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PMC9436376 | 35994654 | 1 | pnas.2205456119fig01 | null | Fig. 1. Comparison of basal TNBC metastatic and primary tumors, healthy tissues, NTs, and other TPs. ( A ) Study design. From GSE110590, we extracted only samples for basal-TNBC subtype including TPs (breast-TPs) and metastases in brain, lung, liver, lymph node, adrenal gland, and skin (TNBC-TMs) and matched them with the TPs of their metastatic organs and their associated NT adjacent to the tumor from TCGA and healthy tissues from GTEx. We performed identical processing of all samples to obtain TPM values. We then utilized several techniques to characterize the differences between TNBC-TMs, breast-TPs, and the TPs of the metastatic sites across tissue types. ( B ) General overview of integrated datasets using HHK clustering on median TPM values of each gene among all samples for each condition. The dendrogram is colored based on the optimal number of clusters as determined from the silhouette plot. BRCA represents breast invasive carcinoma; ACC, adrenocortical carcinoma; Ad, adenocarcinoma; Adrenal G., adrenal gland; PCPG, pheochromocytoma and paraganglioma; Sc, squamous cell carcinoma. ( C ) UMAP plot of all samples in the combined dataset. Points are colored by the associated tissue, and the shape of each point represents the condition: healthy tissue (HT), TM, TP, or NT. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2205456119 |
PMC9436376 | 35994654 | 2 | pnas.2205456119fig02 | null | Fig. 2. Intermediate state of TNBC-TMs between breast-TPs and TPs of the metastatic organs. ( A ) PCA plot for breast-TP and the associated TM in distinct tissue types. In all three groups, TM samples (maroon) lie between breast-TP samples (pink) and the TP samples of their metastatic organs and are closer to TPs of their metastatic organs. ( B ) Deconvolution analysis of the TNBC-TM samples using median expression levels of breast-TPs and TPs of the metastatic destination tissues as references. The result of the analysis is the fraction of similarity of each TM sample (maroon) to the TPs of the destination tissue. A value of 1 on the y axis indicates the maximum proportion of “destination tissue_TP contribution”, meaning maximum similarity to median expression levels of “destination tissue_TP” as reference, and 0 indicates the minimum proportion of “destination tissue_TP contribution.” Boxplot represents the distribution of the proportion of “destination tissue_TP contribution” for TMs. The points, breast-TPs (pink), and TPs of the tissue of destination (colored by cancer type) deconvolution fractions are shown as references. AdrenalG., adrenal gland; BRCA represents breast invasive carcinoma. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2205456119 |
PMC9436376 | 35994654 | 3 | pnas.2205456119fig03 | null | Fig. 3. Divergence of TNBC-TMs from breast-TPs based on DEGs and GSA. ( A ) Venn diagrams of the number of common and specific over-expressed genes (red) and under-expressed genes (blue) in TNBC-TMs compared with breast-TPs. ( B ) Heatmap of differentially over- and under-expressed genes of each metastasis. DEGs of each of the TMs distinct from the other metastases were combined, and the final subset of genes was extracted from breast-TP and TPs of the tissue of metastatic sites and their matched healthy tissues for brain, liver, and lung. The pattern of expression is similar to the tissue of destination in both under-expressed ( Left ) and over-expressed ( Right ) genes. ( C ) Results of the directional GSA of DE analysis results for TNBC metastases in lung, liver, and brain versus paired breast-TPs. Only the Hallmark gene set collection is shown here, and sets with <10 genes were excluded. The more significant (lower value) of the two directional P values for each gene set is shown in the heatmap as a log 10 -transformed value. The distinct directional gene set P values (p adj.dist.dir ) are calculated for coordinated increases (p adj,dist-dir-up ) and decreases (p adj,dist-dir-down ) in expression. The value is also “signed,” meaning that gene sets with a more significant decrease than increase (p adj,dist-dir-down < p adj,dist-dir-up ) are negative (enriched in breast-TPs); otherwise, they are positive (enriched in TNBC-TMs). Only gene sets with a p adj,dist-dir less than 0.01 in at least one TM are shown. ( D ) Nondirectional GSA results for three comparisons. The “p.non.directional” value for each gene set is filtered based on non.dir P values less than 0.01 and shown in the heatmap as a log 10 -transformed P value. HT, healthy tissue; IL, interleukin; NFκB, nuclear factor κB; UV, ultra violet; UVresponse-DN represents genes down-regulated in response to UV radiation. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2205456119 |
PMC9436376 | 35994654 | 4 | pnas.2205456119fig04 | null | Fig. 4. Divergence of TNBC-TMs from breast-TPs based on metabolic signatures. ( A ) Deconvolution analysis of the TNBC-TM samples using median expression levels of metabolism-associated genes in breast-TPs and TPs of the tissue of destination as references. The result of the analysis is the fraction of similarity of each TM sample (maroon) to the TPs of the tissue of its destination based on only their metabolic genes. Boxplot represents the distribution of the proportion of “destination tissue_TP contribution” for TMs. ( B ) Heatmaps showing comparison of reaction content of GEMs specific to TNBC-TMs in distinct tissues with breast-TPs as their tumor of origin and GEMs specific to TPs of the tissue of destination and their matched healthy tissue (HT) and NTs, based on the Jaccard index. ( C ) Subsystem directional GSA results for the comparisons of breast-TPs in distinct tissues with breast-TPs. Shown are the log 10 -transformed “distinct directional” P values (p.dist.dir) for subsystems with P value < 0.01 in at least one comparison. The log 10 -transformed P values are signed, meaning that gene sets significantly enriched in expression increases are positive, while those enriched more in expression decreases are negative. Ad, adenocarcinoma; AdrenalG., adrenal gland; BRCA represents breast invasive carcinoma; Sc, squamous cell carcinoma. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2205456119 |
PMC9436376 | 35994654 | 5 | pnas.2205456119fig05 | null | Fig. 5. Metabolic signatures and essential genes as potential drug targets. ( A ) UpSet plot of comparison combinations in each group. Each row corresponds to a condition, and each bar shows a different combination. The filled-in cells show which condition is part of an intersection, and the lines connecting the filled-in cells show in which direction the plot should be read. TM-specific reactions are colored maroon, and common reactions between breast-TPs and TNBC-TMs are colored pink. ( B ) Genes predicted to be essential for biomass production are colored blue in each condition. Among the essential genes, those that are not essential in most healthy models can be considered potential drug targets for cancer therapy. ACC, adrenocortical carcinoma; Ad, adenocarcinoma; AdrenalG., adrenal gland; amyg., amygdala; basalG, basal ganglia; BRCA represents breast invasive carcinoma; hipp., hippocampus; HT, healthy tissue; hypo., hypothalamus; PCPG, pheochromocytoma and paraganglioma; Sc, squamous cell carcinoma; substantiaN, substantia nigra. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2205456119 |
PMC9436377 | 35981134 | 1 | pnas.2202112119fig01 | null | Computational models are increasingly valuable tools. But articles that report the results of models are frequently not sufficient to reproduce the models. We need to do a better job making the source code of models accessible, understandable, and runnable by others. Image credit: Image credit: Shutterstock/NWM. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2202112119 |
PMC9436377 | 35981134 | 2 | pnas.2202112119fig02 | null | Fig. 1. Articles presenting results of agent-based and individual-based models from 1990–2018. Code with FAIR access refers to code published in persistent, trusted, FAIR-aligned repositories. Code not accessible refers to articles in which the authors do not indicate any location from which code can be downloaded. Image credit: Data from Ref ( 2 ) and used with permission. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2202112119 |
PMC9436377 | 35981134 | 3 | pnas.2202112119fig03 | null | Fig. 2. History of model code published in FAIR-aligned repositories of CoMSES.Net and CSDMS. Image credit: Data compiled by Barton and Lee for CoMSES.Net and Tucker for CSDMS. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2202112119 |
PMC9436378 | 35947637 | 1 | pnas.2206610119fig01 | null | Fig. 1. Identification of the SARS-CoV-2 interactome with signatures of positive selection (PS) in bats and primates. ( A ) Overview of the DGINN pipeline to detect adaptive evolution in SARS-CoV-2 VIPs. CDS, coding DNA sequence; ORF, open reading frame. ( B ) Natural selection acting on bat and primate VIP genes. Comparison of omega (dN/dS) values of the VIPs during bat ( y axis) and primate (x axis) evolution, estimated by Bio++ Model M0. In black, the bisector. In red, the linear regression. The names correspond to genes that we comprehensively analyzed ( Table 1 ). ( C ) Overview of the number of VIPs under significant PS (i.e., by at least three methods in the DGINN screen) in bats and/or primates. A total of 324 genes could be fully analyzed in the two mammalian orders. Numbers represent the number of genes in the categories: No PS or PS, within each host, is represented by a pictogram. The numbers correspond to the conservative values after visual inspection of the positively selected VIP alignments, while the italic numbers are from the automated screen. ( D ) Table showing the genes identified by x,y DGINN methods in bats and primates, respectively. For the genes with low DGINN scores (<3), only the number of genes in each category is shown ( SI Appendix , Fig. S4 for details). Of note, seven primate genes are false positive, as follows: EMC1 (ER membrane protein complex subunit 1), MOV10 (Mov10 RISC complex RNA helicase), POR (cytochrome p450 oxidoreductase), PITRM1 (pitrilysin metallopeptidase 1), RAB14, RAB2A, and TIMM8B (translocase of inner mitochondrial membrane 8 homolog B). | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2206610119 |
PMC9436378 | 35947637 | 2 | pnas.2206610119fig02 | null | Fig. 2. SARS-CoV-2 VIPs under PS are interacting proteins of other coronaviruses, as well as other viral families. Virus–host protein–protein interaction network of VIP genes under PS and interconnected with ( A ) other coronaviruses (from alpha- or beta-coronavirus genus), and ( B ) viral families other than coronaviruses. VIPs interacting with more than one additional viral family are in the Center and arranged in columns (from Left to Right , interconnected with 2 to 6 different viral families). Node sizes at the virus families are proportional to the number of edges. The VIPs not interconnected are shown in SI Appendix , Table S1 . | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2206610119 |
PMC9436378 | 35947637 | 3 | pnas.2206610119fig03 | null | Fig. 3. TMPRSS2 has evolved under strong PS in primates but not in bats. ( A ) Role of TMPRSS2 in SARS-CoV-2 entry. ( B ) Diagram of TMPRSS2 predicted domains, with sites under PS in primates represented by triangles ( Table 1 ). Codon numbering and amino acid residue based on Homo sapiens TMPRSS2. ( C ) 3D structure modeling of human TMPRSS2 (amino acids 1 to 492) with the positively selected sites (red), the SARS-CoV-2 predicted interface (light blue), and the catalytic site (dark blue). ( D ) The positively selected sites identified in primate TMPRSS2 are highly variable in primates ( Top ) but more conserved in bats ( Bottom ) where they are not identified as under adaptive evolution. Left , cladograms of primate and bat TMPRSS2 with species abbreviation and accession number of sequences. Amino acid color-coding, RasMol properties (Geneious, Biomatters). Icon legend is embedded in the figure, with multicolored pictograms/triangles showing cases fulfilling multiple conditions. ( E ) Positively selected sites in primates exhibit different patterns of variability in other mammals, as follows: pangolin, carnivores, artiodactyls, and rodents. Right , numbers in brackets correspond to the number of species within the order with the same TMPRSS2 haplotype at these positions (e.g., the QSSKL motif in Mustela putoris was found in 14 rodent species). The corresponding motif in species/cells susceptible or permissive to coronaviruses is shown in SI Appendix , Fig. S8 . | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2206610119 |
PMC9436378 | 35947637 | 4 | pnas.2206610119fig04 | null | Fig. 4. Domains of FYCO1 that are associated with severe COVID-19 in human have also evolved under significant PS in primates but not in bats. ( A ) Known cellular role of FYCO1. ( B ) Diagram of FYCO1 predicted domains, with sites under PS in primates represented by triangles ( Table 1 ). Codon numbering and amino acid residue based on Homo sapiens FYCO1. ( C ) Amino acid variation at the positively selected sites in primates. Left , cladogram of primate FYCO1 with major clades highlighted. The exact species and accession number of sequences are shown in E . Amino acid color-coding, RasMol properties (Geneious, Biomatters). ( D ) Sites identified in the coding sequence of FYCO1 as under PS in primates ( Top ) and as associated with severe COVID-19 in human from two GWAS studies ( Middle : GWAS1, COVID-19 Host Genetics Initiative, 2021; Bottom : GWAS2, Pairo-Castineira et al., 2020). x axis, nucleotide numbering. ( E ) Amino acid variations in primate species at the sites associated with severe COVID-19 in GWAS. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2206610119 |
PMC9436378 | 35947637 | 5 | pnas.2206610119fig05 | null | Fig. 5. The multifunctional and inflammatory RIPK1 protein exhibits strong evidence of adaptation in bats at key regulatory residues. ( A ) Schematic diagram of the three main functions associated to human RIPK1 in TNF signaling. As part of the TNFR1-associated complex, RIPK1 induces prosurvival signals that notably lead to NFkB activation. When dissociating from this complex, as a result of multiple events involving both phosphorylation and ubiquitination, RIPK1 can associate to FADD and lead to apoptosis or necrosis. ( B ) Diagram of RIPK1 domains with the residues under PS in bats (black triangles) with the corresponding position and amino acid residue in human RIPK1 ( Table 1 ). ( C ) 3D structure prediction of bat ( Rhinolophus ferrumequinum ) RIPK1, using RaptorX. The protein domains are color coded as in B . Residues under PS are in red and numbered is according to their position in bat RIPK1. ( D ) The positively selected sites identified in bat RIPK1 are highly variable in bats ( Top ), but more conserved in primates ( Bottom ), where they are not identified as under adaptive evolution. Left , bat and primate RIPK1 with species abbreviation and accession number of sequences. Amino acid color coding, polarity properties (Geneious, Biomatters). The correspondence of residues from Rhinolophus ferrumequinum bat RIPK1 (gray) to human numbering (black) is shown at the Top . Detailed representation is shown in SI Appendix , Fig. S10 . | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2206610119 |
PMC9436382 | 35994661 | 1 | pnas.2121338119fig01 | null | Fig. 1. Optimizing the learnability of a modular graph. ( A ) A modular graph with 15 nodes, each with degree k i = 4, resulting in 30 edges. ( B – D ) Here, we show the Kullback–Leibler divergence ratio (less than one indicates enhanced learnability) across a section of the λ cc , λ b parameter space, for different values of β . For increased contrast, the ratios have been truncated to the range [ 0.9 , 1.1 ] . ( B ) Results for β = 0.05 , corresponding roughly to the median accuracy of human learners in prior studies ( 21 ). ( C ) Results for β = 0.3 , corresponding to the mean accuracy of human learners in prior studies ( 21 ). ( D ) Results for β = 5, corresponding to an exceptionally accurate network learner. ( E ) The optimal edge weights λ cc and λ b for 0 < β < 1 . ( F ) The Kullback–Leibler divergence between the learned network and the true network for different values of β , both with and without input network optimization. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2121338119 |
PMC9436382 | 35994661 | 2 | pnas.2121338119fig02 | null | Fig. 2. Optimal emphasis modulation of the modular and lattice networks. Here, we show the learned networks resulting from human learning of the modular and lattice networks, respectively ( A and B , Upper ), as well as from the modular and lattice networks optimized for learnability ( A and B , Lower ). Optimized and learned networks were both computed at β = 0.05 . Edge thickness indicates transition probabilities. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2121338119 |
PMC9436382 | 35994661 | 3 | pnas.2121338119fig03 | null | Fig. 3. Optimizing the learnability of synthetic modular networks. ( A and B ) Examples of a standard stochastic block network and a degree-corrected stochastic block network. Node sizes are proportional to node degrees, with cross-cluster edges shown in purple and orange, respectively. ( C and D ) The optimal cross-cluster edge weight λ cc for enhancing learnability versus the fraction f of edges within communities at different values of β . Results are shown for stochastic block networks and degree-corrected stochastic block networks, respectively. ( E and F ) The Kullback–Leibler (KL) divergence ratio D K L ( A | | f ( A in ) ) D K L ( A | | f ( A ) ) achieved with optimal cross-cluster edge weights at different values of β . Results are shown for stochastic block networks and degree-corrected stochastic block networks, respectively. The findings reported in C – F represent results obtained for networks with N = 200 nodes, 5 communities, and an average degree of 〈 k 〉 = 10 . Each curve is an average over the results from 25 generated networks. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2121338119 |
PMC9436382 | 35994661 | 4 | pnas.2121338119fig04 | null | Fig. 4. Optimizing the learnability of semantic networks extracted from college mathematics textbooks. ( A ) A schematic of how edges in the semantic networks were classified based on core–periphery node classification and periphery community structure. ( B ) The optimal weight scaling for each of the four classes of edges shown at different values of β , averaged over all semantic networks. ( C ) The Kullback–Leibler (KL) divergence ratio D K L ( A | | f ( A in ) ) D K L ( A | | f ( A ) ) achieved with optimized weight scaling at different values of β . Results are shown for each of the 10 semantic networks corresponding to the 10 college-level linear algebra textbooks ( 61 – 70 ). ( D ) The distribution of optimized edge-weight scalings for the classes of edges at β = 0.2 , aggregated over all semantic networks. Prob., probability. ( E and F ) The optimal edge-weight scaling versus edge-betweenness centrality and edge-degree centrality, respectively, aggregated over all semantic networks for β = 0.2 . Each datapoint represents an average over 500 edges binned by centrality score. | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2121338119 |
PMC9436382 | 35994661 | 5 | pnas.2121338119fig05 | null | Fig. 5. Performance of network-learning strategies in the transient regime. Each panel shows the Kullback–Leibler (KL) divergence between some true network and the learned network as a function of the number of observed transitions. Three network-learning strategies are shown: maximum-likelihood estimation (optimal in the limit of infinite observations), standard human network learning (supported by ref. 21 ), and optimized human network learning (introduced in this paper). All plots report 10 simulations of each network-learning strategy, with human learning and optimized human learning simulations run at β = 0.1 , close to the median learning accuracy reported in ref. 21 . The three networks analyzed are the modular network with 15 nodes ( A ) ( Fig. 1 A ), the semantic network extracted from the linear algebra textbook authored by Axler ( B ) ( 61 ), and the semantic network extracted from the linear algebra textbook authored by Edwards ( C ) ( 63 ). | CC BY-NC-ND | no | 2022-09-02 23:39:20 | Proc Natl Acad Sci U S A. 2022 Aug 30; 119(35):e2121338119 |
PMC9436508 | 0 | 1 | 10-1055-s-0042-1750014-i6421-1 | null | Fig. 1
Axial and coronal magnetic resonance imaging (gadolinium-enhanced T1-weighted imaging sequence), positron emission tomography, and fused positron emission tomography-computed tomography images show metabolically active thickening with enhancement involving the supraorbital pachymeninges (maximum standardized uptake value [SUVmax]-4;
A
–
C
), bilateral optic sheaths (SUVmax-4.5;
D
–
F
), and dura mater of falx cerebri (
G
–
I
).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):236-238 |
PMC9436508 | 0 | 2 | 10-1055-s-0042-1750014-i6421-2 | null | Fig. 2
Static fluorodeoxyglucose positron emission tomography brain (maximum intensity projection) image shows linear increased tracer uptake along bilateral supraorbital regions depicting as eyebrows.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):236-238 |
PMC9436511 | 0 | 1 | 10-1055-s-0042-1751056-i4921-1 | null | Fig. 1
Brain perfusion single-photon emission computed tomography of a patient with left thalamic bleed with poststroke depression exhibiting hypoperfusion in left thalamus and parietal lobe. (
A
) Visual assessment and (
B
) quantitative analysis in different brain areas using NeuroGam software.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):222-230 |
PMC9436512 | 0 | 1 | 10-1055-s-0042-1755411-i3121-1 | null | Fig. 1
Noncontrast chest computed tomography (CT) obtained as part of the lung perfusion single-photon emission computed tomography/computed tomography scan (
left
) in the sagittal plane (
left
) demonstrating multiple peripheral consolidative opacities (
arrows
) with air bronchograms and reticulations in the left upper lobe. These findings are characteristic of coronavirus disease 2019 pneumonia in the appropriate clinical setting. Notably, contrast-enhanced chest CT (
right
) in the sagittal plane obtained 3 days prior was unremarkable, only demonstrating subsegmental plate-like atelectasis in the left lower lobe.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):210-214 |
PMC9436512 | 0 | 2 | 10-1055-s-0042-1755411-i3121-2 | null | Fig. 2
Chest computed tomography (CT) (
upper left
) and single-photon emission computed tomography-computed tomography (SPECT/CT) perfusion images (
upper right
) in the axial plane at the mid lung level demonstrate multiple peripheral consolidative lung opacities with reticulation predominantly in the left upper lobe as well as the right upper lobe (
arrowheads
) with corresponding areas of decreased perfusion. A new small right-sided pleural effusion has been also developed. SPECT perfusion imaging in the axial plane (
left lower
) reveals multiple small peripheral perfusion defects (
thin arrows
) corresponding to peripheral vascular territories on CT reflecting probable small emboli. SPECT perfusion in the coronal plane (right lower) of the posterior lungs demonstrates large areas of central perfusion defects (
wide arrows
) not corresponding to vascular territories (“stripe sign”).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):210-214 |
PMC9436512 | 0 | 3 | 10-1055-s-0042-1755411-i3121-3 | null | Fig. 3
Single-photon emission computed tomography (SPECT) (
left
) and SPECT/CT perfusion images (
right
) in the axial plane near the lung bases demonstrate large areas of central perfusion defects (
wide arrows
) not reflecting vascular territories. These may represent areas of inflammation with characteristic 'stripe sign” (
thin arrows
) and without underlying CT abnormalities.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):210-214 |
PMC9436513 | 0 | 1 | 10-1055-s-0042-1751039-i9621-1 | null | Fig. 1
(
A
) Maximum intensity projection (MIP) positron emission tomography (PET) image; (
B–D
) computed tomography (CT), PET, and fused PET/CT axial images showing metabolically active ill-defined soft tissue attenuation involving the entire length of penile shaft with central necrotic area (maximum standardized uptake value [SUV
max
]: 19.2); (
E–G
) CT, positron emission tomography (PET), and fused PET/CT coronal images showing metabolically active nodules in right forearm anterior aspect, right inguinal nodes, penile bulb; (
H–J
) CT, PET, and fused PET/CT sagittal images showing metabolically active soft tissue attenuation nodules in root of penis (SUV
max
: 18.2), penile bulb, diffuse skin thickening of scrotum. Hypermetabolic diffuse involvement of bone marrow of both femora, with associated intense uptake in marrow of right femur in distal epiphysis (SUV
max
: 22.5) (MIP image A).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):255-260 |
PMC9436513 | 0 | 2 | 10-1055-s-0042-1751039-i9621-2 | null | Fig. 2
(
A–C
) Computed tomography (CT), positron emission tomography (PET), and fused PET/CT axial images showing metabolically active subcutaneous regions in both ankles; (
D–F
) CT, PET, and fused PET/CT coronal images showing linear hypermetabolism uptake noted in left leg-lateral compartment muscles (
arrow
), maximum standardized uptake value (SUV
max
): 18; (
G–I
) CT, PET, and fused PET/CT sagittal images showing metabolically active left inguinal subcutaneous nodule—largest right measuring 3.3 × 2.3 cm, SUV
max
: 17.5.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):255-260 |
PMC9436513 | 0 | 3 | 10-1055-s-0042-1751039-i9621-3 | null | Fig. 3
Anon-contrast computed tomography (CT) axial image showing ill-defined soft tissue attenuation in penile shaft with central necrotic area; (
B
) fused positron emission tomography/computed tomography (PET/CT) axial image showing metabolic activity involving the entire length of penis (maximum standardized uptake value [SUV
max
]: 19.2); (
C
) fused PET/CT coronal images showing metabolically active right inguinal nodes and penile bulb; (
D
) fused PET/CT sagittal images showing metabolically active soft tissue attenuation nodules in root of penis-largest in left inguinal region measuring 3.3 × 2.3 cm (SUV
max
: 18.2), penile bulb, and diffuse skin thickening of scrotum.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):255-260 |
PMC9436514 | 0 | 1 | 10-1055-s-0042-1755412-i3821-1 | null | Fig. 1
Kaplan–Meier plot of overall survival (OS) of all patients. Estimated OS: 23 months (95% confidence interval: 7.90–38.09).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):215-221 |
PMC9436514 | 0 | 2 | 10-1055-s-0042-1755412-i3821-2 | null | Fig. 2
A 54-year-old female with metastatic neuroendocrine tumor and refractory to chemotherapy presented for peptide receptor radionuclide therapy (PRRT). Pretreatment fluorodeoxyglucose-positron emission tomography (FDG-PET) (
A
) showed no radiotracer uptake (the both hot foci in the pelvis observed on FDG-PET computed tomography [CT] were due to contamination), while all lesions in the liver (maximum standardized uptake value [SUV
max
]: 26.26, size: 34 mm), around the inferior vena cava (IVC) in the right side (SUV
max
: 20.03; size: 23 mm), sacrum (SUV
max
: 34.74), and also a focus in the left side of vermis on pretreatment
68
Ga-DOTATATE PET/CT (
B
) had significant somatostatin receptor expression. The patients underwent four cycles of PRRT (29.6 GBq). The posttreatment scintigraphy after first cycle (
C
) indicated intensive uptake of radiotracer in above-mentioned regions with significantly decrease in number and size in posttreatment scintigraphy after the fourth cycle (
D
). Interestingly, follow-up
68
Ga-DOTATATE PET-CT (
E
) performed 4 months after fourth cycle of PRRT showed excellent partial response with residual viable disease in the liver (SUV
max
: 12.23; size: 20 mm), large-sized IVC metastases (SUV
max
: 4.51; size: 16 mm), and sacrum (SUV
max
: 7.94). In addition, the transverse view of pretherapy
68
Ga-DOTATATE PET-CT (
F
) indicates excellent response of liver lesions to PRRT compared with the transverse view of posttherapy
68
Ga-DOTATATE PET-CT (
G
).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):215-221 |
PMC9436515 | 0 | 1 | 10-1055-s-0042-1750439-i8321-1 | null | Fig. 1
(
A1
) Plain anteroposterior radiograph and (
A2
) coronal computed tomographic (CT) view of the left wrist showing soft tissue edema and comminuted displaced fracture of the distal end of the radius (
A1
,
white arrow
) with erosion of the carpus and third metacarpal base (
A1–A2
,
arrowheads
). Axial CT images in (
B1
) soft-tissue and (
B2
) bone windowing showing associated synovial thickening (
B1
,
black arrows
) and osseous erosion (
B2
,
asterisks
). Ultrasound image in long-axis at the third metacarpal bone showing a hypoechogenic polylobulated mass (
C
,
arrows
) with adjacent comminuted bone fracture (
C
,
arrowheads
).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):244-247 |
PMC9436515 | 0 | 2 | 10-1055-s-0042-1750439-i8321-2 | null | Fig. 2
(
A
) Whole body bone scan showing diffusely increased osseous activity in the left wrist. Close-up dorsal (
B1
) and palmar (
B2
) views of the hands better characterizing distribution of activity in the bones of the left distal upper extremity. (
C
) Ultrasound-guided biopsy (
C
) showing a hypoechogenic polylobulated mass (
arrows
). (
D
) Histopathologic comparison of the primary hepatocellular carcinoma 2 years prior (
D1
—hematoxylin and eosin, original magnification ×20), and more recent left wrist mass infiltrating lamellar bone (
asterisk
) of the third metacarpal (
D2
) (hematoxylin and eosin, original magnification ×10).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):244-247 |
PMC9436516 | 0 | 1 | 10-1055-s-0042-1750438-i7821-1 | null | Fig. 1
Longitudinal ultrasonography image demonstrating a hypoechoic mass lesion involving the uncinate process and pancreatic head with foci of calcifications. There is associated atrophy of the pancreas and dilated main pancreatic duct.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 25; 21(3):239-243 |
PMC9436516 | 0 | 2 | 10-1055-s-0042-1750438-i7821-2 | null | Fig. 2
(
A
) Axial computed tomography image in the arterial phase demonstrating a lobulated hypoenhancing mass lesion involving the uncinate process and head of pancreas with exuberant cauliflower like dystrophic calcifications. (
B
) Coronal reformatted computed tomography image in the portal venous phase demonstrating posterosuperior displacement of the pancreatic body and tail by the mass lesion in the uncinate process and pancreatic head. Note the atrophic pancreas with dilated main pancreatic duct consistent with features of chronic pancreatitis.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 25; 21(3):239-243 |
PMC9436516 | 0 | 3 | 10-1055-s-0042-1750438-i7821-3 | null | Fig. 3
Histopathology image demonstrating duct dilatation, fibrosis, and pancreatic tissue necrosis with parenchymal calcifications consistent with features of chronic pancreatitis (hematoxylin and eosin, ×200).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 25; 21(3):239-243 |
PMC9436517 | 0 | 1 | 10-1055-s-0042-1751031-i1821-1 | null | Fig. 1
Maximum-intensity projection of
18
F-choline positron emission tomography (PET) (
A
) and transaxial views of the thyroid gland on PET (
B
), computed tomography (CT) (
C
), and PET/CT fusion images (
D
) showing intense
18
F-choline uptake in the enlarged right thyroid lobe (
arrows,
maximum standardized uptake value 8.2). Histopathologic examination revealed a pT3a papillary thyroid carcinoma.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):192-199 |
PMC9436517 | 0 | 2 | 10-1055-s-0042-1751031-i1821-2 | null | Fig. 2
Maximum intensity projection (MIP) of
18
F-choline positron emission tomography (PET) (
A
) and transaxial views of the lungs on PET (
B
), computed tomography (CT) (
C
), and PET/CT fusion images (
D
) showing focal
18
F-choline uptake in a left upper lobe lung nodule (
arrows,
diameter: 1.8 cm, maximum standardized uptake value [SUVmax]: 3.6). MIP of
18
F-fluorodesoxyglucose (
18
F-FDG) PET (
E
) showing intense FDG-avidity (
arrow,
SUVmax 9.2) without evidence for metastases. Histopathologically examination after lobectomy revealed pT1b squamous cell lung carcinoma.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):192-199 |
PMC9436517 | 0 | 3 | 10-1055-s-0042-1751031-i1821-3 | null | Fig. 3
Maximum intensity projection of
18
F-choline positron emission tomography (PET) (
A
) and transaxial views of the breasts on PET (
B
), computed tomography (CT) (
C
), and PET/CT fusion images (
D
) showing focal
18
F-choline uptake in a nodular mass in the left breast (
arrows,
diameter: 1.6 cm, maximum standardized uptake value: 4.5). Histopathologic examination revealed a pT1c infiltrating lobular breast carcinoma.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):192-199 |
PMC9436517 | 0 | 4 | 10-1055-s-0042-1751031-i1821-4 | null | Fig. 4
Transaxial views of the upper abdomen on computed tomography (CT) (
A
), positron emission tomography (PET) (
B
) and PET/CT fusion images (
C
) showing focal
18
F-choline uptake in a nodular mass of the right adrenal gland (
arrows,
maximum standardized uptake value: 6.6) and a typical aspect of an adrenal adenoma on CT (radiodensity of -5 Hounsfield units).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):192-199 |
PMC9436517 | 0 | 5 | 10-1055-s-0042-1751031-i1821-5 | null | Fig. 5
Sagittal views of
18
F-choline positron emission tomography (PET) (
A
), computed tomography (CT) (
B
) and PET/CT fusion images (
C
) showing an example of nonspecific intense bone uptake (
arrows,
thoracic vertebrae 2–4, maximum standardized uptake value: 18.1). Additional
18
F-fluorodesoxyglucose (
18
F-FDG) PET (
D
) did not show signs of malignancy and follow-up
18
F-choline PET (
E
) 3 months later showed a near normalization of uptake. The cause of the increased
18
F-choline uptake was not elucidated.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):192-199 |
PMC9436518 | 0 | 1 | 10-1055-s-0042-1750440-i8421-1 | null | Fig. 1
The maximum intensity projection image of whole-body Fluorine-18 prostate specific membrane antigen positron emission tomography/computed tomography (
18
F-PSMA-1007 PET/CT) (
A
) shows multiple foci of abnormal tracer uptake in the pelvis and abdomen. The transaxial fused PET/CT and contrast-enhanced computed tomography images showed increased uptake of radiotracer in primary tumor in prostate infiltrating the neck of urinary bladder, rectum, levator ani, and obturator muscles along with pelvic lymphadenopathy (
B, C
). An isolated PSMA avid enhancing nodule was also noted in the mucosal aspect of anterolateral wall of rectum away from the primary lesion in transaxial (
D, E
;
black arrows
) and sagittal (
F, G
;
black arrows
) sections.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):248-250 |
PMC9436518 | 0 | 2 | 10-1055-s-0042-1750440-i8421-2 | null | Fig. 2
The maximum intensity projection image of whole-body fluorine-18 prostate specific membrane antigen positron emission tomography/computed tomography (
18
F-PSMA-1007 PET/CT) post six cycles of chemotherapy (
A
) shows persistent radiotracer uptake in the primary and pre-existing metastatic sites in pelvis along with new foci of PSMA uptake. The transaxial fused PET/CT and contrast-enhanced computed tomography images showed persistent uptake of radiotracer in the previously documented nodular deposit in rectum (
B, C
). A new PSMA avid hypodense lesion was visualized in the anterior wall of rectum on transaxial (
D, E
;
white arrows
) and sagittal (
F, G
;
white arrows
) sections.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):248-250 |
PMC9436521 | 0 | 1 | 10-1055-s-0042-1751057-i12221-1 | null | Fig. 1
A 64-year-old woman with amyloid deposition on gastric biopsy. (
A
) Echocardiography shows biventricular hypertrophy (
solid white arrows
) and atrial fibrillation. (
B
) Axial contrast-enhanced computed tomography shows left ventricular hypertrophy (
solid black arrows
). (
C
and
D
) cardiovascular magnetic resonance reveals concentric left ventricular hypertrophy (
dashed white arrows
in
C
) and diffuse transmural myocardial enhancement of ventricles (
dashed yellow arrows
in
D
).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):173-183 |
PMC9436521 | 0 | 2 | 10-1055-s-0042-1751057-i12221-2 | null | Fig. 2
A 64-year-old patient genopositive for mutant ATTR c.349G > T (p.Ala117Ser). (
A
) Four-chamber view with longitudinal strain map. (
B
) The bullseye longitudinal map of all myocardial segments. Note the reduced global longitudinal strain at −10.6% and apical sparing (> 2:1 apical/basal ratio or “cherry on top”) pattern. ATTR, transthyretin amyloidosis.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):173-183 |
PMC9436521 | 0 | 3 | 10-1055-s-0042-1751057-i12221-3 | null | Fig. 3
Spectrum of
99m
Tc-3,3-diphosphono-1,2- propanodicarboxylic acid uptake. (
A
) Unaffected control subject without visually detectable uptake. (
B
) Patient with light chain amyloidosis without visually detectable myocardial uptake; mild uptake is visible only at the soft tissue level. (
C
and
D
) Two patients with TTR-related amyloidosis showing strong myocardial uptake with absent bone uptake (reprinted from Perugini et al
28
).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):173-183 |
PMC9436521 | 0 | 4 | 10-1055-s-0042-1751057-i12221-4 | null | Fig. 4
Raw images of a representative negative (
A
) and positive subject (
B
) are shown 1 hour after radiotracer infusion. ROI circles are depicted in red and the contralateral comparison circle is depicted in blue. C/L, contralateral; Cts, counts; ROI, region of interest; Std Dev, standard deviation (reprinted from from Bokhari et al
23
).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):173-183 |
PMC9436521 | 0 | 5 | 10-1055-s-0042-1751057-i12221-5 | null | Fig. 5
Schematic representation of global subendocardial and transmural patterns of late gadolinium enhancement (LGE) in amyloidosis (
enhancement depicted in white
).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):173-183 |
PMC9436521 | 0 | 6 | 10-1055-s-0042-1751057-i12221-6 | null | Fig. 6
Schematic representation of query amyloid late enhancement (QALE) score. The QALE score is assessed on late gadolinium enhancement (LGE) images at the level of base, mid, and apex of the ventricles. The highest score is 4 at each level or 6 if right ventricle is involved. The total score ranges from 0 (no LGE) to 18 (global transmural left ventricle (LV) LGE and right ventricle (RV) involvement).
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):173-183 |
PMC9436521 | 0 | 7 | 10-1055-s-0042-1751057-i12221-7 | null | Fig. 7
Cardiovascular magnetic resonance short-axis (
A
) and long-axis (
B
) images through the mid-left ventricle demonstrate application of myocardial tagging at end-diastole. The tag lines are seen as dark lines that deform along with the myocardium during systole.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):173-183 |
PMC9436521 | 0 | 8 | 10-1055-s-0042-1751057-i12221-8 | null | Fig. 8
Diagnostic algorithm in suspected cardiac amyloidosis (CA). Echocardiography is the first line of investigation in clinically suspected patients with CA. Cardiac magnetic resonance imaging (CMR) is not diagnostic but can exclude other causes or direct further biopsy. ATTR is more likely if the monoclonal assay is negative and the bone scintigraphy shows grade 2–3 uptake. A combination of positive monoclonal assay and positive CMR findings can indicate light chain type of CA. ATTR, transthyretin amyloidosis.
| CC BY-NC-ND | no | 2022-09-02 23:39:21 | World J Nucl Med. 2022 Aug 16; 21(3):173-183 |