Successful multimodal management of a large hepatocellular carcinoma in a non-cirrhotic liver: a case report.

BACKGROUND: Hepatocellular carcinoma (HCC) found in a non cirrhotic liver represents a minority of HCC cases and remains poorly studied. Due to its specific characteristics and evolution, this tumour requires a different management compared to HCC in a cirrhotic liver. CASE REPORT: The authors describe the case of a 68-year-old man diagnosed with a large giant and only mildly symptomatic HCC in a non-cirrhotic liver. The 23 cm HCC was discovered when a thoracoabdominal computed tomography was performed following mild abdominal pain. After a multidisciplinary discussion the tumour was judged to be borderline, but potentially resectable after neoadjuvant therapy and preparation for surgery. The patient underwent selective internal radiation therapy radioembolization of the right hepatic artery lobe with 5,5 GBq of 90Y-labeled glass microspheres. It was followed by extended right hepatectomy after preparation by embolization of the right portal and the right hepatic veins. Thirty months after surgical resection the patient showed neither clinical, radiological nor biological signs of HCC recurrence. DISCUSSION: HCC in non-cirrhotic liver is less common than in cirrhotic liver but has a better prognosis, thanks to a greater opportunity for surgical resection. The symptoms often emerge late and are unspecific, thus delaying the HCC diagnosis. Advances in surgical resection by laparotomy or laparoscopy, and neoadjuvant therapy in preparation for surgery, have proven to be effective. However, high mortality persists due to late diagnosis linked to the inability of identifying groups at risk of HCC in the non-cirrhotic population and inadequate screening.

Deep learning based identification of bone scintigraphies containing metastatic bone disease foci.

PURPOSE: Metastatic bone disease (MBD) is the most common form of metastases, most frequently deriving from prostate cancer. MBD is screened with bone scintigraphy (BS), which have high sensitivity but low specificity for the diagnosis of MBD, often requiring further investigations. Deep learning (DL) - a machine learning technique designed to mimic human neuronal interactions- has shown promise in the field of medical imaging analysis for different purposes, including segmentation and classification of lesions. In this study, we aim to develop a DL algorithm that can classify areas of increased uptake on bone scintigraphy scans. METHODS: We collected 2365 BS from three European medical centres. The model was trained and validated on 1203 and 164 BS scans respectively. Furthermore we evaluated its performance on an external testing set composed of 998 BS scans. We further aimed to enhance the explainability of our developed algorithm, using activation maps. We compared the performance of our algorithm to that of 6 nuclear medicine physicians. RESULTS: The developed DL based algorithm is able to detect MBD on BSs, with high specificity and sensitivity (0.80 and 0.82 respectively on the external test set), in a shorter time compared to the nuclear medicine physicians (2.5 min for AI and 30 min for nuclear medicine physicians to classify 134 BSs). Further prospective validation is required before the algorithm can be used in the clinic.

Distinction of Lymphoma from Sarcoidosis on 18F-FDG PET/CT: Evaluation of Radiomics-Feature-Guided Machine Learning Versus Human Reader Performance.

Sarcoidosis and lymphoma often share common features on 18F-FDG PET/CT, such as intense hypermetabolic lesions in lymph nodes and multiple organs. We aimed at developing and validating radiomics signatures to differentiate sarcoidosis from Hodgkin lymphoma (HL) and diffuse large B-cell lymphoma (DLBCL). Methods: We retrospectively collected 420 patients (169 sarcoidosis, 140 HL, and 111 DLBCL) who underwent pretreatment 18F-FDG PET/CT at the University Hospital of Liege. The studies were randomly distributed to 4 physicians, who gave their diagnostic suggestion among the 3 diseases. The individual and pooled performance of the physicians was then calculated. Interobserver variability was evaluated using a sample of 34 studies interpreted by all physicians. Volumes of interest were delineated over the lesions and the liver using MIM software, and 215 radiomics features were extracted using the RadiomiX Toolbox. Models were developed combining clinical data (age, sex, and weight) and radiomics (original and tumor-to-liver TLR radiomics), with 7 different feature selection approaches and 4 different machine-learning (ML) classifiers, to differentiate sarcoidosis and lymphomas on both lesion-based and patient-based approaches. Results: For identifying lymphoma versus sarcoidosis, physicians' pooled sensitivity, specificity, area under the receiver-operating-characteristic curve (AUC), and accuracy were 0.99 (95% CI, 0.97-1.00), 0.75 (95% CI, 0.68-0.81), 0.87 (95% CI, 0.84-0.90), and 89.3%, respectively, whereas for identifying HL in the tumor population, it was 0.58 (95% CI, 0.49-0.66), 0.82 (95% CI, 0.74-0.89), 0.70 (95% CI, 0.64-0.75) and 68.5%, respectively. Moderate agreement was found among observers for the diagnosis of lymphoma versus sarcoidosis and HL versus DLBCL, with Fleiss κ-values of 0.66 (95% CI, 0.45-0.87) and 0.69 (95% CI, 0.45-0.93), respectively. The best ML models for identifying lymphoma versus sarcoidosis showed an AUC of 0.94 (95% CI, 0.93-0.95) and 0.85 (95% CI, 0.82-0.88) in lesion- and patient-based approaches, respectively, using TLR radiomics (plus age for the second). To differentiate HL from DLBCL, we obtained an AUC of 0.95 (95% CI, 0.93-0.96) in the lesion-based approach using TLR radiomics and 0.86 (95% CI, 0.80-0.91) in the patient-based approach using original radiomics and age. Conclusion: Characterization of sarcoidosis and lymphoma lesions is feasible using ML and radiomics, with very good to excellent performance, equivalent to or better than that of physicians, who showed significant interobserver variability in their assessment.

The use of a visual 4-point scoring scale improves the yield of 18F-FDG PET-CT imaging in the diagnosis of renal and hepatic cyst infection in patients with autosomal dominant polycystic kidney disease.

PURPOSE: [18F]FDG PET/CT (PET/CT) proved useful in the diagnosis of renal and hepatic cyst infection (CyI) in patients with autosomal dominant polycystic kidney disease (ADPKD). However, the definition of CyI by PET/CT is unclear. Here, we characterize the [18F]FDG uptake in CyI in order to infer a visual 4-point diagnostic scale. METHODS: All ADPKD patients hospitalized between 2007 and 2019 for suspected CyI and who underwent an [18F]FDG PET/CT scan were listed. CyI was defined by 5 concomitant criteria: fever ≥ 38 °C; abdominal pain; peak plasma CRP ≥ 70 mg/L; no other cause of inflammation; and favorable outcomes after antibiotics for ≥ 21 days. First, all PET/CT images were visually interpreted. Next, the [18F]FDG uptake around the suspected CyI was scored using a semiquantitative 4-point scale in comparison to blood and liver activities. RESULTS: Sixty [18F]FDG PET/CT scans were performed for suspected CyI in 38 ADPKD patients. Twenty-nine episodes met the gold-standard criteria for CyI. The visual assessment of PET/CT images reached a sensitivity of 73.1% and a specificity of 70.6%. Using the 4-point scale, an [18F]FDG score ≥ 3 (i.e., cyst uptake > liver) improved the specificity to 85.3%. CONCLUSION: [18F]FDG PET-CT is helpful in CyI diagnosis in ADPKD, and the use of a 4-point scoring of [18F]FDG uptake improves its diagnostic yield, with positive and negative predictive values of 78.3 and 78.4%, respectively. External validation is required.

Inter-observer variability of 90Y PET/CT dosimetry in hepatocellular carcinoma after glass microspheres transarterial radioembolization.

INTRODUCTION: Strong correlation has been demonstrated between tumor dose and response and between healthy liver dose and side effects. Individualized dosimetry is increasingly recommended in the current clinical routine. However, hepatic and tumor segmentations could be complex in some cases. The aim of this study is to assess the reproducibility of the tumoral and non-tumoral liver dosimetry in selective internal radiation therapy (SIRT). MATERIAL AND METHODS: Twenty-three patients with hepatocellular carcinoma (HCC) who underwent SIRT with glass microspheres were retrospectively included in the study. Tumor (TV) and total liver volumes (TLV), and mean absorbed doses in tumoral liver (TD) and non-tumoral liver (THLD) were determined on the 90Y PET/CT studies using Simplicit90YTM software, by three independent observers. Dosimetry datasets were obtained by a medical physicist helped by a nuclear medicine (NM) physician with 10 years of experience (A), by a NM physician with 4-year experience (B), and by a resident who first performed 10 dosimetry assessments as a training (C). Inter-observer agreement was evaluated using intra-class correlation coefficients (ICC), coefficients of variation (CV), Bland-Altman plots, and reproducibility coefficient (RDC). RESULTS: A strong agreement was observed between all three readers for estimating TLV (ICC 0.98) and THLD (ICC 0.97). Agreement was lower for TV delineation (ICC 0.94) and particularly for TD (ICC 0.73), especially for the highest values. Regarding TD, the CV (%) was 26.5, 26.9, and 20.2 between observers A and B, A and C, and B and C, respectively, and the RDC was 1.5. Regarding THLD, it was 8.5, 12.7, and 9.4, and the RDC was 1.3. CONCLUSION: Using a standardized methodology, and regardless of the different experiences of the observers, the estimation of THLD is highly reproducible. Although the reproducibility of the assessment of tumor irradiation is overall quite high, large variations may be observed in a limited number of patients.

Observer variability in the assessment of renal 18F-FDG uptake in kidney transplant recipients.

18F-FDG PET/CT imaging may help non-invasively disprove the diagnosis of acute kidney allograft rejection (AR) in kidney transplant recipients (KTR). The present study aims at evaluating the repeatability and reproducibility of the quantification of renal 18F-FDG uptake in KTR. We prospectively performed 18F-FDG PET/CT in 95 adult KTR who underwent surveillance transplant biopsy between 3 to 6 months post transplantation. Images were obtained 180 minutes after injecting 3 MBq 18F-FDG per kg body weight. Mean standard uptake value (SUVmean) of kidney cortex was independently measured by 2 experienced observers in 4 volumes of interest (VOI) distributed in the upper (n = 2) and lower (n = 2) poles. The first observer repeated SUV assessment in the uppermost VOI, blinded to the initial results. Intra-class correlation coefficients (ICC) and Bland-Altman plots were calculated. An ICC of 0.96 with 95%CI of [0.94; 0.97] was calculated for the intra-observer measurements. The ICC for inter-observer reproducibility for each VOI was 0.87 [0.81-0.91], 0.87 [0.81-0.91], 0.85 [0.78-0.89] and 0.83 [0.76-0.88] for the upper to the lower renal poles, respectively. The repeatability and reproducibility of the quantification of kidney allograft 18F-FDG uptake are both consistent, which makes it transferrable to the clinical routine.

Comparative dosimetry between 99mTc-MAA SPECT/CT and 90Y PET/CT in primary and metastatic liver tumors.

INTRODUCTION: The aim of this study is to determine whether 99mTc-MAA SPECT/CT-based dosimetry could predict the actual absorbed dose in hepatocellular carcinoma (HCC) or liver metastases, treated by glass or resin microspheres. MATERIAL AND METHODS: Fifty-seven patients who underwent selective internal radiation therapy (SIRT) were retrospectively included in the study, for a total of 59 treatments. Nineteen HCC were treated by resin microspheres (HCC-SIR), 20 HCC with glass microspheres (HCC-Thera), and 20 liver metastases with resin microspheres (Metastases-SIR). The mean absorbed doses in tumoral liver (Dm) and non-tumoral liver (DmNTL) were determined on the 99mTc-MAA SPECT/CT and the 90Y PET/CT, and compared with each other. RESULTS: DmNTL was < 50 Gy in the 3 groups, with a strong correlation in all population, albeit slightly lower in Metastases-SIR than HCC-SIR and HCC-Thera (CCC 0.8, 0.94 and 0.96, respectively). In tumoral liver, Dm was higher in HCC than metastases (159 ± 117 Gy versus 63 ± 31 Gy). 99mTc-MAA SPECT/CT proved to be a better indicator of Dm in HCC compared with metastases, with similar 99mTc-MAA-90Y concordance in resin and glass microspheres (CCC HCC-SIR 0.82, CCC HCC-Thera 0.82, and CCC Metastases-SIR 0.52). CONCLUSION: 99mTc-MAA SPECT/CT is a reasonably reliable tool for predicting the dose to the non-tumoral liver in both HCC and metastases, regardless of the type of microspheres. It is also fairly reliable for predicting the tumor dose in HCC, again regardless of the type of spheres, although individual variations are observed.

Diagnostic yield of 18 F-FDG PET/CT imaging and urinary CXCL9/creatinine levels in kidney allograft subclinical rejection.

Subclinical kidney allograft acute rejection (SCR) corresponds to "the unexpected histological evidence of acute rejection in a stable patient." SCR detection relies on surveillance biopsy. Noninvasive approaches may help avoid biopsy-associated complications. From November 2015 to January 2018, we prospectively performed positron emission tomography/computed tomography (PET/CT) after injection of F18 -fluorodeoxyglucose (18 F-FDG) in adult kidney transplant recipients with surveillance biopsy at ~3 months posttransplantation. The Banff-2017 classification was used. The ratio of the mean standard uptake value (mSUVR) between kidney cortex and psoas muscle was measured. Urinary levels of CXCL-9 were concomitantly quantified. Our 92-patient cohort was categorized upon histology: normal (n = 70), borderline (n = 16), and SCR (n = 6). No clinical or biological difference was observed between groups. The mSUVR reached 1.87 ± 0.55, 1.94 ± 0.35, and 2.41 ± 0.54 in normal, borderline, and SCR groups, respectively. A significant difference in mSUVR was found among groups. Furthermore, mSUVR was significantly higher in the SCR vs normal group. The area under the receiver operating characteristic curve (AUC) was 0.79, with 83% sensitivity using an mSUVR threshold of 2.4. The AUC of urinary CXCL-9/creatinine ratios comparatively reached 0.79. The mSUVR positively correlated with ti and acute composite Banff scores. 18 F-FDG-PET/CT helps noninvasively exclude SCR, with a negative predictive value of 98%. External validations are required.

The Uptake of 18F-FDG by Renal Allograft in Kidney Transplant Recipients Is Not Influenced by Renal Function.

PURPOSE OF THE REPORT: F-FDG PET/CT has been recently proposed as a noninvasive tool for the diagnosis of renal allograft acute rejection (AR) in kidney transplant recipients (KTRs). Still, the influence of kidney function on F-FDG uptake by renal grafts remains unknown. PATIENTS AND METHODS: We retrospectively identified all KTRs who underwent at least one F-FDG PET/CT. Kidney transplant recipients with documented pyelonephritis or AR were excluded. Estimated glomerular filtration rate (eGFR) was assessed using chronic kidney disease (CKD)-EPI equation. Mean standardized uptake values (SUVmean) of renal graft cortex and aorta were measured in 4 and 1 volumes of interest, respectively. Spearman rank correlation coefficient (ρ) and analysis of variance (ANOVA) were performed. RESULTS: Eighty-two KTRs underwent F-FDG PET/CT for tumor staging (n = 46), suspected infection (n = 11), or fever of unknown origin (n = 25). Mean eGFR was 50 ± 19 mL/min per 1.73 m, including CKD stage 1 (n = 3), stage 2 (n = 21), stage 3a (n = 20), stage 3b (n = 29), and stage 4 (n = 9). Mean kidney and aorta SUVmean were 1.8 ± 0.2 and 1.7 ± 0.3, respectively. No significant correlation was observed between eGFR and kidney SUVmean (ρ, 0.119; P, 0.28) or aorta SUVmean (ρ, -0.144; P, 0.20). ANOVA showed no difference of kidney (P, 0.62) and aorta (P, 0.85) SUVmean between CKD groups. Mean coefficient of variation (on the basis of kidney SUVmean of >3 consecutive F-FDG PET/CT in 15 patients with no significant change of eGFR) reached 13.1%. CONCLUSIONS: The uptake of F-FDG by renal allografts within an hour postinjection is not significantly impacted by CKD.