Interim PET-guided ABVD or ABVD/escalated BEACOPP for newly diagnosed advanced-stage classic Hodgkin lymphoma (JCOG1305).

This single-arm confirmatory study (JCOG1305) aimed to evaluate the utility of interim positron emission tomography (iPET)-guided therapy for newly diagnosed advanced-stage classic Hodgkin lymphoma (cHL). Patients aged 16-60 years with cHL received two cycles of doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) and then underwent an iPET scan (PET2), which was centrally reviewed using a five-point Deauville scale. PET2-negative patients continued an additional four cycles of ABVD, whereas PET2-positive patients switched to six cycles of escalated bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone (eBEACOPP). The co-primary endpoints were 2-year progression-free survival (PFS) among all eligible and PET2-positive patients. Ninety-three patients were enrolled between January 2016 and December 2019. One patient was ineligible because of a diagnostic error. The median age of the 92 eligible patients was 35 (interquartile range, 28-48) years. Forty (43%) patients had stage III disease, and 43 (47%) had stage IV disease. The remaining nine (10%) patients had stage IIB disease with risk factors. Nineteen PET2-positive (21%) patients received eBEACOPP, 18 completed six cycles of eBEACOPP, 73 PET2-negative (79%) patients continued ABVD, and 70 completed an additional four cycles of ABVD. With a median follow-up period of 41.1 months, the 2-year PFS of 92 eligible patients and 19 PET2-positive patients were 84.8% (80% confidence interval [CI], 79.2-88.9) and 84.2% (80% CI, 69.7-92.1), respectively. Both primary endpoints were met at the prespecified threshold. This study demonstrates that iPET-guided therapy is a useful treatment option for younger patients with newly diagnosed advanced-stage cHL. Registration number: jRCTs031180218.

Association of excess visceral fat and severe illness in hospitalized COVID-19 patients in Japan: a retrospective cohort study.

BACKGROUND/OBJECTIVES: Obesity, defined by body mass index (BMI), is a well-known risk factor for the severity of coronavirus disease 2019 (COVID-19). Adipose tissue distribution has also been implicated as an important factor in the body's response to infection, and excess visceral fat (VF), which is prevalent in Japanese, may contribute significantly to the severity. Therefore, this study aimed to evaluate the association of obesity and VF with COVID-19 severe illness in Japan. SUBJECTS/METHODS: This retrospective cohort study involved 550 COVID-19 patients admitted to a tertiary care hospital with BMI and body composition data, including VF. The primary endpoint was severe illness, including death, due to COVID-19 during hospitalization. Logistic regression analysis was applied to examine the quartiles of BMI and VF on severe illness after adjusting for covariates such as age, sex, subcutaneous fat, paraspinal muscle radiodensity, and comorbidities affecting VF (COPD, cancer within 5 years, immunosuppressive agent use). RESULTS: The median age was 56.0 years; 71.8% were males. During hospitalization, 82 (14.9%) experienced COVID-19 severe illness. In the multivariate logistic regression analysis, Q4 of BMI was not significantly associated with severe illness compared to Q1 of BMI (OR 1.03; 95% CI 0.37-2.86; p = 0.95). Conversely, Q3 and Q4 of VF showed a higher risk for severe illness compared to Q1 of VF (OR 2.68; 95% CI 1.01-7.11; p = 0.04, OR 3.66; 95% CI 1.30-10.26; p = 0.01, respectively). Stratified analysis by BMI and adjusted for covariates showed the positive association of VF with severe illness only in the BMI < 25 kg/m2 group. CONCLUSIONS: High BMI was not an independent risk factor for COVID-19 severe illness in hospitalized patients in Japan, whereas excess VF significantly influenced severe illness, especially in patients with a BMI < 25 kg/m2.

Deep convolutional neural network for differentiating between sarcoidosis and lymphoma based on [18F]FDG maximum-intensity projection images.

OBJECTIVES: To compare the [18F]FDG PET/CT findings of untreated sarcoidosis and malignant lymphoma (ML) and develop convolutional neural network (CNN) models to differentiate between these diseases using maximum intensity projection (MIP) [18F]FDG PET images. METHODS: We retrospectively collected data on consecutive patients newly diagnosed with sarcoidosis and ML who underwent [18F]FDG PET/CT before treatment. Two nuclear radiologists reviewed the images. CNN models were created using MIP PET images and evaluated with k-fold cross-validation. The points of interest were visualized using gradient-weighted class activation mapping (Grad-CAM). RESULTS: A total of 56 patients with sarcoidosis and 62 patients with ML were included. Patients with sarcoidosis had more prominent FDG accumulation in the mediastinal lymph nodes and lung lesions, while those with ML had more prominent accumulation in the cervical lymph nodes (all p < 0.001). For the mediastinal lymph nodes, sarcoidosis patients had significant FDG accumulation in the level 2, 4, 7, and 10 lymph nodes (all p < 0.01). Otherwise, the accumulation in ML patients tended to be in the level 1 lymph nodes (p = 0.08). The CNN model using frontal and lateral MIP images achieved an average accuracy of 0.890 (95% CI: 0.804-0.977), a sensitivity of 0.898 (95% CI: 0.782-1.000), a specificity of 0.907 (95% CI: 0.799-1.000), and an area under the curve of 0.963 (95% CI: 0.899-1.000). Grad-CAM showed that the model focused on the sites of abnormal FDG accumulation. CONCLUSIONS: CNN models based on differences in FDG accumulation sites archive high performance in differentiating between sarcoidosis and ML. CLINICAL RELEVANCE STATEMENT: We developed a CNN model using MIP images of [18F]FDG PET/CT to distinguish between sarcoidosis and malignant lymphoma. It achieved high performance and could be useful in diagnosing diseases with involvement across organs and lymph nodes. KEY POINTS: • There are differences in FDG distribution when comparing whole-body [18F]FDG PET/CT findings in patients with sarcoidosis and malignant lymphoma before treatment. • Convolutional neural networks, a type of deep learning technique, trained with maximum-intensity projection PET images from two angles showed high performance. • A deep learning model that utilizes differences in FDG distribution may be helpful in differentiating between diseases with lesions that are characteristically widespread among organs and lymph nodes.

Transient receptor potential cation channel subfamily V member 1 (TRPV1) targeted PET imaging.

Transient receptor potential cation channel subfamily V member 1 (TRPV1) was identified using capsaicin, a pungent compound that is present in red pepper. The activation of TRPV1 induces an influx of calcium ions into cells and causes excitation of sensory neurons, associating with thermal sensing, sweating and pain. TRPV1 is also identified in various types of cancer cells. The expression of TRPV1 in cancer cells depends on the type of cancer and the stage of the disease. Therefore, TRPV1 has been considered a potential target of medicinal chemistry for drug development, and blocking its activation may lead to cancer therapy and pain relief. However, the details of the pathophysiological function of TRPV1 in vivo are still unclear. To explore practical use of TRPV1, we focused on positron emission tomography imaging and developed a 11C-radiolabeled tracer to visualize TRPV1.

Phase I/IIa trial of 18F-prostate specific membrane antigen (PSMA) 1007 PET/CT in healthy volunteers and prostate cancer patients.

OBJECTIVE: 18F-PSMA 1007 is a promising PET tracer for prostate cancer. We aimed to examine the safety, biodistribution, radiation dosimetry, and clinical effectiveness in Japanese healthy volunteers and patients with prostate cancer. METHODS: Part A evaluated the pharmacokinetics and exposure doses in three healthy volunteers. Part B evaluated the diagnostic accuracy in patients with untreated preoperative prostate cancer (Cohort 1, n = 7) and patients with biochemical recurrence (Cohort 2, n = 3). All subjects received a single dose of 3.7 MBq/kg 18F-PSMA 1007. Results: 18F-PSMA 1007 was found to be safe and well tolerated in all subjects. No serous AEs or drug-related AEs were identified during the present study. The average blood radioactivity concentration reached a maximum of 47.87 ± 1.05 (percentage of injected dose [%ID]/ml) at 5 min and then decreased to 1.60 ± 0.78 in 6 h. The systemic radioactivity reached a maximum of 211.05 ± 6.77 (%ID$\times$103) at 5 min and decreased to 7.18 ± 3.91 in 6 h. The sensitivity and positive predictive value were 100% and 100% based on both pathologic and imaging confirmation as gold standard. In Cohort 1, 15 primary foci (11.9%) were >5 mm in the largest diameter and identified in 39 of 126 segments (30.1%). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for 60 min uptake time acquisition were 80.0, 96.5, 91.4, 91.2 and 91.3%, respectively. CONCLUSIONS: Our study revealed that 18F-PSMA 1007 was safe, well tolerated and showed high accuracy in the diagnosis of prostate cancer.

English version of Japanese Clinical Practice Guidelines 2022 for gastrointestinal stromal tumor (GIST) issued by the Japan Society of Clinical Oncology.

The Japan Society of Clinical Oncology Clinical Practice Guidelines 2022 for gastrointestinal stromal tumor (GIST) have been published in accordance with the Minds Manual for Guideline Development 2014 and 2017. A specialized team independent of the working group for the revision performed a systematic review. Since GIST is a rare type of tumor, clinical evidence is not sufficient to answer several clinical and background questions. Thus, in these guidelines, we considered that consensus among the experts who manage GIST, the balance between benefits and harms, patients' wishes, medical economic perspective, etc. are important considerations in addition to the evidence. Although guidelines for the treatment of GIST have also been published by the National Comprehensive Cancer Network (NCCN) and the European Society for Medical Oncology (ESMO), there are some differences between the treatments proposed in those guidelines and the treatments in the present guidelines because of the differences in health insurance systems among countries.

Stepwise algorithm using computed tomography and magnetic resonance imaging for differential diagnosis of fat-poor angiomyolipoma in small renal masses: A prospective validation study.

OBJECTIVES: To validate the diagnostic accuracy of a stepwise algorithm to differentiate fat-poor angiomyolipoma (fp-AML) from renal cancer in small renal masses (SRMs). METHODS: We prospectively enrolled 223 patients with solid renal masses <4 cm and no visible fat on unenhanced computed tomography (CT). Patients were assessed using an algorithm that utilized the dynamic CT and MRI findings in a stepwise manner. The diagnostic accuracy of the algorithm was evaluated in patients whose histology was confirmed through surgery or biopsy. The clinical course of the patients was further analyzed. RESULTS: The algorithm classified 151 (68%)/42 (19%)/30 (13%) patients into low/intermediate/high AML probability groups, respectively. Pathological diagnosis was made for 183 patients, including 10 (5.5%) with fp-AML. Of these, 135 (74%)/36 (20%)/12 (6.6%) were classified into the low/intermediate/high AML probability groups, and each group included 1 (0.7%)/3 (8.3%)/6 (50%) fp-AMLs, respectively, leading to the area under the curve for predicting AML of 0.889. Surgery was commonly opted in the low and intermediate AML probability groups (84% and 64%, respectively) for initial management, while surveillance was selected in the high AML probability group (63%). During the 56-month follow-up, 36 (82%) of 44 patients initially surveyed, including 13 of 18 (72%), 6 of 7 (86%), and 17 of 19 (89%) in the low/intermediate/high AML probability groups, respectively, continued surveillance without any progression. CONCLUSIONS: This study confirmed the high diagnostic accuracy for differentiating fp-AMLs. These findings may help in the management of patients with SRMs.

Effectiveness of remdesivir with corticosteroids for COVID-19 patients in intensive care unit: A hospital-based observational study.

The effectiveness of remdesivir on survival in coronavirus disease 2019 (COVID-19), especially in cases treated in the intensive care unit (ICU), is controversial. We investigated the effectiveness of remdesivir with corticosteroids on the survival of COVID-19 patients in a real ICU clinical practice. For laboratory-confirmed COVID-19 patients admitted to the ICU of a tertiary hospital in Tokyo (April 2020-November 2021) and who received corticosteroids, the effectiveness of remdesivir for survival, stratified by interval length (within 9 or 10+ days), was retrospectively analyzed using Cox regression model. A total of 168 patients were included: 35 with no remdesivir use (control), 96 with remdesivir use within 9 days, and 37 with remdesivir use with an interval of 10+ days. In-hospital mortality was 45.7%, 10.4%, and 16.2%, respectively. After adjusting for possible covariates including comorbidities, laboratory data, oxygen demand, or level of pneumonia, remdesivir use within 9 days from symptom onset reduced mortality risk (hazard ratio [HR]: 0.10; 95% confidence interval (CI): 0.025-0.428) compared to the control group. However, remdesivir use with an interval of 10+ days showed no significant association with mortality (HR: 0.42; 95% CI: 0.117-1.524). Among COVID-19 patients who received corticosteroids in ICU, remdesivir use within 9 days from symptom onset was associated with reduced in-hospital mortality risk.

Novel utility of Vesical Imaging-Reporting and Data System in multimodal treatment for muscle-invasive bladder cancer.

OBJECTIVES: To examine the clinical significance of the Vesical Imaging-Reporting and Data System (VI-RADS) in predicting outcome of multimodal treatment (MMT) in muscle-invasive bladder cancer (MIBC) patients. METHODS: We reviewed 78 pathologically proven MIBC patients who underwent MMT including transurethral resection and chemoradiotherapy, followed by partial or radical cystectomy. Treatment response was assessed through histologic evaluation of cystectomy specimens. Two radiologists categorized the index lesions of pretherapeutic MRI according to the 5-point VI-RADS score. The associations of VI-RADS score with the therapeutic effect of MMT were analyzed. The diagnostic performance of VI-RADS scores with a cut-off VI-RADS scores ≤ 2 or ≤ 3 for predicting pathologic complete response to MMT (MMT-CR) was evaluated. RESULTS: MMT-CR was achieved in 2 (100%) of VI-RADS score 1 (n = 2), 16 (84%) of score 2 (n = 19), 12 (86%) of score 3 (n = 14), 7 (64%) of score 4 (n = 11), and 14 (44%) of score 5 (n = 32). VI-RADS score was inversely associated with the incidence of MMT-CR (p = 0.00049). The cut-off VI-RADS score ≤ 2 and ≤ 3 could predict the favorable therapeutic outcome of MMT with high specificity (0.89 with 95% confidence interval [CI]: 0.71-0.98 and 0.82 with 95% CI: 0.62-0.94, respectively) and high positive predictive value (0.86 with 95% CI: 0.64-0.97 and 0.86 with 95% CI: 0.70-0.95, respectively). CONCLUSION: VI-RADS score may serve as an imaging marker in MIBC patients for predicting the therapeutic outcome of MMT. CLINICAL RELEVANCE STATEMENT: Muscle-invasive bladder cancer patients with a lower Vesical Imaging-Reporting and Data System score can be a good candidate for bladder-sparing treatment incorporating multimodal treatment. KEY POINTS: • Vesical Imaging-Reporting and Data System (VI-RADS) score was potentially valuable for classifying pathologic tumor response in patients with muscle-invasive bladder cancer. • The likelihood of achieving complete response of multimodal treatment (MMT) decreased with increasing VI-RADS score. • VI-RADS score could serve as an imaging marker that optimizes patient selection for MMT.

Prognostic impact of the radiological infiltrative feature of primary renal tumor in metastatic renal cell carcinoma.

OBJECTIVES: Recent studies suggest that the radiological infiltrative feature (r-IF) of renal tumors is strongly correlated with poor oncologic outcomes in locally advanced renal cell carcinoma (RCC). This study investigated the prognostic impact of r-IF of primary renal tumors in metastatic RCC (mRCC) in comparison with International Metastatic RCC Database Consortium (IMDC) risk model. METHODS: We retrospectively analyzed 91 patients with previously untreated mRCC. Dynamic computed tomography of the primary renal tumor was reviewed to assess r-IF, defined as a focally/extensively ill-defined tumor interface with normal renal parenchyma. RESULTS: The median age was 67 years, and 69 patients (76%) were men. Prior nephrectomy was performed in 47 patients (52%). The median size of the primary renal tumor was 6.7 cm, and 50 patients (55%) presented with cT3-4 stage. Overall, 25 (28%)/52 (57%)/14 (15%) patients were classified into IMDC favorable/intermediate/poor-risk groups, respectively. An image review identified r-IFs in the primary renal tumor in 40 patients (44%). The incidences of r-IFs were 28%/46%/64% in IMDC favorable/intermediate/poor-risk groups, respectively. During a median follow-up of 2.6 years, 31 patients (34%) died of RCC. On multivariable analysis, r-IF and IMDC intermediate-poor risks were independently associated with poor cancer-specific survival (CSS). Two-year CSS were 64%/87% in patients with/without r-IF, respectively. C-index was improved from 0.73 to 0.81 by adding r-IF to the IMDC risk factors. CONCLUSIONS: R-IF of the primary renal tumor was an independent risk factor for poor CSS in patients with mRCC, which may improve the prognostic accuracy when combined with the IMDC risk model.

Clinical Utility of Breast Ultrasound Images Synthesized by a Generative Adversarial Network.

BACKGROUND AND OBJECTIVES: This study compares the clinical properties of original breast ultrasound images and those synthesized by a generative adversarial network (GAN) to assess the clinical usefulness of GAN-synthesized images. MATERIALS AND METHODS: We retrospectively collected approximately 200 breast ultrasound images for each of five representative histological tissue types (cyst, fibroadenoma, scirrhous, solid, and tubule-forming invasive ductal carcinomas) as training images. A deep convolutional GAN (DCGAN) image-generation model synthesized images of the five histological types. Two diagnostic radiologists (reader 1 with 13 years of experience and reader 2 with 7 years of experience) were given a reading test consisting of 50 synthesized and 50 original images (≥1-month interval between sets) to assign the perceived histological tissue type. The percentages of correct diagnoses were calculated, and the reader agreement was assessed using the kappa coefficient. RESULTS: The synthetic and original images were indistinguishable. The correct diagnostic rates from the synthetic images for readers 1 and 2 were 86.0% and 78.0% and from the original images were 88.0% and 78.0%, respectively. The kappa values were 0.625 and 0.650 for the synthetic and original images, respectively. The diagnoses made from the DCGAN synthetic images and original images were similar. CONCLUSION: The DCGAN-synthesized images closely resemble the original ultrasound images in clinical characteristics, suggesting their potential utility in clinical education and training, particularly for enhancing diagnostic skills in breast ultrasound imaging.

Usefulness of texture features of apparent diffusion coefficient maps in predicting chemoradiotherapy response in muscle-invasive bladder cancer.

OBJECTIVES: To examine the usefulness of the texture analysis (TA) of apparent diffusion coefficient (ADC) maps in predicting the chemoradiotherapy (CRT) response of muscle-invasive bladder cancer (MIBC). METHODS: We reviewed 45 MIBC patients who underwent cystectomy after CRT. CRT response was assessed through histologic evaluation of cystectomy specimens. Two radiologists determined the volume of interest for the index lesions on ADC maps of pretherapeutic 1.5-T MRI and performed TA using the LIFEx software. Forty-six texture features (TFs) were selected based on their contribution to the prediction of CRT sensitivity. To evaluate diagnostic performance, diagnostic models from the selected TFs were created using random forest (RF) and support vector machine (SVM), respectively. RESULTS: Twenty-three patients achieved pathologic complete response (pCR) to CRT. The feature selection identified first quartile ADC (Q1 ADC), gray-level co-occurrence matrix (GLCM) correlation, and GLCM homogeneity as important in predicting CRT response. Patients who achieved pCR showed significantly lower Q1 ADC and GLCM correlation values (0.66 × 10-3 mm2/s and 0.53, respectively) than those who did not (0.81 × 10-3 mm2/s and 0.70, respectively; p < 0.05 for both). The AUCs of the RF and SVM models incorporating the selected TFs were 0.82 (95% confidence interval [CI]: 0.67-0.97) and 0.96 (95% CI: 0.91-1.00), respectively, and the AUC of the SVM model was better than that of the mean ADC value (0.76, 95% CI: 0.61-0.90; p = 0.0037). CONCLUSION: TFs can serve as imaging biomarkers in MIBC patients for predicting CRT sensitivity. TAs of ADC maps can potentially optimize patient selection for CRT. KEY POINTS: • Texture analysis of ADC maps and feature selection identified important texture features for classifying pathologic tumor response in patients with muscle-invasive bladder cancer. • The machine learning model incorporating the texture features set, which included first quartile ADC, GLCM correlation, and GLCM homogeneity, showed high performance in predicting chemoradiotherapy response. • Texture features could serve as imaging biomarkers that optimize eligible patient selection for chemoradiotherapy in muscle-invasive bladder cancer.

Imaging-detected bone stress injuries at the Tokyo 2020 summer Olympics: epidemiology, injury onset, and competition withdrawal rate.

BACKGROUND: Prevention and early detection of injuries are essential in optimising sport participation and performance. The aim of this study is to investigate the epidemiology, athlete injury history, and competition withdrawal rate of imaging-detected bone stress injuries during the Tokyo 2020 Olympic Games. METHODS: We collected and analysed imaging and clinical information in athletes with bone stress injuries diagnosed in the Olympic Village polyclinic during the Games. Two physicians independently and retrospectively reviewed all imaging examinations of bone stress injuries. RESULTS: A total of 11,315 individual athletes from 206 National Olympic Committees competed at the Games, during which 567 MRIs and 352 X-rays were performed at the Olympic Village polyclinic. Radiology examinations revealed four stress fractures and 38 stress reactions in 29 athletes (median age 24 years, range 18-35 years). Of these, 72% of athletes (n = 21) had symptoms before entering the Olympic Village. Bone stress injuries were most common in women (55%), the lower extremities (66%), and track and field athletes (45%). Six athletes (21%) did not start or did not finish their competitions. CONCLUSIONS: This study revealed 42 imaging-detected bone stress injuries in the polyclinic of the Tokyo 2020 Olympic Village. The high proportion of athletes with symptoms before entering the village and the high proportion of competition withdrawals suggests the usefulness of an early MRI examination.

Total diffusion volume in MRI vs. total lesion glycolysis in PET/CT for tumor volume evaluation of multiple myeloma.

OBJECTIVE: This study compared the tumor burden and prognostic impact of total diffusion volume (tDV) and total lesion glycolysis (TLG) in the same patients with newly diagnosed multiple myeloma (NDMM) simultaneously. We also examined the relationship between these imaging tumor volumes (TVs) and plasma cell (PC) TV in bone marrow (BM) specimens. METHODS: We retrospectively reviewed the data of 63 patients with newly diagnosed multiple myeloma (NDMM) from April 2016 to March 2018. tDV was calculated from whole-body diffusion-weighted imaging and TLG was calculated from the average standard uptake value and the metabolic tumor volume, respectively. Cellularity of BM hematopoietic tissue and the percentage of BM PCs were used as a reference of PC volume in the BM. RESULTS: The Spearman correlation coefficient between tDV and TLG was moderate (ɤs = 0.588, p < 0.001) when PET false-negative patients were excluded. There were positive correlations between the BM plasma cell volume (BMPCV) and the imaging TVs (ɤs = 0.505, vs. tDV; and 0.464, vs. TLG). Patients with high tDV and high TLG, as determined by the receiver operating characteristic curve, had worse survival; moreover, patients with both high tDV and high TLG showed the worst prognosis (median progression-free and overall survival: 13.2 and 28.9 months, respectively). CONCLUSIONS: Although tDV and TLG each reflected the total TV, in several cases, tDV and TLG were discrepant due to the biological features of each MM. It is important to use both modalities for complementary assessment of total tumor burden and biological characteristics in MM. KEY POINTS: • Total diffusion volume (tDV) and total lesion glycolysis (TLG) reflect the total tumor volume and have prognostic value in patients with multiple myeloma (MM). • tDV and TLG could assess MM from different biological perspectives and should be considered for each patient individually.

CT Abnormalities of the Pancreas Associated With the Subsequent Diagnosis of Clinical Stage I Pancreatic Ductal Adenocarcinoma More Than 1 Year Later: A Case-Control Study.

BACKGROUND. Pancreatic ductal adenocarcinoma (PDAC) is highly lethal, partly because of challenges in early diagnosis. However, the prognosis for earlier stages (carcinoma in situ or category T1a invasive carcinoma) is relatively favorable. OBJECTIVE. The purpose of this study was to investigate findings of an earlier diagnosis of PDAC on CT examinations performed at least 1 year before the diagnosis of clinical stage I PDAC. METHODS. This retrospective study included 103 patients with clinical stage I PDAC and a CT examination performed at least 1 year before the CT examination that detected PDAC, as well as 103 control patients without PDAC on CT examinations separated by at least 10 years. The frequency and temporal characteristics of focal pancreatic abnormalities (pancreatic mass, main pancreatic duct [MPD] change, parenchymal atrophy, faint parenchymal enhancement, cyst, and parenchymal calcification) seen on CT examinations conducted before diagnosis (prediagnostic CT) were determined. RESULTS. A focal pancreatic abnormality was present on the most recent prediagnostic CT examination in 55/103 (53.4%) patients with PDAC versus 21/103 (20.4%) control patients (p < .001). In patients with PDAC, the most common focal abnormalities on prediagnostic CT were atrophy (39/103, 37.9%), faint enhancement (17/65, 26.2%), and MPD change (14/103, 13.6%), which were all more frequent in patients with PDAC than in control patients (p < .05). In 54/55 (98.2%) patients with PDAC, the PDAC corresponded to the site of a focal abnormality (exact location or the abnormality's upstream or downstream edge) on prediagnostic CT. Frequency of focal abnormalities decreased with increasing time before CT that detected PDAC (> 1 to ≤ 2 years before diagnosis, 64.9%; > 2 to ≤ 3 years, 49.2%; > 3 to ≤ 5 years, 41.8%; > 5 to ≤ 7 years, 29.7%; > 7 to ≤ 10 years, 18.5%; more than 10 years, 0%). Mean duration from the finding's initial appearance to diagnosis of PDAC was 4.6 years for atrophy, 3.3 years for faint enhancement, and 1.1 years for MPD change. CONCLUSION. Most patients with clinical stage I PDAC showed focal pancreatic abnormalities on CT performed at least 1 year before diagnosis. Focal MPD change exhibited the shortest duration from its development to subsequent diagnosis, whereas atrophy and faint enhancement exhibited a relatively prolonged course. CLINICAL IMPACT. These findings could facilitate earlier PDAC diagnosis and thus improve prognosis.

Uterine Cervical Carcinoma: Evaluation Using Non-Gaussian Diffusion Kurtosis Imaging and Its Correlation With Histopathological Findings.

OBJECTIVE: The aim of the study was to assess non-Gaussian diffusion kurtosis imaging (DKI)'s usefulness as a noninvasive method to evaluate tumor invasion depth, histological grade, and lymph node metastasis in cervical carcinoma (CC) patients. METHODS: Twenty-two consecutive patients with histologically confirmed CC were examined by 1.5-T MRI and non-Gaussian DKI with 4 b values of 0, 500, 1000, and 2000 s/mm2. Kurtosis (K), diffusivity (D), and apparent diffusion coefficient (ADC) maps were compared with histopathological findings. RESULTS: Kurtosis maps revealed the fibrous stroma as a distinct high K zone (1.442 ± 0.373) that was significantly different from values of the cervical mucosa, outer stroma, and parametrium (0.648 ± 0.083, 0.715 ± 0.113, and 0.504 ± 0.060, respectively, P < 0.0001). Kurtosis (1.189 ± 0.228) and D (0.961 ± 0.198 × 10-3 mm2/s) values of all CCs were significantly different from those of all uterine cervical wall layers. Kurtosis and D values were significantly correlated with histological grades of CCs (r = 0.934, P < 0.0001, and r = -0.925, P < 0.0001, respectively), whereas no significant differences were found in ADC values between grades 2 and 3 CCs (P = 0.787). Metastatic and nonmetastatic lymph nodes showed significantly different K (P < 0.0001) and D (P < 0.0001) values; however, their ADC values did not show significant differences (P = 0.437). For differentiating grade 3 CCs from grade 1 or 2 CCs, the areas under the curve for K (0.991, P = 0.0375) and D (0.982, P = 0.0337) values were significantly higher than those for ADC values (0.759). For differentiating metastatic and nonmetastatic lymph nodes, the areas under the curve for K (0.974, P = 0.0028) and D (0.968, P = 0.0018) values were significantly higher than those for ADC (0.596). CONCLUSIONS: Non-Gaussian DKI may be clinically useful for noninvasive evaluation of tumor invasion depth, histological grade, and lymph node metastasis in CC patients.

Virtual Interpolation Images of Tumor Development and Growth on Breast Ultrasound Image Synthesis With Deep Convolutional Generative Adversarial Networks.

OBJECTIVES: We sought to generate realistic synthetic breast ultrasound images and express virtual interpolation images of tumors using a deep convolutional generative adversarial network (DCGAN). METHODS: After retrospective selection of breast ultrasound images of 528 benign masses, 529 malignant masses, and 583 normal breasts, 20 synthesized images of each were generated by the DCGAN. Fifteen virtual interpolation images of tumors were generated by changing the value of the input vector. A total of 60 synthesized images and 20 virtual interpolation images were evaluated by 2 readers, who scored them on a 5-point scale (1, very good; to 5, very poor) and then answered whether the synthesized image was benign, malignant, or normal. RESULTS: The mean score of overall quality for synthesized images was 3.05, and that of the reality of virtual interpolation images was 2.53. The readers classified the generated images with a correct answer rate of 92.5%. CONCLUSIONS: A DCGAN can generate high-quality synthetic breast ultrasound images of each pathologic tissue and has the potential to create realistic virtual interpolation images of tumor development.

Infiltrative tumor interface with normal renal parenchyma in locally advanced renal cell carcinoma: Clinical relevance and pathological implications.

OBJECTIVES: Locally advanced renal cell carcinoma is considered clinically aggressive, despite heterogeneity in survival outcomes. We investigated the clinical relevance and pathological implications of infiltrative tumor interface with normal renal parenchyma on preoperative imaging in locally advanced renal cell carcinoma. METHODS: A total of 77 patients with locally advanced renal cell carcinoma (≥pT3a Nany M0) who underwent radical or partial nephrectomy (2008-2018) were analyzed. Preoperative dynamic computed tomography images were reviewed to assess radiological infiltrative features. A radiological infiltrative feature was defined as an ill-defined tumor interface with normal renal parenchyma. The tumor interfaces were analyzed histologically and compared with radiological findings. RESULTS: The median tumor size was 6.4 cm. Lymphadenopathy was observed in four patients (5.2%). Clear cell renal cell carcinoma was diagnosed in 66 patients (86%) and Fuhrman grade was 3-4 in 38 patients (49%). A total of 30 patients (39%) showed radiological infiltrative features, which were significantly associated with larger tumor size and higher clinical T stage. The specificity and sensitivity of radiological infiltrative features in predicting pathological renal parenchymal infiltration were 90 and 64%, respectively. During a median follow-up period of 3.8 years, 27 patients (35%) developed cancer recurrences, and six patients (7.8%) died of renal cell carcinoma. Multivariable analysis showed that the presence of radiological infiltrative features was an independent risk factor for cancer recurrence. Cancer recurrence and cancer-specific mortality were significantly stratified by the presence or absence of radiological infiltrative features (P < 0.001 and P = 0.02, respectively). CONCLUSIONS: Locally advanced renal cell carcinoma can show radiological infiltrative features preoperatively, which are significantly associated with unfavorable prognosis. Radiological infiltrative features on preoperative imaging correspond with a high specificity to pathological renal parenchymal infiltration.

Can Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia?

Background and Objectives: This study aimed to investigate whether predictive indicators for the deterioration of respiratory status can be derived from the deep learning data analysis of initial chest computed tomography (CT) scans of patients with coronavirus disease 2019 (COVID-19). Materials and Methods: Out of 117 CT scans of 75 patients with COVID-19 admitted to our hospital between April and June 2020, we retrospectively analyzed 79 CT scans that had a definite time of onset and were performed prior to any medication intervention. Patients were grouped according to the presence or absence of increased oxygen demand after CT scan. Quantitative volume data of lung opacity were measured automatically using a deep learning-based image analysis system. The sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of the opacity volume data were calculated to evaluate the accuracy of the system in predicting the deterioration of respiratory status. Results: All 79 CT scans were included (median age, 62 years (interquartile range, 46-77 years); 56 (70.9%) were male. The volume of opacity was significantly higher for the increased oxygen demand group than for the nonincreased oxygen demand group (585.3 vs. 132.8 mL, p < 0.001). The sensitivity, specificity, and AUC were 76.5%, 68.2%, and 0.737, respectively, in the prediction of increased oxygen demand. Conclusion: Deep learning-based quantitative analysis of the affected lung volume in the initial CT scans of patients with COVID-19 can predict the deterioration of respiratory status to improve treatment and resource management.

Clinical Usefulness of Ultrasound-Guided Fine Needle Aspiration and Core Needle Biopsy for Patients with Axillary Lymphadenopathy.

Background and Objectives: It is necessary to properly diagnose and manage axillary lymphadenopathy caused by a variety of diseases. This study aimed to evaluate the utility of ultrasound (US)-guided sampling in patients with axillary lymphadenopathy. Materials and Methods: Patients with axillary lymphadenopathy (excluding patients with newly diagnosed breast cancer) who underwent US-guided fine needle aspiration (FNA) or core needle biopsy (CNB) at a single center between February 2016 and September 2020 were retrospectively examined. The association between US imaging findings and malignancy was investigated and the diagnostic performance of US-guided sampling was assessed. Results: Fifty-five patients (including eight males) were included in the study; of these, 34 patients (61.8%) were finally diagnosed with a malignant lymph node lesion. Twenty-two patients (40.0%) had undergone FNA and 33 (60.0%) had undergone CNB. Larger short and long axis diameters, thicker lymph node cortex, and the absence of fatty hilum on the US were significantly associated with malignancy (p < 0.05). The diagnostic performance of FNA, CNB, and FNA + CNB was excellent (sensitivity, specificity, and accuracy of 0.909, 0.900, and 0.917 for FNA, 0.958, 1.000, and 0.970 for CNB, and 0.941, 0.952, and 0.945 for FNA + CNB, respectively). Conclusions: US-guided FNA and CNB play an important role in the diagnosis and management of patients with axillary lymphadenopathy.