax) and BM-to-aorta uptake ratio (BAR). As a result, we have found that increased BAR was observed in 20 (8.7%), 21 (13.0%), 21 (12.6%) of cervical, endometrial, and ovarian cancer, respectively, and was associated with significantly shorter survival. Increased BAR was also closely associated with increased granulopoiesis. In vitro and in vivo experiments revealed that tumor-derived granulocyte colony-stimulating factor (G-CSF) was involved in the underlying causative mechanism of increased BM FDG-uptake, and that immune suppression mediated by G-CSF-induced myeloid-derived suppressor cells (MDSCs) is responsible for the poor prognosis of this type of cancer. In conclusion, increased BM FDG-uptake, as represented by increased BAR, is an indicator of poor prognosis in patients with gynecological cancer.

scholarly journals Feature-Weighted Sampling for Proper Evaluation of Classification Models

2021 ◽  
Vol 11 (5) ◽  
pp. 2039
Author(s):  
Hyunseok Shin ◽  
Sejong Oh
Keyword(s):  
Random Sampling ◽  
Sampling Method ◽  
Classification Model ◽  
Training Set ◽  
Test Set ◽  
Feature Importance ◽  
Proper Training ◽  
Machine Learning Applications ◽  
Test Sets ◽  
The Given

In machine learning applications, classification schemes have been widely used for prediction tasks. Typically, to develop a prediction model, the given dataset is divided into training and test sets; the training set is used to build the model and the test set is used to evaluate the model. Furthermore, random sampling is traditionally used to divide datasets. The problem, however, is that the performance of the model is evaluated differently depending on how we divide the training and test sets. Therefore, in this study, we proposed an improved sampling method for the accurate evaluation of a classification model. We first generated numerous candidate cases of train/test sets using the R-value-based sampling method. We evaluated the similarity of distributions of the candidate cases with the whole dataset, and the case with the smallest distribution–difference was selected as the final train/test set. Histograms and feature importance were used to evaluate the similarity of distributions. The proposed method produces more proper training and test sets than previous sampling methods, including random and non-random sampling.

scholarly journals Multiple PET tracers for use in the classification of gliomas according to the 2016 WHO criteria

2020 ◽  
Author(s):  
Keisuke Miyake ◽  
Kenta Suzuki ◽  
Tomoya B Ogawa ◽  
Daisuke Ogawa ◽  
Tetsuhiro Hatakeyama ◽  
...  
Keyword(s):  
Who Classification ◽  
Standardized Uptake Value ◽  
Metabolic Tumor Volume ◽  
Who Criteria ◽  
Pet Tracers ◽  
Pet Tracer ◽  
Positron Emission ◽  
18F Fdg ◽  
Classification Of Gliomas

Abstract Background The molecular diagnosis of gliomas such as isocitrate dehydrogenase (IDH) status (wild-type [wt] or mutation [mut]) is especially important in the 2016 WHO classification. Positron emission tomography (PET) has afforded molecular and metabolic diagnostic imaging. The present study aimed to define the interrelationship between the 2016 WHO classification of gliomas and the integrated data from PET images using multiple tracers, including 18F-fluorodeoxyglucose ( 18F-FDG), 11C-methionine ( 11C-MET), 18F-fluorothymidine ( 18F-FLT), and 18F-fluoromisonidazole ( 18F-FMISO). Methods This retrospective, single-center study comprised 113 patients with newly diagnosed glioma based on the 2016 WHO criteria. Patients were divided into four glioma subtypes (Mut, Codel, Wt, and glioblastoma multiforme [GBM]). Tumor standardized uptake value (SUV) divided by mean normal cortical SUV (tumor-normal tissue ratio [TNR]) was calculated for 18F-FDG, 11C-MET, and 18F-FLT. Tumor-blood SUV ratio (TBR) was calculated for 18F-FMISO. To assess the diagnostic accuracy of PET tracers in distinguishing glioma subtypes, a comparative analysis of TNRs and TBR as well as the metabolic tumor volume (MTV) were calculated by Scheffe’s multiple comparison procedure for each PET tracer following the Kruskal–Wallis test. Results The differences in mean 18F-FLT TNR and 18F-FMISO TBR were significant between GBM and other glioma subtypes (p &lt; 0.001). Regarding the comparison between Gd-T1WI volumes and 18F-FLT MTVs or 18F-FMISO MTVs, we identified significant differences between Wt and Mut or Codel (p &lt; 0.01). Conclusion Combined administration of four PET tracers might aid in the preoperative differential diagnosis of gliomas according to the 2016 WHO criteria.

scholarly journals Quantitative, Dynamic 18F-FDG PET/CT in Monitoring of Smoldering Myeloma: A Case Report

Diagnostics ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 649
Author(s):  
Christos Sachpekidis ◽  
Matthias Türk ◽  
Antonia Dimitrakopoulou-Strauss
Keyword(s):  
Bone Marrow ◽  
Plasma Cells ◽  
Autologous Transplantation ◽  
Standardized Uptake Value ◽  
Focal Lesions ◽  
Fdg Uptake ◽  
Pet Ct ◽  
18F Fdg ◽  
Smoldering Myeloma

We report on a 52-year-old patient with an initial diagnosis of smoldering myeloma (SMM), who was monitored by means of dynamic and static positron emission tomography/computed tomography (PET/CT) with the radiotracer 1⁸F-fluorodeoxyglucose (18F-FDG). Baseline PET/CT revealed no pathological signs. Six months later, a transition to symptomatic, multiple myeloma (MM) was diagnosed. The transition was not accompanied by focal, hypermetabolic lesions on PET/CT. However, a diffusely increased 18F-FDG uptake in the bone marrow, accompanied by a marked increase of semi-quantitative (standardized uptake value, SUV) and quantitative, pharmacokinetic 18F-FDG parameters, was demonstrated. After successful treatment, including tandem autologous transplantation, the diffuse uptake in the bone marrow as well as the semi-quantitative and quantitative parameters showed a marked remission. This response was also confirmed by the clinical follow-up of the patient. These findings suggest that in MM a diffuse 18F-FDG uptake in the bone marrow may indeed reflect an actual bone marrow infiltration by plasma cells. Moreover, SUV values and kinetic parameters, not only from myeloma lesions but also from random bone marrow samples, may be used for MM monitoring. This could be particularly helpful in the follow-up of myeloma patients negative for 18F-FDG-avid focal lesions.

scholarly journals Weakly supervised deep learning for determining the prognostic value of 18F-FDG PET/CT in extranodal natural killer/T cell lymphoma, nasal type

2021 ◽  
Author(s):  
Rui Guo ◽  
Xiaobin Hu ◽  
Haoming Song ◽  
Pengpeng Xu ◽  
Haoping Xu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Fdg Pet ◽  
Cell Lymphoma ◽  
Training Set ◽  
Test Set ◽  
Natural Killer T Cell ◽  
Pet Ct ◽  
Weakly Supervised ◽  
Fdg Pet Ct ◽  
Killer T Cell

Abstract Purpose To develop a weakly supervised deep learning (WSDL) method that could utilize incomplete/missing survival data to predict the prognosis of extranodal natural killer/T cell lymphoma, nasal type (ENKTL) based on pretreatment 18F-FDG PET/CT results. Methods One hundred and sixty-seven patients with ENKTL who underwent pretreatment 18F-FDG PET/CT were retrospectively collected. Eighty-four patients were followed up for at least 2 years (training set = 64, test set = 20). A WSDL method was developed to enable the integration of the remaining 83 patients with incomplete/missing follow-up information in the training set. To test generalization, these data were derived from three types of scanners. Prediction similarity index (PSI) was derived from deep learning features of images. Its discriminative ability was calculated and compared with that of a conventional deep learning (CDL) method. Univariate and multivariate analyses helped explore the significance of PSI and clinical features. Results PSI achieved area under the curve scores of 0.9858 and 0.9946 (training set) and 0.8750 and 0.7344 (test set) in the prediction of progression-free survival (PFS) with the WSDL and CDL methods, respectively. PSI threshold of 1.0 could significantly differentiate the prognosis. In the test set, WSDL and CDL achieved prediction sensitivity, specificity, and accuracy of 87.50% and 62.50%, 83.33% and 83.33%, and 85.00% and 75.00%, respectively. Multivariate analysis confirmed PSI to be an independent significant predictor of PFS in both the methods. Conclusion The WSDL-based framework was more effective for extracting 18F-FDG PET/CT features and predicting the prognosis of ENKTL than the CDL method.

scholarly journals Pulmonary Findings of [18F]FDG PET/CT Images on Asymptomatic COVID-19 Patients

Pathogens ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 839
Author(s):  
Tzu-Chuan Ho ◽  
Chin-Chuan Chang ◽  
Hung-Pin Chan ◽  
Ying-Fong Huang ◽  
Yi-Ming Arthur Chen ◽  
...  
Keyword(s):  
Systematic Review ◽  
Fdg Pet ◽  
Standardized Uptake Value ◽  
Fdg Uptake ◽  
Asymptomatic Patients ◽  
Positron Emission ◽  
Pet Ct ◽  
18F Fdg ◽  
Maximal Standardized Uptake Value ◽  
Fdg Pet Ct

During the coronavirus disease 2019 (COVID-19) pandemic, several case studies demonstrated that many asymptomatic patients with COVID-19 underwent fluorine-18 fluorodeoxyglucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) examination for various indications. However, there is a lack of literature to characterize the pattern of [18F]FDG PET/CT imaging on asymptomatic COVID-19 patients. Therefore, a systematic review to analyze the pulmonary findings of [18F]FDG PET/CT on asymptomatic COVID-19 patients was conducted. This systematic review was performed under the guidelines of PRISMA. PubMed, Medline, and Web of Science were used to search for articles for this review. Articles with the key words: “asymptomatic”, “COVID-19”, “[18F]FDG PET/CT”, and “nuclear medicine” were searched for from 1 January 2020 to 20 May 2021. Thirty asymptomatic patients with COVID-19 were included in the eighteen articles. These patients had a mean age of 62.25 ± 14.85 years (male: 67.71 ± 12.00; female: 56.79 ± 15.81). [18F]FDG-avid lung lesions were found in 93.33% (28/30) of total patients. The major lesion was [18F]FDG-avid multiple ground-glass opacities (GGOs) in the peripheral or subpleural region in bilateral lungs, followed by the consolidation. The intensity of [18F]FDG uptake in multiple GGOs was 5.605 ± 2.914 (range from 2 to 12) for maximal standardized uptake value (SUVmax). [18F]FDG-avid thoracic lymph nodes (LN) were observed in 40% (12/40) of the patients. They mostly appeared in both mediastinal and hilar regions with an SUVmax of 5.8 ± 2.93 (range from 2.5 to 9.6). The [18F]FDG uptake was observed in multiple GGOs, as well as in the mediastinal and hilar LNs. These are common patterns in PET/CT of asymptomatic patients with COVID-19.

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