Evaluation of thresholding methods for the quantification of [68Ga]Ga-PSMA-11 PET molecular tumor volume and their effect on survival prediction in patients with advanced prostate cancer undergoing [177Lu]Lu-PSMA-617 radioligand therapy.

PURPOSE: The aim of this study was to systematically evaluate the effect of thresholding algorithms used in computer vision for the quantification of prostate-specific membrane antigen positron emission tomography (PET) derived tumor volume (PSMA-TV) in patients with advanced prostate cancer. The results were validated with respect to the prognostication of overall survival in patients with advanced-stage prostate cancer. MATERIALS AND METHODS: A total of 78 patients who underwent [177Lu]Lu-PSMA-617 radionuclide therapy from January 2018 to December 2020 were retrospectively included in this study. [68Ga]Ga-PSMA-11 PET images, acquired prior to radionuclide therapy, were used for the analysis of thresholding algorithms. All PET images were first analyzed semi-automatically using a pre-evaluated, proprietary software solution as the baseline method. Subsequently, five histogram-based thresholding methods and two local adaptive thresholding methods that are well established in computer vision were applied to quantify molecular tumor volume. The resulting whole-body molecular tumor volumes were validated with respect to the prognostication of overall patient survival as well as their statistical correlation to the baseline methods and their performance on standardized phantom scans. RESULTS: The whole-body PSMA-TVs, quantified using different thresholding methods, demonstrate a high positive correlation with the baseline methods. We observed the highest correlation with generalized histogram thresholding (GHT) (Pearson r (r), p value (p): r = 0.977, p < 0.001) and Sauvola thresholding (r = 0.974, p < 0.001) and the lowest correlation with Multiotsu (r = 0.877, p < 0.001) and Yen thresholding methods (r = 0.878, p < 0.001). The median survival time of all patients was 9.87 months (95% CI [9.3 to 10.13]). Stratification by median whole-body PSMA-TV resulted in a median survival time from 11.8 to 13.5 months for the patient group with lower tumor burden and 6.5 to 6.6 months for the patient group with higher tumor burden. The patient group with lower tumor burden had significantly higher probability of survival (p < 0.00625) in eight out of nine thresholding methods (Fig. 2); those methods were SUVmax50 (p = 0.0038), SUV ≥3 (p = 0.0034), Multiotsu (p = 0.0015), Yen (p = 0.0015), Niblack (p = 0.001), Sauvola (p = 0.0001), Otsu (p = 0.0053), and Li thresholding (p = 0.0053). CONCLUSION: Thresholding methods commonly used in computer vision are promising tools for the semiautomatic quantification of whole-body PSMA-TV in [68Ga]Ga-PSMA-11-PET. The proposed algorithm-driven thresholding strategy is less arbitrary and less prone to biases than thresholding with predefined values, potentially improving the application of whole-body PSMA-TV as an imaging biomarker.

Towards a fast PET/MRI protocol for breast cancer imaging: maintaining diagnostic confidence while reducing PET and MRI acquisition times.

OBJECTIVES: To investigate the diagnostic feasibility of a shortened breast PET/MRI protocol in breast cancer patients. METHODS: Altogether 90 women with newly diagnosed T1tumor-staged (T1ts) and T2tumor-staged (T2ts) breast cancer were included in this retrospective study. All underwent a dedicated comprehensive breast [18F]FDG-PET/MRI. List-mode PET data were retrospectively reconstructed with 20, 15, 10, and 5 min for each patient to simulate the effect of reduced PET acquisition times. The SUVmax/mean of all malign breast lesions was measured. Furthermore, breast PET data reconstructions were analyzed regarding image quality, lesion detectability, signal-to-noise ratio (SNR), and image noise (IN). The simultaneously acquired comprehensive MRI protocol was then shortened by retrospectively removing sequences from the protocol. Differences in malignant breast lesion detectability between the original and the fast breast MRI protocol were evaluated lesion-based. The 20-min PET reconstructions and the original MRI protocol served as reference. RESULTS: In all PET reconstructions, 127 congruent breast lesions could be detected. Group comparison and T1ts vs. T2ts subgroup comparison revealed no significant difference of subjective image quality between 20, 15, 10, and 5 min acquisition times. SNR of qualitative image evaluation revealed no significant difference between different PET acquisition times. A slight but significant increase of IN with decreasing PET acquisition times could be detected. Lesion SUVmax group comparison between all PET acquisition times revealed no significant differences. Lesion-based evaluation revealed no significant difference in breast lesion detectability between original and fast breast MRI protocols. CONCLUSIONS: Breast [18F]FDG-PET/MRI protocols can be shortened from 20 to below 10 min without losing essential diagnostic information. KEY POINTS: • A highly accurate breast cancer evaluation is possible by the shortened breast [18F]FDG-PET/MRI examination protocol. • Significant time saving at breast [18F]FDG-PET/MRI protocol could increase patient satisfaction and patient throughput for breast cancer patients at PET/MRI.

Simultaneous multislice diffusion-weighted imaging versus standard diffusion-weighted imaging in whole-body PET/MRI.

OBJECTIVE: To compare standard (STD-DWI) single-shot echo-planar imaging DWI and simultaneous multislice (SMS) DWI during whole-body positron emission tomography (PET)/MRI regarding acquisition time, image quality, and lesion detection. METHODS: Eighty-three adults (47 females, 57%), median age of 64 years (IQR 52-71), were prospectively enrolled from August 2018 to March 2020. Inclusion criteria were (a) abdominal or pelvic tumors and (b) PET/MRI referral from a clinician. Patients were excluded if whole-body acquisition of STD-DWI and SMS-DWI sequences was not completed. The evaluated sequences were axial STD-DWI at b-values 50-400-800 s/mm2 and the apparent diffusion coefficient (ADC), and axial SMS-DWI at b-values 50-300-800 s/mm2 and ADC, acquired with a 3-T PET/MRI scanner. Three radiologists rated each sequence's quality on a five-point scale. Lesion detection was quantified using the anatomic MRI sequences and PET as the reference standard. Regression models were constructed to quantify the association between all imaging outcomes/scores and sequence type. RESULTS: The median whole-body STD-DWI acquisition time was 14.8 min (IQR 14.1-16.0) versus 7.0 min (IQR 6.7-7.2) for whole-body SMS-DWI, p < 0.001. SMS-DWI image quality scores were higher than STD-DWI in the abdomen (OR 5.31, 95% CI 2.76-10.22, p < 0.001), but lower in the cervicothoracic junction (OR 0.21, 95% CI 0.10-0.43, p < 0.001). There was no significant difference in the chest, mediastinum, pelvis, and rectum. STD-DWI detected 276/352 (78%) lesions while SMS-DWI located 296/352 (84%, OR 1.46, 95% CI 1.02-2.07, p = 0.038). CONCLUSIONS: In cancer staging and restaging, SMS-DWI abbreviates acquisition while maintaining or improving the diagnostic yield in most anatomic regions. KEY POINTS: • Simultaneous multislice diffusion-weighted imaging enables faster whole-body image acquisition. • Simultaneous multislice diffusion-weighted imaging maintains or improves image quality when compared to single-shot echo-planar diffusion-weighted imaging in most anatomical regions. • Simultaneous multislice diffusion-weighted imaging leads to superior lesion detection.

"A net for everyone": fully personalized and unsupervised neural networks trained with longitudinal data from a single patient.

BACKGROUND: With the rise in importance of personalized medicine and deep learning, we combine the two to create personalized neural networks. The aim of the study is to show a proof of concept that data from just one patient can be used to train deep neural networks to detect tumor progression in longitudinal datasets. METHODS: Two datasets with 64 scans from 32 patients with glioblastoma multiforme (GBM) were evaluated in this study. The contrast-enhanced T1w sequences of brain magnetic resonance imaging (MRI) images were used. We trained a neural network for each patient using just two scans from different timepoints to map the difference between the images. The change in tumor volume can be calculated with this map. The neural networks were a form of a Wasserstein-GAN (generative adversarial network), an unsupervised learning architecture. The combination of data augmentation and the network architecture allowed us to skip the co-registration of the images. Furthermore, no additional training data, pre-training of the networks or any (manual) annotations are necessary. RESULTS: The model achieved an AUC-score of 0.87 for tumor change. We also introduced a modified RANO criteria, for which an accuracy of 66% can be achieved. CONCLUSIONS: We show a novel approach to deep learning in using data from just one patient to train deep neural networks to monitor tumor change. Using two different datasets to evaluate the results shows the potential to generalize the method.

The future of radiosynoviorthesis: bright or bleak?

Radiosynoviorthesis (RSO) is a decades known, effective intra-articular nuclear medicine local therapy, with few rare side-effects, in which inflamed synovial membrane is treated by means of colloidal beta-emitters. There are major variations worldwide in terms of acceptance, frequency of use and approved indications for this procedure. Thus, reliable figures that reflect reality are only available for a few countries. A Europe-wide survey revealed that RSO is carried out most frequently in Germany, where RSO is the most common nuclear medicine therapy with about 70,000 joints treated per year. The main indications include synovitis due to rheumatoid arthritis, hemophilia and pigmented villonodular synovitis (PVNS), and depending on national approvals, osteoarthritis. Despite the many indications, there are very few published scientific studies and therefore, RSO evidence is lacking. Reliable data on the clinical usage of RSO and demographics of RSO specialists are only available in Germany, thus we discuss the future challenges of RSO mainly from a German perspective. In the German healthcare system, RSO is performed primarily on an outpatient basis and plays only a minor role in the university setting. The necessary expertise for RSO is therefore lacking, for the most part, at university training centers. Currently, nearly more than three quarters of the German RSO experts are over fifty years old, illustrating a shortage of young talent. In the future, RSO providers from the non-university or private sector will have to cooperate with universities through networks and will have to intensify their cooperation with referring physicians, such as rheumatologist and orthopedic surgeons, and patients in order to maintain a timely and beneficial exchange of information. In networks of RSO experts, the participants must jointly develop and establish training concepts and facilities for future talents, elaborate on guidelines, if clinically useful expand the range of indications, initiate studies to generate further evidence and finally make the procedure more public. In addition, it is worthwhile to apply this process beyond human medicine to other fields, such as medical physics and veterinary medicine. If these points are implemented, the future of RSO will be bright, if it fails, it looks bleak.

PET tracers in musculoskeletal disease beyond FDG.

Musculoskeletal tumors comprise a multitude of tumor entities with different grades of malignancy, biological behavior, and therapeutic options. Positron emission tomography (PET) using the glucose analog [18F]fluorodeoxyglucose (FDG) is an established imaging modality for detection and staging of cancer, despite some shortcomings. Numerous studies have evaluated the role of PET imaging musculoskeletal tumors beyond FDG. The use of more specific novel PET radiopharmaceuticals such as the proliferation marker [18F]fluorodeoxythymidine (FLT), the bone-imaging agent [18F]sodium fluoride, amino acid tracers ([11C]methionine, [18F]fluoroethyltyrosine), or biomarkers of neoangiogenesis ([18F]galacto-RGD) can potentially provide insights into the biology of musculoskeletal tumors with focus on tumor grading, treatment monitoring, posttherapy assessment, and estimation of individual prognosis. In this article, we review the potential role of these alternative PET tracers in musculoskeletal disorders with emphasis on oncologic applications.

GAN-based generation of realistic 3D volumetric data: A systematic review and taxonomy.

With the massive proliferation of data-driven algorithms, such as deep learning-based approaches, the availability of high-quality data is of great interest. Volumetric data is very important in medicine, as it ranges from disease diagnoses to therapy monitoring. When the dataset is sufficient, models can be trained to help doctors with these tasks. Unfortunately, there are scenarios where large amounts of data is unavailable. For example, rare diseases and privacy issues can lead to restricted data availability. In non-medical fields, the high cost of obtaining enough high-quality data can also be a concern. A solution to these problems can be the generation of realistic synthetic data using Generative Adversarial Networks (GANs). The existence of these mechanisms is a good asset, especially in healthcare, as the data must be of good quality, realistic, and without privacy issues. Therefore, most of the publications on volumetric GANs are within the medical domain. In this review, we provide a summary of works that generate realistic volumetric synthetic data using GANs. We therefore outline GAN-based methods in these areas with common architectures, loss functions and evaluation metrics, including their advantages and disadvantages. We present a novel taxonomy, evaluations, challenges, and research opportunities to provide a holistic overview of the current state of volumetric GANs.

(18) F-fluorodeoxyglucose positron emission tomography/computed tomography for the detection of recurrent bone and soft tissue sarcoma.

BACKGROUND: The clinical utility of modern hybrid imaging modalities for detecting recurrent bone or soft tissue sarcoma remains to be determined. In this report, the authors present a clinical study on the diagnostic accuracy and incremental value of integrated (18) F-fluorodeoxyglucose positron emission tomography/computed tomography ((18) F-FDG PET/CT) in patients with a history of sarcoma who have clinically suspected disease recurrence. METHODS: Forty-three patients who had a history of bone or soft tissue sarcoma and had documented complete remission underwent (18) F-FDG PET/CT. Image analysis was performed independently for (18) F-FDG PET (n = 43) and for contrast-enhanced spiral CT (CE-CT) (n = 30) by 2 separate readers, whereas combined (18) F-FDG PET/CT (n = 43) images were analyzed in consensus by both readers. Imaging findings were rated on a 5-point scale and finally were reported as malignant, benign, or equivocal. Imaging findings were validated either by histopathology (n = 24) or by clinical follow-up (n = 19). RESULTS: (18) F-FDG PET/CT had greater sensitivity and specificity compared with CE-CT alone (94% and 92% vs 78% and 67%, respectively), resulting in significantly greater accuracy (93% vs 73%; P = .03). (18) F-FDG PET/CT was particularly superior regarding detection of local recurrence or soft tissue lesions (sensitivity and specificity: 83% and 100% vs 50% and 100%, respectively) or bone metastases (100% and 100% vs 85% and 88%, respectively). CONCLUSIONS: (18) F-FDG PET/CT had greater diagnostic accuracy in the detection of recurrent bone or soft tissue sarcoma compared with CE-CT alone. The detection of local recurrence was the most evident advantage of (18) F-FDG PET/CT over CE-CT. Cancer 2013. © 2012 American Cancer Society.

Positive Prostate-specific Membrane Antigen Findings: How To Interpret Them.

Prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) is more accurate than conventional imaging for primary staging of high-risk prostate cancer and localization of biochemical recurrence. Knowledge of PSMA expression patterns and standardized reporting facilitate accurate interpretation of positive PSMA findings. PSMA PET/CT should be adopted as part of clinical routine, as recommended in international guidelines.

Molecular Imaging of Lymphoma: Future Directions and Perspectives.

More than 250,000 patients die from Hodgkin or non-Hodgkin lymphoma each year. Currently, molecular imaging with 18F-FDG-PET/CT is the standard of care for lymphoma staging and therapy response assessment. In this review, we will briefly summarize the role of molecular imaging for lymphoma diagnosis, staging, outcome prediction, and prognostication. We discuss future directions in response assessment and surveillance with quantitative PET parameters, the utility of interim assessment, and the differences with response assessment to immunomodulatory therapy. Lastly, we will cover innovations in the field regarding novel tracers and artificial intelligence.

Clinical Translation of Targeted α-Therapy: An Evolution or a Revolution?

The field of radioligand therapy has advanced greatly in recent years, driven largely by ß-emitting therapies targeting somatostatin receptor-expressing tumors and the prostate-specific membrane antigen. Now, more clinical trials are under way to evaluate α-emitting targeted therapies as potential next-generation theranostics with even higher efficacy due to their high linear energy and short range in human tissues. In this review, we summarize the important studies ranging from the first Food and Drug Administration-approved α-therapy, 223Ra-dichloride, for treatment of bone metastases in castration-resistant prostate cancer, including concepts in clinical translation such as targeted α-peptide receptor radiotherapy and 225Ac-PSMA-617 for treatment of prostate cancer, innovative therapeutic models evaluating new targets, and combination therapies. Targeted α-therapy is one of the most promising fields in novel targeted cancer therapy, with several early- and late-stage clinical trials for neuroendocrine tumors and metastatic prostate cancer already in progress, along with significant interest and investment in additional early-phase studies. Together, these studies will help us understand the short- and long-term toxicity of targeted α-therapy and potentially identify suitable therapeutic combination partners.

Novel 68Ga-FAPI PET/CT Offers Oncologic Staging Without COVID-19 Vaccine-Related Pitfalls.

In the setting of ongoing coronavirus disease 2019 vaccination, vaccine-related tracer uptake in locoregional lymph nodes has become a well-known issue in tumor staging by 18F-FDG PET/CT. 68Ga-fibroblast-activation protein inhibitor (FAPI) PET/CT is a new oncologic imaging tool that may overcome this limitation. Methods: We assessed postvaccine head-to-head and same-day 18F-FDG and 68Ga-FAPI-46 PET/CT findings in a series of 11 patients from a large, prospective imaging registry. All patients with documented tracer uptake in locoregional lymph nodes on PET/CT or PET/MRI, after vaccination within 6 wk, were eligible for investigation. Result: Significant visual lymph node uptake adjacent to the injection site was noted in 11 of 11 (100%) patients with 18F-FDG PET/CT, versus 0 of 11 (0%) with 68Ga-FAPI PET/CT. 18F-FDG detected 73% and 68Ga-FAPI PET/CT 94% of all tumor lesions. Conclusion: In this case-series study, 68Ga-FAPI showed its potential to avoid 18F-FDG PET/CT postvaccination pitfalls and presented superior tumor localization.

Novel measures for the diagnosis of hepatic steatosis using contrast-enhanced computer tomography images.

PURPOSE: Hepatic steatosis is often diagnosed non-invasively. Various measures and accompanying diagnostic thresholds based on contrast-enhanced CT and virtual non-contrast images have been proposed. We compare these established criteria to novel and fully automated measures. METHOD: CT data sets of 197 patients were analyzed. Regions of interest (ROIs) were manually drawn for the liver, spleen, portal vein, and aorta to calculate four established measures of liver-fat. Two novel measures capturing the deviation between the empirical distributions of HU measurements across all voxels within the liver and spleen were calculated. These measures were calculated with both manual ROIs and using fully automated organ segmentations. Agreement between the different measures was evaluated using correlational analysis, as well as their ability to discriminate between fatty and healthy liver. RESULTS: Established and novel measures of fatty liver were at a high level of agreement. Novel methods were statistically indistinguishable from the established ones when taking established diagnostic thresholds or physicians' diagnoses as ground truth and this high performance level persisted for automatically selected ROIs. CONCLUSION: Automatically generated organ segmentations led to comparable results as manual ROIs, suggesting that the implementation of automated methods can prove to be a valuable tool for incidental diagnosis. Differences in the distribution of HU measurements across voxels between liver and spleen can serve as surrogate markers for the liver-fat-content. Novel measures do not exhibit a measurable disadvantage over established methods based on simpler measures such as across-voxel averages in a population with low incidence of fatty liver.

Non-exposed endoscopic wall-inversion surgery with one-step nucleic acid amplification for early gastrointestinal tumors: Personal experience and literature review.

BACKGROUND: Laparoscopic and endoscopic cooperative surgery is a safe, organ-sparing surgery that achieves full-thickness resection with adequate margins. Recent studies have demonstrated the safety and efficacy of these procedures. However, these techniques are limited by the exposure of the tumor and mucosa to the peritoneal cavity, which could lead to viable cancer cell seeding and the spillage of gastric juice or enteric liquids into the peritoneal cavity. Non-exposed endoscopic wall-inversion surgery (NEWS) is highly accurate in determining the resection margins to prevent intraperitoneal contamination because the tumor is inverted into the visceral lumen instead of the peritoneal cavity. Accurate intraoperative assessment of the nodal status could allow stratification of the extent of resection. One-step nucleic acid amplification (OSNA) can provide a rapid method of evaluating nodal tissue, whilst near-infrared laparoscopy together with indocyanine green can identify relevant nodal tissue intraoperatively. AIM: To determine the safety and feasibility of NEWS in early gastric and colon cancers and of adding rapid intraoperative lymph node (LN) assessment with OSNA. METHODS: The patient-based experiential portion of our investigations was conducted at the General and Oncological Surgery Unit of the St. Giuseppe Moscati Hospital (Avellino, Italy). Patients with early-stage gastric or colon cancer (diagnosed via endoscopy, endoscopic ultrasound, and computed tomography) were included. All lesions were treated by NEWS procedure with intraoperative OSNA assay between January 2022 and October 2022. LNs were examined intraoperatively with OSNA and postoperatively with conventional histology. We analyzed patient demographics, lesion features, histopathological diagnoses, R0 resection (negative margins) status, adverse events, and follow-up results. Data were collected prospectively and analyzed retrospectively. RESULTS: A total of 10 patients (5 males and 5 females) with an average age of 70.4 ± 4.5 years (range: 62-78 years) were enrolled in this study. Five patients were diagnosed with gastric cancer. The remaining 5 patients were diagnosed with early-stage colon cancer. The mean tumor diameter was 23.8 ± 11.6 mm (range: 15-36 mm). The NEWS procedure was successful in all cases. The mean procedure time was 111.5 ± 10.7 min (range: 80-145 min). The OSNA assay revealed no LN metastases in any patients. Histologically complete resection (R0) was achieved in 9 patients (90.0%). There was no recurrence during the follow-up period. CONCLUSION: NEWS combined with sentinel LN biopsy and OSNA assay is an effective and safe technique for the removal of selected early gastric and colon cancers in which it is not possible to adopt conventional endoscopic resection techniques. This procedure allows clinicians to acquire additional information on the LN status intraoperatively.

Histology-Based Prediction of Therapy Response to Neoadjuvant Chemotherapy for Esophageal and Esophagogastric Junction Adenocarcinomas Using Deep Learning.

PURPOSE: Quantifying treatment response to gastroesophageal junction (GEJ) adenocarcinomas is crucial to provide an optimal therapeutic strategy. Routinely taken tissue samples provide an opportunity to enhance existing positron emission tomography-computed tomography (PET/CT)-based therapy response evaluation. Our objective was to investigate if deep learning (DL) algorithms are capable of predicting the therapy response of patients with GEJ adenocarcinoma to neoadjuvant chemotherapy on the basis of histologic tissue samples. METHODS: This diagnostic study recruited 67 patients with I-III GEJ adenocarcinoma from the multicentric nonrandomized MEMORI trial including three German university hospitals TUM (University Hospital Rechts der Isar, Munich), LMU (Hospital of the Ludwig-Maximilians-University, Munich), and UME (University Hospital Essen, Essen). All patients underwent baseline PET/CT scans and esophageal biopsy before and 14-21 days after treatment initiation. Treatment response was defined as a ≥35% decrease in SUVmax from baseline. Several DL algorithms were developed to predict PET/CT-based responders and nonresponders to neoadjuvant chemotherapy using digitized histopathologic whole slide images (WSIs). RESULTS: The resulting models were trained on TUM (n = 25 pretherapy, n = 47 on-therapy) patients and evaluated on our internal validation cohort from LMU and UME (n = 17 pretherapy, n = 15 on-therapy). Compared with multiple architectures, the best pretherapy network achieves an area under the receiver operating characteristic curve (AUROC) of 0.81 (95% CI, 0.61 to 1.00), an area under the precision-recall curve (AUPRC) of 0.82 (95% CI, 0.61 to 1.00), a balanced accuracy of 0.78 (95% CI, 0.60 to 0.94), and a Matthews correlation coefficient (MCC) of 0.55 (95% CI, 0.18 to 0.88). The best on-therapy network achieves an AUROC of 0.84 (95% CI, 0.64 to 1.00), an AUPRC of 0.82 (95% CI, 0.56 to 1.00), a balanced accuracy of 0.80 (95% CI, 0.65 to 1.00), and a MCC of 0.71 (95% CI, 0.38 to 1.00). CONCLUSION: Our results show that DL algorithms can predict treatment response to neoadjuvant chemotherapy using WSI with high accuracy even before therapy initiation, suggesting the presence of predictive morphologic tissue biomarkers.

Voxel-Based Dosimetry Predicts Hepatotoxicity in Hepatocellular Carcinoma Patients Undergoing Radioembolization with 90Y Glass Microspheres.

Personalized dosimetry holds promise to improve radioembolization treatment outcomes in hepatocellular carcinoma (HCC) patients. To this end, tolerance absorbed doses for nontumor liver tissue are assessed by calculating the mean absorbed dose to the whole nontumor liver tissue (AD-WNTLT), which may be limited by its neglect of nonuniform dose distribution. Thus, we analyzed whether voxel-based dosimetry could be more accurate in predicting hepatotoxicity in HCC patients undergoing radioembolization. Methods: In total, 176 HCC patients were available for this retrospective analysis; of these, 78 underwent partial- and 98 whole-liver treatment. Posttherapeutic changes in bilirubin were graded using the Common Terminology Criteria for Adverse Events. We performed voxel-based and multicompartment dosimetry using pretherapeutic 99mTc-labeled human serum albumin SPECT and contrast-enhanced CT/MRI and defined the following dosimetry parameters: AD-WNTLT; the nontumor liver tissue volume exposed to at least 20 Gy (V20), at least 30 Gy (V30), and at least 40 Gy (V40); and the threshold absorbed dose to the 20% (AD-20) and 30% (AD-30) of nontumor liver tissue with the lowest absorbed dose. Their impact on hepatotoxicity after 6 mo was analyzed using the area under the receiver-operating-characteristic curve; thresholds were identified using the Youden index. Results: The area under the curve for prediction of posttherapeutic grade 3+ increases in bilirubin was acceptable for V20 (0.77), V30 (0.78), and V40 (0.79), whereas it was low for AD-WNTLT (0.67). The predictive value could further be increased in the subanalysis of patients with whole-liver treatment, where a good discriminatory power was found for V20 (0.80), V30 (0.82), V40 (0.84), AD-20 (0.80), and AD-30 (0.82) and an acceptable discriminatory power was found for AD-WNTLT (0.63). The accuracies of V20 (P = 0.03), V30 (P = 0.009), V40 (P = 0.004), AD-20 (P = 0.04), and AD-30 (P = 0.02) were superior to that of AD-WNTLT but did not differ significantly from each other. The respective thresholds were 78% (V30), 72% (V40), and 43 Gy (AD-30). Statistical significance was not reached for partial-liver treatment. Conclusion: Voxel-based dosimetry may more accurately predict hepatotoxicity than multicompartment dosimetry in HCC patients undergoing radioembolization, which could enable dose escalation or deescalation with the intent to optimize treatment response. Our results indicate that a V40 of 72% may be particularly useful in whole-liver treatment. However, further research is warranted to validate these results.

Oncologic Staging with 68Ga-FAPI PET/CT Demonstrates a Lower Rate of Nonspecific Lymph Node Findings Than 18F-FDG PET/CT.

Nonspecific lymph node uptake on 18F-FDG PET/CT imaging is a significant pitfall for tumor staging. Fibroblast activation protein α expression on cancer-associated fibroblasts and some tumor cells is less sensitive to acute inflammatory stimuli, and fibroblast activation protein-directed PET may overcome this limitation. Methods: Eighteen patients from our prospective observational study underwent 18F-FDG and 68Ga fibroblast activation protein inhibitor (FAPI) PET/CT scans within a median of 2 d (range, 0-22 d). Lymph nodes were assessed on histopathology and compared with SUV measurements. Results: On a per-patient basis, lymph nodes were rated malignant in 10 (56%) versus 7 (39%) patients by 18F-FDG PET/CT versus 68Ga-FAPI PET/CT scans, respectively, with a respective accuracy of 55% versus 94% for true lymph node metastases. Five of 6 (83%) false-positive nodes on the 18F-FDG PET/CT scans were rated true negative by the 68Ga-FAPI PET/CT scans. On a per-lesion basis, tumor detection rates were similar (85/89 lesions, 96%). Conclusion: 68Ga-FAPI PET/CT imaging demonstrated higher accuracy for true nodal involvement and therefore has the potential to replace 18F-FDG PET/CT imaging for cancer staging.

COVID-19 Pandemic: What Have We Learned and What to Expect in the Future?

The COVID-19 pandemic resulted in an unprecedented and unexpected challenge for societies and healthcare systems, including nuclear medicine providers. This article summarizes the major events imposed on nuclear medicine by COVID-19 from a global perspective, focuses on the major lessons learned regarding attitude, medical procedures, organizational implications and strategical considerations, and then discusses what to expect (and how to prepare) for the future. While the look back to what has happened is clearly evidence based, the look ahead and the conclusions drawn require the disclaimer of only representing the personal opinion and prediction of the authors. The COVID-19 pandemic relentlessly revealed deficiencies on an organizational, systematic and leadership level in nuclear medicine and beyond. Crisis gives us the opportunity to learn and furthermore perpare for the future. The authors' take home messages include the recommendation to focus on developing a culture of responsibility and ownership as opposed to blame, strengthening teams and communication, adapting existing structures based on the lessons learned during COVID-19, as well as establishing an environment of active decision making, prioritizing proposal of solutions rather than simply stating problems, incentivizing support and collaboration, not opposition.

Role of one-step nucleic acid amplification in colorectal cancer lymph node metastases detection.

Current histopathological staging procedures in colorectal cancer (CRC) depend on midline division of the lymph nodes (LNs) with one section of hematoxylin and eosin staining. Cancer cells outside this transection line may be missed, which could lead to understaging of Union for International Cancer Control Stage II high-risk patients. The one-step nucleic acid amplification (OSNA) assay has emerged as a rapid molecular diagnostic tool for LN metastases detection. It is a molecular technique that can analyze the entire LN tissue using a reverse-transcriptase loop-mediated isothermal amplification reaction to detect tumor-specific cytokeratin 19 mRNA. Our findings suggest that the OSNA assay has a high diagnostic accuracy in detecting metastatic LNs in CRC and a high negative predictive value. OSNA is a standardized, observer-independent technique, which may lead to more accurate staging. It has been suggested that in stage II CRC, the upstaging can reach 25% and these patients can access postoperative adjuvant chemotherapy. Moreover, intraoperative OSNA sentinel node evaluation may allow early CRC to be treated with organ-preserving surgery, while in more advanced-stage disease, a tailored lymphadenectomy can be performed considering the presence of aberrant lymphatic drainage and skip metastases.

Medical deep learning-A systematic meta-review.

Deep learning has remarkably impacted several different scientific disciplines over the last few years. For example, in image processing and analysis, deep learning algorithms were able to outperform other cutting-edge methods. Additionally, deep learning has delivered state-of-the-art results in tasks like autonomous driving, outclassing previous attempts. There are even instances where deep learning outperformed humans, for example with object recognition and gaming. Deep learning is also showing vast potential in the medical domain. With the collection of large quantities of patient records and data, and a trend towards personalized treatments, there is a great need for automated and reliable processing and analysis of health information. Patient data is not only collected in clinical centers, like hospitals and private practices, but also by mobile healthcare apps or online websites. The abundance of collected patient data and the recent growth in the deep learning field has resulted in a large increase in research efforts. In Q2/2020, the search engine PubMed returned already over 11,000 results for the search term 'deep learning', and around 90% of these publications are from the last three years. However, even though PubMed represents the largest search engine in the medical field, it does not cover all medical-related publications. Hence, a complete overview of the field of 'medical deep learning' is almost impossible to obtain and acquiring a full overview of medical sub-fields is becoming increasingly more difficult. Nevertheless, several review and survey articles about medical deep learning have been published within the last few years. They focus, in general, on specific medical scenarios, like the analysis of medical images containing specific pathologies. With these surveys as a foundation, the aim of this article is to provide the first high-level, systematic meta-review of medical deep learning surveys.