Dosimetric Analysis of a Phase I Study of PSMA-Targeting Radiopharmaceutical Therapy With [177Lu]Ludotadipep in Patients With Metastatic Castration-Resistant Prostate Cancer.

OBJECTIVE: 177Lutetium [Lu] Ludotadipep is a novel prostate-specific membrane antigen targeting therapeutic agent with an albumin motif added to increase uptake in the tumors. We assessed the biodistribution and dosimetry of [177Lu]Ludotadipep in patients with metastatic castration-resistant prostate cancer (mCRPC). MATERIALS AND METHODS: Data from 25 patients (median age, 73 years; range, 60-90) with mCRPC from a phase I study with activity escalation design of single administration of [177Lu]Ludotadipep (1.85, 2.78, 3.70, 4.63, and 5.55 GBq) were assessed. Activity in the salivary glands, lungs, liver, kidneys, and spleen was estimated from whole-body scan and abdominal SPECT/CT images acquired at 2, 24, 48, 72, and 168 h after administration of [177Lu]Ludotadipep. Red marrow activity was calculated from blood samples obtained at 3, 10, 30, 60, and 180 min, and at 24, 48, and 72 h after administration. Organ- and tumor-based absorbed dose calculations were performed using IDAC-Dose 2.1. RESULTS: Absorbed dose coefficient (mean ± standard deviation) of normal organs was 1.17 ± 0.81 Gy/GBq for salivary glands, 0.05 ± 0.02 Gy/GBq for lungs, 0.14 ± 0.06 Gy/GBq for liver, 0.77 ± 0.28 Gy/GBq for kidneys, 0.12 ± 0.06 Gy/GBq for spleen, and 0.07 ± 0.02 Gy/GBq for red marrow. The absorbed dose coefficient of the tumors was 10.43 ± 7.77 Gy/GBq. CONCLUSION: [177Lu]Ludotadipep is expected to be safe at the dose of 3.7 GBq times 6 cycles planned for a phase II clinical trial with kidneys and bone marrow being the critical organs, and shows a high tumor absorbed dose.

SPECT/CT Radiomics for Differentiating between Enchondroma and Grade I Chondrosarcoma.

This study was performed to assess the value of SPECT/CT radiomics parameters in differentiating enchondroma and atypical cartilaginous tumors (ACTs) located in the long bones. Quantitative HDP SPECT/CT data of 49 patients with enchondromas or ACTs in the long bones were retrospectively reviewed. Patients were randomly split into training (n = 32) and test (n = 17) data, and SPECT/CT radiomics parameters were extracted. In training data, LASSO was employed for feature reduction. Selected parameters were compared with classic quantitative parameters for the prediction of diagnosis. Significant parameters from training data were again tested in the test data. A total of 12 (37.5%) and 6 (35.2%) patients were diagnosed as ACTs in training and test data, respectively. LASSO regression selected two radiomics features, zone-length non-uniformity for zone (ZLNUGLZLM) and coarseness for neighborhood grey-level difference (CoarsenessNGLDM). Multivariate analysis revealed higher ZLNUGLZLM as the only significant independent factor for the prediction of ACTs, with sensitivity and specificity of 85.0% and 58.3%, respectively, with a cut-off value of 191.26. In test data, higher ZLNUGLZLM was again associated with the diagnosis of ACTs, with sensitivity and specificity of 83.3% and 90.9%, respectively. HDP SPECT/CT radiomics may provide added value for differentiating between enchondromas and ACTs.

Irreversible electroporation for prostate cancer using PSMA PET-CT.

Background: To demonstrate the clinical usefulness of prostate-specific membrane antigen (PSMA) positron emission tomography (PET) computerized tomography (CT) for irreversible electroporation (IRE) in prostate cancer patients. Methods: From January to May 2021, 17 men were diagnosed with localized prostate cancer through preoperative mpMRI and [18F] florastamin PSMA PET-CT imaging, followed by transperineal MRI-ultrasound fusion-guided biopsy. The patients underwent IRE focal therapy at the target lesions under general anesthesia. To evaluate the treatment outcome, serum prostate-specific antigen (PSA) levels were followed up in the 1st, 3rd, 6th, 9th, 12th months, and mpMRI was taken in the 1st and 12th months, followed by MR fusion biopsy in the 12th month post-IRE. Results: The mean age of the patients was 66.1 ± 9.3 with a median PSA of 7.5 ng/ml. After the treatment, PSA nadir was 4.06 ± 3.4, and 11 (64.7%) achieved decline of PSA more than 50% from the baseline. Rate of negative biopsy for prostate cancer is 88% (15/17) at 12 months MR fusion biopsy after the IRE treatment. Among the relapsed cases, 1 (6.9%) patient recurred at margin of treated area, and 1 (6.9%) patient was from outfield recurrence. When excluding initial four patients, none of the patients had cancer recur. Conclusions: When treating with IRE focal therapy, PSMA-PET CT is a potentially valuable diagnostic approach for localizing prostate cancer; it supports the detection of lesions with conventional mpMRI, enabling to perform the procedure more completely.

Initial Experiences of Selective RET Inhibitor Selpercatinib in Adults with Metastatic Differentiated Thyroid Carcinoma and Medullary Thyroid Carcinoma: Real-World Case Series in Korea.

Recently, selpercatinib, a highly selective inhibitor of RET receptor tyrosine kinase, has been used for RET-altered thyroid cancer. We present four cases of patients with advanced thyroid cancer who were treated with selpercatinib. The first patient was a 63-year-old male with advanced medullary thyroid cancer (MTC) treated with vandetanib. Six months ago, he had an intracranial hemorrhage and swallowing difficulty. He started selpercatinib with percutaneous endoscopic gastrostomy (PEG). For 11 months, a partial response (PR) was observed stably with PEG administration without any more cardiovascular events. The second patient was a 67-year-old female with advanced MTC treated with vandetatib. After selpercatinib treatment, a PR was observed for most metastatic sites, including choroidal metastasis. The third patient was a 32-year-old female with advanced papillary thyroid cancer (PTC) without history of systematic treatment. For six months, a PR was observed at her metastatic site with manageable adverse events. The last patient was a 59-year-old female with advanced PTC treated with lenvatinib. She suffered from a panic disorder and pleural pain due to metastasis during lenvatinib treatment. After selpercatinib treatment, her pain and panic symptoms were improved. Facing varying clinical obstacles of the real world, selpercatinib safely proved remarkable therapeutic efficacy regardless of previous treatment or metastatic site.

Automatic Lung Cancer Segmentation in [18F]FDG PET/CT Using a Two-Stage Deep Learning Approach.

Purpose: Since accurate lung cancer segmentation is required to determine the functional volume of a tumor in [18F]FDG PET/CT, we propose a two-stage U-Net architecture to enhance the performance of lung cancer segmentation using [18F]FDG PET/CT. Methods: The whole-body [18F]FDG PET/CT scan data of 887 patients with lung cancer were retrospectively used for network training and evaluation. The ground-truth tumor volume of interest was drawn using the LifeX software. The dataset was randomly partitioned into training, validation, and test sets. Among the 887 PET/CT and VOI datasets, 730 were used to train the proposed models, 81 were used as the validation set, and the remaining 76 were used to evaluate the model. In Stage 1, the global U-net receives 3D PET/CT volume as input and extracts the preliminary tumor area, generating a 3D binary volume as output. In Stage 2, the regional U-net receives eight consecutive PET/CT slices around the slice selected by the Global U-net in Stage 1 and generates a 2D binary image as the output. Results: The proposed two-stage U-Net architecture outperformed the conventional one-stage 3D U-Net in primary lung cancer segmentation. The two-stage U-Net model successfully predicted the detailed margin of the tumors, which was determined by manually drawing spherical VOIs and applying an adaptive threshold. Quantitative analysis using the Dice similarity coefficient confirmed the advantages of the two-stage U-Net. Conclusion: The proposed method will be useful for reducing the time and effort required for accurate lung cancer segmentation in [18F]FDG PET/CT.

A Single Dose of Novel PSMA-Targeting Radiopharmaceutical Agent [177Lu]Ludotadipep for Patients with Metastatic Castration-Resistant Prostate Cancer: Phase I Clinical Trial.

[177Lu]Ludotadipep, which enables targeted delivery of beta-particle radiation to prostate tumor cells, had been suggested as a promising therapeutic option for mCRPC. From November 2020 to March 2022, a total of 30 patients were enrolled for single dose of [177Lu]Ludotadipep RPT, 6 subjects in each of the 5 different activity groups of 1.9 GBq, 2.8 GBq, 3.7 GBq, 4.6 GBq, and 5.6 GBq. [177Lu]Ludotadipep was administered via venous injection, and patients were hospitalized for three days to monitor for any adverse effects. Serum PSA levels were followed up at weeks 1, 2, 3, 4, 6, 8, and 12, and PSMA PET/CT with [18F]Florastamin was obtained at baseline and again at weeks 4 and 8. The subjects required positive PSMA PET/CT prior to [177Lu]Ludotadipep administration. Among the 29 subjects who received [177Lu]Ludotadipep, 36 treatment emergent adverse events (TEAEs) occurred in 17 subjects (58.6%) and 4 adverse drug reactions (ADRs) in 3 subjects (10.3%). Of the total 24 subjects who had full 12-week follow-up data, 16 (66.7%) showed decrease in PSA of any magnitude, and 9 (37.5%) showed a decrease in PSA by 50% or greater. A total of 5 of the 24 patients (20.8%) showed disease progression (PSA increase of 25% or higher from the baseline) at the 12th week following single dose of [177Lu]Ludotadipep. These data thus far suggest that [177Lu]Ludotadipep could be a promising RPT agent with low toxicity in mCRPC patients who have not been responsive to conventional treatments.

18F-FES PET/CT for Characterization of Brain and Leptomeningeal Metastasis in Double Primary Cancer Patient.

ABSTRACT: The clinical value of 16α-18F-fluoro-17 ß-estradiol (18F-FES) PET in breast cancer has been widely investigated because it can visualize estrogen receptor-expressing lesions. This relatively new radiotracer adds clinical values by characterization of metastasis in double primary cancer. It also has advantage in finding small brain lesions, which has no background brain activity. Here, we present 18F-FES PET findings of brain and leptomeningeal metastases in a patient with breast and lung malignancy.

Development of Amyloid PET Analysis Pipeline Using Deep Learning-Based Brain MRI Segmentation-A Comparative Validation Study.

Amyloid positron emission tomography (PET) scan is clinically essential for the non-invasive assessment of the presence and spatial distribution of amyloid-beta deposition in subjects with cognitive impairment suspected to have been a result of Alzheimer's disease. Quantitative assessment can enhance the interpretation reliability of PET scan; however, its clinical application has been limited due to the complexity of preprocessing. This study introduces a novel deep-learning-based approach for SUVR quantification that simplifies the preprocessing step and significantly reduces the analysis time. Using two heterogeneous amyloid ligands, our proposed method successfully distinguished standardized uptake value ratio (SUVR) between amyloidosis-positive and negative groups. The proposed method's intra-class correlation coefficients were 0.97 and 0.99 against PETSurfer and PMOD, respectively. The difference of global SUVRs between the proposed method and PETSurfer or PMOD were 0.04 and -0.02, which are clinically acceptable. The AUC-ROC exceeded 0.95 for three tools in the amyloid positive assessment. Moreover, the proposed method had the fastest processing time and had a low registration failure rate (1%). In conclusion, our proposed method calculates SUVR that is consistent with PETSurfer and PMOD, and has advantages of fast processing time and low registration failure rate. Therefore, PET quantification provided by our proposed method can be used in clinical practice.

Comparison of FDG PET/CT and Bone Marrow Biopsy Results in Patients with Diffuse Large B Cell Lymphoma with Subgroup Analysis of PET Radiomics.

Whether FDG PET/CT can replace bone marrow biopsy (BMBx) is undecided in patients with diffuse large B cell lymphoma (DLBCL). We compared the visual PET findings and PET radiomic features, with BMBx results. A total of 328 patients were included; 269 (82%) were PET-negative and 59 (18%) were PET-positive for bone lesions on visual assessment. A fair degree of agreement was present between PET and BMBx findings (ĸ = 0.362, p < 0.001). Bone involvement on PET/CT lead to stage IV in 12 patients, despite no other evidence of extranodal lesion. Of 35 discordant PET-positive and BMBx-negative cases, 22 (63%) had discrete bone uptake on PET/CT. A total of 144 patients were eligible for radiomic analysis, and two grey-level zone-length matrix derived parameters obtained from the iliac crests showed a trend for higher values in the BMBx-positive group compared to the BMBx-negative group (mean 436.6 ± 449.0 versus 227.2 ± 137.8, unadjusted p = 0.037 for high grey-level zone emphasis; mean 308.8 ± 394.4 versus 135.7 ± 97.2, unadjusted p = 0.048 for short-zone high grey-level emphasis), but statistical significance was not found after multiple comparison correction. Visual FDG PET/CT assessment and BMBx results were discordant in 17% of patients with newly diagnosed DLBCL, and the two tests are complementary in the evaluation of bone involvement.

Changes in treatment intent and target definition for preoperative radiotherapy after 18F-Fluorodeoxyglucose positron emission tomography in rectal cancer: A Meta-analysis.

PURPOSE: To evaluate the impact of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) on changes in treatment plan and target definition for preoperative radiotherapy in patients with rectal cancer. METHODS: Embase, PubMed, and Cochrane Library were searched up to November 2020 for all studies investigating the role of preoperative FDG PET in patients who underwent neoadjuvant radiotherapy before curative-intent surgery. The proportion of patients whose treatment plan (curative vs. palliative intent) or target definition was changed after FDG PET was analyzed. A random-effects model was used for pooled analysis. The change in target definition was compared between conventional radiological imaging-based target volume [gross tumor volume (GTV) or planning target volume (PTV)] and PET-based target volume (GTV or PTV) using the standardized mean difference (SMD) and 95% confidence interval (CI). RESULTS: A total of 336 patients from twelve studies were included. In eight studies, PET changed either the treatment intent or target definition in 24.8% of patients (95% CI 15.1% to 37.9%, I2 = 69%). In ten studies, the PET-based GTV was lower than the conventional imaging-based target volume (SMD -7.0, 95% CI -1.39 to -0.01). However, there was no significant difference between conventional imaging-based and PET-based PTV (SMD -0.07, 95% CI -0.75 to 0.62). In six studies evaluating the initial staging based on PET, the initial staging (nodal or metastasis status) was changed in 53 of 229 patients (23.1%). Newly detected or additional distant metastases were identified in 22 patients (9.6%) after FDG PET. CONCLUSION: The use of FDG PET influences radiotherapy planning in a fourth of patients with rectal cancer. FDG PET can provide additive information for accurate tumor delineation, although PET-based PTV did not significantly change. These findings suggest that FDG PET may be beneficial to patients with rectal cancer before establishing a radiotherapy plan.

Comparison of early F-18 Florbetaben PET/CT to Tc-99m ECD SPECT using voxel, regional, and network analysis.

This study aimed to validate early-phase F-18 Florbetaben positron emission tomography (eFBB PET) as a brain perfusion test and determine the optimal reference region. A total of 27 patients with early Parkinson's disease with Tc-99m ethyl cysteinate dimer single photon emission tomography (ECD SPECT) and FBB PET were included. Six reference regions, including whole brain (GN), pons, central white matter (CWM), whole cerebellum (WC), WC with brain stem (WC + B), and cerebellar grey matter (CG), were applied to obtain SUVR using cortex volume-of-interest (VOI). Reference regions of WC (r 0.886), WC + B (r 0.897), and CG (r 0.904) had highest correlation values of cortex-VOI SUVR between both perfusion images (all p < 0.001). Early-phase FBB PET had a significant linear correlation of CG-normalized SUVR of the cortex, basal ganglia, thalamus, and midbrain with ECD SPECT in voxel-wise analysis (FDR adjusted-p < 0.05). Early-phase FBB PET extracts more ICNS than ECD SPECT, as 9 ICNS and 4 ICNs, respectively. Both eFBB PET and ECD SPECT well discriminated PD from DLB (Area-under-curve of receiver-operating-characteristics, 0.911 for eFBB PET, 0.922 for ECD SPECT). Our findings suggest that eFBB PET is a reliable perfusion test based on a high correlation with ECD SPECT using cerebellum-based normalization methods.

Paradoxical Cerebral Perfusion in Parkinson's Disease Patients with Orthostatic Hypotension: A Dual-Phase 18F-Florbetaben Positron Emission Tomography Study.

BACKGROUND: Orthostatic hypotension (OH) may antedate Parkinson's disease (PD) or be found in early stages of the disease. OH may induce a PD brain to chronic hypotensive insults. 18F-Florbetaben (18F-FBB) tracer has a high first-pass influx rate and can be used with positron emission tomography (PET) as a surrogate marker for early- and late-phase evaluation of cerebral perfusion and cerebral amyloidosis, respectively. OBJECTIVE: In this study, we evaluated whether 18F-FBB uptake in the early- and late-phases of PD was related to OH. This study manipulated the imaging modality to illustrate the physiology of cerebral flow with OH in PD (PD + OH). METHODS: A group of 73 early-stage PD patients was evaluated with a head-up tilt-test and 18F-FBB PET imaging. The cognitive status was assessed by a comprehensive battery of neuropsychological tests. PET images were normalized, and both early- and late-phase standardized uptake value ratios (SUVRs) of pre-specified regions were obtained. The associations between regional SUVRs and OH and cognitive status were analyzed. RESULTS: Twenty (27.4%) participants had OH. Thirteen (17.8%) patients were interpreted as having amyloid pathology based on regional 18F-FBB uptake. Early-phase SUVRs were higher in specific brain regions of PD + OH patients than those without OH. However, late-phase SUVRs did not differ between the groups. The early-phase SUVRs were not influenced by amyloid burden or by interaction between amyloid and orthostatic hypotension. Cognitive functions were not disparate when PD + OH patients were contrasted with non-OH patients in this study. CONCLUSION: Cerebral blood flow was elevated in patients with early PD + OH. This finding suggests augmented cerebral perfusion in PD + OH might be a compensatory regulation in response to chronic OH.

Prognostic value of tumor metabolic imaging phenotype by FDG PET radiomics in HNSCC.

OBJECTIVE: Tumor metabolic phenotype can be assessed with integrated image pattern analysis of 18F-fluoro-deoxy-glucose (FDG) Positron Emission Tomography/Computed Tomography (PET/CT), called radiomics. This study was performed to assess the prognostic value of radiomics PET parameters in head and neck squamous cell carcinoma (HNSCC) patients. METHODS: 18F-fluoro-deoxy-glucose (FDG) PET/CT data of 215 patients from HNSCC collection free database in The Cancer Imaging Archive (TCIA), and 122 patients in Seoul St. Mary's Hospital with baseline FDG PET/CT for locally advanced HNSCC were reviewed. Data from TCIA database were used as a training cohort, and data from Seoul St. Mary's Hospital as a validation cohort. With the training cohort, primary tumors were segmented by Nestles' adaptive thresholding method. Segmental tumors in PET images were preprocessed using relative resampling of 64 bins. Forty-two PET parameters, including conventional parameters and texture parameters, were measured. Binary groups of homogeneous imaging phenotypes, clustered by K-means method, were compared for overall survival (OS) and disease-free survival (DFS) by log-rank test. Selected individual radiomics parameters were tested along with clinical factors, including age and sex, by Cox-regression test for OS and DFS, and the significant parameters were tested with multivariate analysis. Significant parameters on multivariate analysis were again tested with multivariate analysis in the validation cohort. RESULTS: A total of 119 patients, 70 from training, and 49 from validation cohort, were included in the study. The median follow-up period was 62 and 52 months for the training and the validation cohort, respectively. In the training cohort. binary groups with different metabolic radiomics phenotypes showed significant difference in OS (p = 0.036), and borderline difference in DFS (p = 0.086). Gray-Level Non-Uniformity for zone (GLNUGLZLM) was the most significant prognostic factor for both OS (hazard ratio [HR] 3.1, 95% confidence interval [CI] 1.4-7.3, p = 0.008) and DFS (HR 4.5, CI 1.3-16, p = 0.020). Multivariate analysis revealed GLNUGLZLM as an independent prognostic factor for OS (HR 3.7, 95% CI 1.1-7.5, p = 0.032). GLNUGLZLM remained as an independent prognostic factor in the validation cohort (HR 14.8. 95% CI 3.3-66, p < 0.001). CONCLUSIONS: Baseline FDG PET radiomics contain risk information for survival prognosis in HNSCC patients. The metabolic heterogeneity parameter, GLNUGLZLM, may assist clinicians in patient risk assessment as a feasible prognostic factor.

Tumor immune profiles noninvasively estimated by FDG PET with deep learning correlate with immunotherapy response in lung adenocarcinoma.

Rationale: The clinical application of biomarkers reflecting tumor immune microenvironment is hurdled by the invasiveness of obtaining tissues despite its importance in immunotherapy. We developed a deep learning-based biomarker which noninvasively estimates a tumor immune profile with fluorodeoxyglucose positron emission tomography (FDG-PET) in lung adenocarcinoma (LUAD). Methods: A deep learning model to predict cytolytic activity score (CytAct) using semi-automatically segmented tumors on FDG-PET trained by a publicly available dataset paired with tissue RNA sequencing (n = 93). This model was validated in two independent cohorts of LUAD: SNUH (n = 43) and The Cancer Genome Atlas (TCGA) cohort (n = 16). The model was applied to the immune checkpoint blockade (ICB) cohort, which consists of patients with metastatic LUAD who underwent ICB treatment (n = 29). Results: The predicted CytAct showed a positive correlation with CytAct of RNA sequencing in validation cohorts (Spearman rho = 0.32, p = 0.04 in SNUH cohort; spearman rho = 0.47, p = 0.07 in TCGA cohort). In ICB cohort, the higher predicted CytAct of individual lesion was associated with more decrement in tumor size after ICB treatment (Spearman rho = -0.54, p < 0.001). Higher minimum predicted CytAct in each patient associated with significantly prolonged progression free survival and overall survival (Hazard ratio 0.25, p = 0.001 and 0.18, p = 0.004, respectively). In patients with multiple lesions, ICB responders had significantly lower variance of predicted CytActs (p = 0.005). Conclusion: The deep learning model that predicts CytAct using FDG-PET of LUAD was validated in independent cohorts. Our approach may be used to noninvasively assess an immune profile and predict outcomes of LUAD patients treated with ICB.

Relationship of EGFR Mutation to Glucose Metabolic Activity and Asphericity of Metabolic Tumor Volume in Lung Adenocarcinoma.

PURPOSE: EGFR-mutation (EGFR-mt) is a major oncogenic driver mutation in lung adenocarcinoma (ADC) and is more often observed in Asian population. In lung ADC, some radiomics parameters of FDG PET have been reported to be associated with EGFR-mt. Here, the associations between EGFR-mt and PET parameters, particularly asphericity (ASP), were evaluated in Asian population. METHODS: Lung ADC patients who underwent curative surgical resection as the first treatment were retrospectively enrolled. EGFR mutation was defined as exon 19 deletion and exon 21 point mutation and was evaluated using surgical specimens. On FDG PET, image parameters of maximal standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and ASP were obtained. The parameters were compared between EGFR-mt and wild type (EGFR-wt) groups, and the relationships between these PET parameters and EGFR-mt were evaluated. RESULTS: A total of 64 patients (median age 66 years, M:F = 34:30) were included in the analysis, and 29 (45%) patients showed EGFR-mt. In EGFR-mt group, all the image parameters of SUVmax, MTV, TLG, and ASP were significantly lower than in EGFR-wt group (all adjusted P < 0.050). In univariable logistic regression, SUVmax (P = 0.003) and ASP (P = 0.010) were significant determinants for EGFR-mt, whereas MTV was not (P = 0.690). Multivariate analysis revealed that SUVmax and ASP are independent determinants for EGFR-mt, regardless of inclusion of MTV in the analysis (P < 0.05). CONCLUSION: In Asian NSCLC/ADC patients, SUVmax, MTV, and ASP on FDG PET are significantly related to EGFR mutation status. Particularly, low SUVmax and ASP are independent determinants for EGFR-mt.

A pan-cancer analysis of the clinical and genetic portraits of somatostatin receptor expressing tumor as a potential target of peptide receptor imaging and therapy.

PURPOSE: Although somatostatin receptor (SST) is a promising theranostic target and is widely expressed in tumors of various organs, the indication for therapies targeting SST is limited to typical gastroenteropancreatic neuroendocrine tumors (NETs). Thus, broadening the scope of the current clinical application of peptide receptor radiotherapy (PRRT) can be supported by a better understanding of the landscape of SST-expressing tumors. METHODS: SST expression levels were assessed in data from The Cancer Genome Atlas across 10,701 subjects representing 32 cancer types. As the major target of PRRT is SST subtype 2 (SST2), correlation analyses between the pan-cancer profiles, including clinical and genetic features, and SST2 level were conducted. The median SST2 expression level of pheochromocytoma and paraganglioma (PCPG) samples was used as the threshold to define "high-SST2 tumors." The prognostic value of SST2 in each cancer subtype was evaluated by using Cox proportional regression analysis. RESULTS: We constructed a resource of SST expression patterns associated with clinicopathologic features and genomic alterations. It provides an interactive tool to analyze SST expression patterns in various cancer types. As a result, eight of the 31 cancer subtypes other than PCPG had more than 5% of tumors with high-SST2 expression. Low-grade glioma (LGG) showed the highest proportion of high-SST2 tumors, followed by breast invasive carcinoma (BRCA). LGG showed different SST2 levels according to tumor grade and histology. IDH1 mutation was significantly associated with high-SST2 status. In BRCA, the SST2 level was different according to the hormone receptor status. High-SST2 status was significantly associated with good prognosis in LGG patients. High-SST2 status showed a trend for association with poor prognosis in triple-negative breast cancer subjects. CONCLUSION: A broad range of SST2 expression was observed across diverse cancer subtypes. The SST2 expression level showed a significant association with genomic and clinical aspects across cancers, especially in LGG and BRCA. These findings extend our knowledge base to diversify the indications for PRRT as well as SST imaging.

Basal and Acetazolamide Brain Perfusion SPECT in Internal Carotid Artery Stenosis.

Internal carotid artery (ICA) stenosis including Moyamoya disease needs revascularization when hemodynamic insufficiency is validated. Vascular reserve impairment was the key to find the indication for endarterectomy/bypass surgery in the atherosclerotic ICA stenosis and to determine the indication, treatment effect, and prognosis in Moyamoya diseases. Vascular reserve was quantitatively assessed by 1-day split-dose I-123 IMP basal/acetazolamide SPECT in Japan or by Tc-99m HMPAO SPECT in other countries using qualitative or semi-quantitative method. We summarized the development of 1-day basal/ acetazolamide brain perfusion SPECT for ICA stenosis, both quantitative and qualitative methods, and their methodological issues regarding (1) acquisition protocol; (2) qualitative assessment, either visual or deep learning-based; (3) clinical use for atherosclerotic ICA steno-occlusive diseases and mostly Moyamoya diseases; and (4) their impact on the choice of treatment options. Trials to use CT perfusion or perfusion MRI using contrast materials or arterial spin labeling were briefly discussed in their endeavor to use basal studies alone to replace acetazolamide-challenge SPECT. Theoretical and practical issues imply that basal perfusion evaluation, no matter how much sophisticated, will not disclose vascular reserve. Acetazolamide rarely causes serious adverse reactions but included fatality, and now, we need to monitor patients closely in acetazolamide-challenge studies.

Association of metabolic and genetic heterogeneity in head and neck squamous cell carcinoma with prognostic implications: integration of FDG PET and genomic analysis.

PURPOSE: The linkage between the genetic and phenotypic heterogeneity of the tumor has not been thoroughly evaluated. Herein, we investigated how the genetic and metabolic heterogeneity features of the tumor are associated with each other in head and neck squamous cell carcinoma (HNSC). We further assessed the prognostic significance of those features. METHODS: The mutant-allele tumor heterogeneity (MATH) score (n = 508), a genetic heterogeneity feature, and tumor glycolysis feature (GlycoS) (n = 503) were obtained from the HNSC dataset in the cancer genome atlas (TCGA). We identified matching patients (n = 33) who underwent 18F-fluorodeoxyglucose positron emission tomography (FDG PET) from the cancer imaging archive (TCIA) and obtained the following information from the primary tumor: metabolic, metabolic-volumetric, and metabolic heterogeneity features. The association between the genetic and metabolic features and their prognostic values were assessed. RESULTS: Tumor metabolic heterogeneity and metabolic-volumetric features showed a mild degree of association with MATH (n = 25, ρ = 0.4~0.5, P < 0.05 for all features). The patients with higher FDG PET features and MATH died sooner. Combination of MATH and tumor metabolic heterogeneity features showed a better stratification of prognosis than MATH. Also, higher MATH and GlycoS were associated with significantly worse overall survival (n = 499, P = 0.002 and 0.0001 for MATH and GlycoS, respectively). Furthermore, both MATH and GlycoS independently predicted overall survival after adjusting for clinicopathologic features and the other (P = 0.015 and 0.006, respectively). CONCLUSION: Both tumor metabolic heterogeneity and metabolic-volumetric features assessed by FDG PET showed a mild degree of association with genetic heterogeneity in HNSC. Both metabolic and genetic heterogeneity features were predictive of survival and there was an additive prognostic value when the metabolic and genetic heterogeneity features were combined. Also, MATH and GlycoS were independent prognostic factors in HNSC; they can be used for precise prognostication once validated.

Perspectives in Radiomics for Personalized Medicine and Theranostics.

Radiomics handles imaging biomarker from high-throughput feature extraction through complex pattern recognition that is difficult for human to process. Recent medical paradigms are rapidly changing to personalized medicine, including molecular targeted therapy, immunotherapy, and theranostics, and the importance of biomarkers for these is growing day by day. Even though biopsy continues to gold standard for tumor assessment in personalized medicine, imaging is expected to complement biopsy because it allows whole tumor evaluation, whole body evaluation, and non-invasive and repetitive evaluation. Radiomics is known as a useful method to get imaging biomarkers related to intratumor heterogeneity in molecular targeted therapy as well as one-size-fits-all therapy. It is also expected to be useful in new paradigms such as immunotherapy and somatostatin receptor (SSTR) or prostate-specific membrane antigen (PSMA)-targeted theranostics. Radiomics research should move to multimodality (CT, MR, PET, etc.), multicenter, and prospective studies from current single modality, single institution, and retrospective studies. Image-quality harmonization, intertumor heterogeneity, and integrative analysis of information from different scales are thought to be important keywords in future radiomics research. It is clear that radiomics will play an important role in personalized medicine.

Radiomics in Oncological PET/CT: a Methodological Overview.

Radiomics is a medical imaging analysis approach based on computer-vision. Metabolic radiomics in particular analyses the spatial distribution patterns of molecular metabolism on PET images. Measuring intratumoral heterogeneity via image is one of the main targets of radiomics research, and it aims to build a image-based model for better patient management. The workflow of radiomics using texture analysis follows these steps: 1) imaging (image acquisition and reconstruction); 2) preprocessing (segmentation & quantization); 3) quantification (texture matrix design & texture feature extraction); and 4) analysis (statistics and/or machine learning). The parameters or conditions at each of these steps are effect on the results. In statistical testing or modeling, problems such as multiple comparisons, dependence on other variables, and high dimensionality of small sample size data should be considered. Standardization of methodology and harmonization of image quality are one of the most important challenges with radiomics methodology. Even though there are current issues in radiomics methodology, it is expected that radiomics will be clinically useful in personalized medicine for oncology.