Metabolic tumour area: a novel prognostic indicator based on 18F-FDG PET/CT in patients with diffuse large B-cell lymphoma in the R-CHOP era.

BACKGROUND: The metabolic tumour area (MTA) was found to be a promising predictor of prostate cancer. However, the role of MTA based on 18F-FDG PET/CT in diffuse large B-cell lymphoma (DLBCL) prognosis remains unclear. This study aimed to elucidate the prognostic significance of MTA and evaluate its incremental value to the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) for DLBCL patients treated with first-line R-CHOP regimens. METHODS: A total of 280 consecutive patients with newly diagnosed DLBCL and baseline 18F-FDG PET/CT data were retrospectively evaluated. Lesions were delineated via a semiautomated segmentation method based on a 41% SUVmax threshold to estimate semiquantitative metabolic parameters such as total metabolic tumour volume (TMTV) and MTA. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off values. Progression-free survival (PFS) and overall survival (OS) were the endpoints that were used to evaluate the prognosis. PFS and OS were estimated via Kaplan‒Meier curves and compared via the log-rank test. RESULTS: Univariate analysis revealed that patients with high MTA, high TMTV and NCCN-IPI ≥ 4 were associated with inferior PFS and OS (P < 0.0001 for all). Multivariate analysis indicated that MTA remained an independent predictor of PFS and OS [hazard ratio (HR), 2.506; 95% confidence interval (CI), 1.337-4.696; P = 0.004; and HR, 1.823; 95% CI, 1.005-3.310; P = 0.048], whereas TMTV was not. Further analysis using the NCCN-IPI model as a covariate revealed that MTA and NCCN-IPI were still independent predictors of PFS (HR, 2.617; 95% CI, 1.494-4.586; P = 0.001; and HR, 2.633; 95% CI, 1.650-4.203; P < 0.0001) and OS (HR, 2.021; 95% CI, 1.201-3.401; P = 0.008; and HR, 3.869; 95% CI, 1.959-7.640; P < 0.0001; respectively). Furthermore, MTA was used to separate patients with high NCCN-IPI risk scores into two groups with significantly different outcomes. CONCLUSIONS: Pre-treatment MTA based on 18F-FDG PET/CT and NCCN-IPI were independent predictor of PFS and OS in DLBCL patients treated with R-CHOP. MTA has additional predictive value for the prognosis of patients with DLBCL, especially in high-risk patients with NCCN-IPI ≥ 4. In addition, the combination of MTA and NCCN-IPI may be helpful in further improving risk stratification and guiding individualised treatment options. TRIAL REGISTRATION: This research was retrospectively registered with the Ethics Committee of the Third Affiliated Hospital of Soochow University, and the registration number was approval No. 155 (approved date: 31 May 2022).

Tumour growth rate predicts overall survival in patients with recurrent WHO grade 4 glioma.

PURPOSE: Accurate prognostication may aid in the selection of patients who will benefit from surgery at recurrent WHO grade 4 glioma. This study aimed to evaluate the role of serial tumour volumetric measurements for prognostication at first tumour recurrence. METHODS: We retrospectively analyzed patients with histologically-diagnosed WHO grade 4 glioma at initial and at first tumour recurrence at a tertiary hospital between May 2000 and September 2018. We performed auto-segmentation using ITK-SNAP software, followed by manual adjustment to measure serial contrast-enhanced T1W (CE-T1W) and T2W lesional volume changes on all MRI images performed between initial resection and repeat surgery. RESULTS: Thirty patients met inclusion criteria; the median overall survival using Kaplan-Meier analysis from second surgery was 10.5 months. Seventeen (56.7%) patients received treatment post second surgery. Univariate cox regression analysis showed that greater rate of increase in lesional volume on CE-T1W (HR = 2.57; 95% CI [1.18, 5.57]; p = 0.02) in the last 2 MRI scans leading up to the second surgery was associated with a higher mortality likelihood. Patients with higher Karnofsky Performance Score (KPS) (HR = 0.97; 95% CI [0.95, 0.99]; p = 0.01) and who received further treatment following second surgery (HR = 0.43; 95% CI [0.19, 0.98]; p = 0.04) were shown to have a better survival. CONCLUSION: Higher rate of CE-T1W lesional growth on the last 2 MRI images prior to surgery at recurrence was associated with increase mortality risk. A larger prospective study is required to determine and validate the threshold to distinguish rapidly progressive tumour with poor prognosis.

TGFBR3L is associated with gonadotropin production in non-functioning gonadotroph pituitary neuroendocrine tumours.

PURPOSE: Transforming growth factor-beta receptor 3-like (TGFBR3L) is a pituitary enriched membrane protein selectively detected in gonadotroph cells. TGFBR3L is named after transforming growth factor-beta receptor 3 (TGFBR3), an inhibin A co-receptor in mice, due to sequence identity to the C-terminal region. We aimed to characterize TGFBR3L detection in a well-characterized, prospectively collected cohort of non-functioning pituitary neuroendocrine tumours (NF-PitNETs) and correlate it to clinical data. METHODS: 144 patients operated for clinically NF-PitNETs were included. Clinical, radiological and biochemical data were recorded. Immunohistochemical (IHC) staining for FSHß and LHß was scored using the immunoreactive score (IRS), TGFBR3L and TGFBR3 were scored by the percentage of positive stained cells. RESULTS: TGFBR3L staining was selectively present in 52% of gonadotroph tumours. TGFBR3L was associated to IRS of LHß (median 2 [IQR 0-3] in TGFBR3L negative and median 6 [IQR 3-9] in TGFBR3L positive tumours, p < 0.001), but not to the IRS of FSHß (p = 0.32). The presence of TGFBR3L was negatively associated with plasma gonadotropin concentrations in males (P-FSH median 5.5 IU/L [IQR 2.9-9.6] and median 3.0 [IQR 1.8-5.6] in TGFBR3L negative and positive tumours respectively, p = 0.008) and P-LH (median 2.8 IU/L [IQR 1.9-3.7] and median 1.8 [IQR 1.1-3.0] in TGFBR3L negative and positive tumours respectively, p = 0.03). TGFBR3 stained positive in 22% (n = 25) of gonadotroph tumours with no correlation to TGFBR3L. CONCLUSION: TGFBR3L was selectively detected in half (52%) of gonadotroph NF-PitNETs. The association to LHß staining and plasma gonadotropins suggests that TGFBR3L may be involved in hormone production in gonadotroph NF-PitNETs.

A coordinated strategy for a simple, pragmatic approach to the early identification of the ultra-high-risk patient with diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is the most frequent aggressive lymphoma seen in clinical practice. Despite huge strides in understanding its biology, front-line therapy has remained unchanged for decades. Roughly one-third of patients have primary refractory or relapse following the end of conventional first-line therapy. The outcome of patients with primary refractory disease and those with early relapse (defined as relapse less than 1 year from the end of therapy) is markedly inferior to those with later relapse and is exemplified by dismal overall survival. In this article, the authors term patients with features that identify them as being at particularly high-risk for either primary refractory disease or early relapse, as 'ultra-high-risk'. As new treatment options become established (e.g. bispecific T-cell engagers, chimeric antigen receptor 'CAR' T-cells and antibody-drug conjugates), it is likely that there will be a push to incorporate some of these agents into the first-line setting for patients identified as ultra-high-risk. In this review, the authors outline advances in positron emission tomography, widely available laboratory assays and clinical prognosticators, which can detect a high proportion of patients with ultra-high-risk disease. Since these approaches are pragmatic and able to be adopted widely, they could be incorporated into routine clinical practice.

Pre-treatment total metabolic tumour volumes in lymphoma: Does quantity matter?

Positron emission tomography/computed tomography (PET/CT) is used for the staging of lymphomas. Clinical information, such as Ann Arbor stage and number of involved sites, is derived from baseline staging and correlates with tumour volume. With modern imaging software, exact measures of total metabolic tumour volumes (tMTV) can be determined, in a semi- or fully-automated manner. Several technical factors, such as tumour segmentation and PET/CT technology influence tMTV and there is no consensus on a standardized uptake value (SUV) thresholding method, or how to include the volumes in the bone marrow and spleen. In diffuse large B-cell lymphoma, follicular lymphoma, peripheral T-cell lymphoma, and Hodgkin lymphoma, tMTV has been shown to predict progression-free survival and/or overall survival, after adjustments for clinical risk scores. However, most studies have used receiver operating curves to determine the optimal cut-off for tMTV and many studies did not include a training-validation approach, which led to the risk of overestimation of the independent prognostic value of tMTV. The identified cut-off values are heterogeneous, even when the same SUV thresholding method is used. Future studies should focus on testing tMTV in homogeneously-treated cohorts and seek to validate identified cut-off values externally so that a prognostic value can be documented, over and above currently used clinical surrogates for tumour volume.

Deep learning-based tumour segmentation and total metabolic tumour volume prediction in the prognosis of diffuse large B-cell lymphoma patients in 3D FDG-PET images.

OBJECTIVES: To demonstrate the effectiveness of automatic segmentation of diffuse large B-cell lymphoma (DLBCL) in 3D FDG-PET scans using a deep learning approach and validate its value in prognosis in an external validation cohort. METHODS: Two PET datasets were retrospectively analysed: 297 patients from a local centre for training and 117 patients from an external centre for validation. A 3D U-Net architecture was trained on patches randomly sampled within the PET images. Segmentation performance was evaluated by six metrics, including the Dice similarity coefficient (DSC), Jaccard similarity coefficient (JSC), sensitivity (Se), positive predictive value (PPV), Hausdorff distance 95 (HD 95), and average symmetric surface distance (ASSD). Finally, the prognostic value of predictive total metabolic tumour volume (pTMTV) was validated in real clinical applications. RESULTS: The mean DSC, JSC, Se, PPV, HD 95, and ASSD (with standard deviation) for the validation cohort were 0.78 ± 0.25, 0.69 ± 0.26, 0.81 ± 0.27, 0.82 ± 0.25, 24.58 ± 35.18, and 4.46 ± 8.92, respectively. The mean ground truth TMTV (gtTMTV) and pTMTV were 276.6 ± 393.5 cm3 and 301.9 ± 510.5 cm3 in the validation cohort, respectively. Perfect homogeneity in the Bland-Altman analysis and a strong positive correlation in the linear regression analysis (R2 linear = 0.874, p < 0.001) were demonstrated between gtTMTV and pTMTV. pTMTV (≥ 201.2 cm3) (PFS: HR = 3.097, p = 0.001; OS: HR = 6.601, p < 0.001) was shown to be an independent factor of PFS and OS. CONCLUSIONS: The FCN model with a U-Net architecture can accurately segment lymphoma lesions and allow fully automatic assessment of TMTV on PET scans for DLBCL patients. Furthermore, pTMTV is an independent prognostic factor of survival in DLBCL patients. KEY POINTS: •The segmentation model based on a U-Net architecture shows high performance in the segmentation of DLBCL patients on FDG-PET images. •The proposed method can provide quantitative information as a predictive TMTV for predicting the prognosis of DLBCL patients.

The importance of measuring baseline tumour volume (or alternatively tumour length along with its rectal circumferential extent) in the watch-and-wait strategy in rectal cancer: a review.

BACKGROUND: The impact of the tumour volume or size on achieving clinical complete response (cCR) after radio(chemo)therapy is poorly understood. MATERIALS AND METHODS: A literature search was performed to gather data on the predictive value of baseline tumour volume or size in achieving cCR. RESULTS: In total, nine reports were identified. In two of three studies evaluating the baseline tumour volumetry, the tumour volume was the most powerful predictor for cCR. In four of six studies evaluating baseline tumour size without volumetry, tumour dimension was significantly associated with cCR, in one study reached borderline significance and in one report was insignificant. In three of four studies where a multivariable analysis was performed, the cT category did not show an independent predictive value for cCR. Because the tumour shape is often (semi)annular, its circumferential rectal extent along with the tumour length probably impact the tumour volume most, and thus, could be considered an acceptable alternative for time-consuming volumetry. CONCLUSIONS: Our review suggests that baseline tumour volume (or alternatively, tumour length along with its circumferential rectal extent) is the most relevant clinical predictor of cCR. Therefore, we postulate assessing and reporting these parameters in studies on the watch-and-wait strategy.

Deep learning-based automatic delineation of anal cancer gross tumour volume: a multimodality comparison of CT, PET and MRI.

BACKGROUND: Accurate target volume delineation is a prerequisite for high-precision radiotherapy. However, manual delineation is resource-demanding and prone to interobserver variation. An automatic delineation approach could potentially save time and increase delineation consistency. In this study, the applicability of deep learning for fully automatic delineation of the gross tumour volume (GTV) in patients with anal squamous cell carcinoma (ASCC) was evaluated for the first time. An extensive comparison of the effects single modality and multimodality combinations of computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI) have on automatic delineation quality was conducted. MATERIAL AND METHODS: 18F-fluorodeoxyglucose PET/CT and contrast-enhanced CT (ceCT) images were collected for 86 patients with ASCC. A subset of 36 patients also underwent a study-specific 3T MRI examination including T2- and diffusion-weighted imaging. The resulting two datasets were analysed separately. A two-dimensional U-Net convolutional neural network (CNN) was trained to delineate the GTV in axial image slices based on single or multimodality image input. Manual GTV delineations constituted the ground truth for CNN model training and evaluation. Models were evaluated using the Dice similarity coefficient (Dice) and surface distance metrics computed from five-fold cross-validation. RESULTS: CNN-generated automatic delineations demonstrated good agreement with the ground truth, resulting in mean Dice scores of 0.65-0.76 and 0.74-0.83 for the 86 and 36-patient datasets, respectively. For both datasets, the highest mean Dice scores were obtained using a multimodal combination of PET and ceCT (0.76-0.83). However, models based on single modality ceCT performed comparably well (0.74-0.81). T2W-only models performed acceptably but were somewhat inferior to the PET/ceCT and ceCT-based models. CONCLUSION: CNNs provided high-quality automatic GTV delineations for both single and multimodality image input, indicating that deep learning may prove a versatile tool for target volume delineation in future patients with ASCC.

Hemispheric infiltrative grade II gliomas in adults: association of residual tumour volume and extent of tumour resection with malignant transformation.

OBJECTIVES: Evaluation of the impact of surgical treatment on malignant transformation (MT) of adult supratentorial infiltrative grade II gliomas (G2G) in a series of chemotherapy and radiotherapy-naïve patients. BACKGROUND: Despite G2G are slow-growing tumours, they typically undergo MT with a subsequent fatal disease course. An extensive resection alone likely changes their biological behaviour and defers MT; however, this impact is not unequivocally confirmed. METHODS: Thirty-eight chemotherapy and radiotherapy-naïve adult patients operated from 2005 till 2014 for a G2G were investigated. Based on postoperative magnetic resonance imaging (MRI) and/or positron emission tomography follow-up (FU) scans, the patients were classified as "transformers" (15 patients in whom MT occurred during the FU-period) and "non-transformers" (23 patients). RESULTS: The follow-up period of "non-transformers" was longer (p <0.0001). After adjustment for known risk factors - age, male sex, astrocytoma histology, preoperative tumour volume, preoperative contrast enhancement and positive isocitrate dehydrogenase 1 gene mutation status - a larger log postoperative tumour volume (p=0.031) and a smaller extent of resection (p=0.0086) were associated with a shorter MT-free survival. CONCLUSION: In our series, less extensive resections were associated with a shorter time to MT. Our data support an adoption of techniques enabling extensive G2G resections, such as intraoperative imaging and awake resections, into everyday routine (Tab. 1, Fig. 2, Ref. 40).

Motion-compensated FDG PET/CT for oesophageal cancer.

PURPOSE: Respiratory-induced motion of oesophageal tumours and lymph nodes can influence positron-emission tomography/computed tomography (PET/CT). The aim was to compare standard three-dimensional (3D) and motion-compensated PET/CT regarding standardized uptake value (SUV), metabolic tumour volume (MTV) and detection of lymph node metastases. METHODS: This prospective observational study (NCT02424864) included 37 newly diagnosed oesophageal cancer patients. Diagnostic PET/CT was reconstructed in 3D and motion-compensated PET/CT. MTVs of the primary tumour were calculated using an automated region-growing algorithm with SUV thresholds of 2.5 (MTV2.5) and ≥ 50% of SUVmax (MTV50%). Blinded for reconstruction method, a nuclear medicine physician assessed all lymph nodes showing 18F­fluorodeoxyglucose uptake for their degree of suspicion. RESULTS: The mean (95% CI) SUVmax of the primary tumour was 13.1 (10.6-15.5) versus 13.0 (10.4-15.6) for 3D and motion-compensated PET/CT, respectively. MTVs were also similar between the two techniques. Bland-Altman analysis showed mean differences between both measurements (95% limits of agreement) of 0.08 (-3.60-3.75), -0.26 (-2.34-1.82), 4.66 (-29.61-38.92) cm3 and -0.95 (-19.9-18.0) cm3 for tumour SUVmax, lymph node SUVmax, MTV2.5 and MTV50%, respectively. Lymph nodes were classified as highly suspicious (30/34 nodes), suspicious (20/22) and dubious (66/59) for metastases on 3D/motion-compensated PET/CT. No additional lymph node metastases were found on motion-compensated PET/CT. SUVmax of the most intense lymph nodes was similar for both scans: mean (95% CI) 6.6 (4.3-8.8) and 6.8 (4.5-9.1) for 3D and motion-compensated, respectively. CONCLUSION: SUVmax of the primary oesophageal tumour and lymph nodes was comparable on 3D and motion-compensated PET/CT. The use of motion-compensated PET/CT did not improve lymph node detection.

Fully automatic segmentation of diffuse large B cell lymphoma lesions on 3D FDG-PET/CT for total metabolic tumour volume prediction using a convolutional neural network.

PURPOSE: Lymphoma lesion detection and segmentation on whole-body FDG-PET/CT are a challenging task because of the diversity of involved nodes, organs or physiological uptakes. We sought to investigate the performances of a three-dimensional (3D) convolutional neural network (CNN) to automatically segment total metabolic tumour volume (TMTV) in large datasets of patients with diffuse large B cell lymphoma (DLBCL). METHODS: The dataset contained pre-therapy FDG-PET/CT from 733 DLBCL patients of 2 prospective LYmphoma Study Association (LYSA) trials. The first cohort (n = 639) was used for training using a 5-fold cross validation scheme. The second cohort (n = 94) was used for external validation of TMTV predictions. Ground truth masks were manually obtained after a 41% SUVmax adaptive thresholding of lymphoma lesions. A 3D U-net architecture with 2 input channels for PET and CT was trained on patches randomly sampled within PET/CTs with a summed cross entropy and Dice similarity coefficient (DSC) loss. Segmentation performance was assessed by the DSC and Jaccard coefficients. Finally, TMTV predictions were validated on the second independent cohort. RESULTS: Mean DSC and Jaccard coefficients (± standard deviation) in the validations set were 0.73 ± 0.20 and 0.68 ± 0.21, respectively. An underestimation of mean TMTV by - 12 mL (2.8%) ± 263 was found in the validation sets of the first cohort (P = 0.27). In the second cohort, an underestimation of mean TMTV by - 116 mL (20.8%) ± 425 was statistically significant (P = 0.01). CONCLUSION: Our CNN is a promising tool for automatic detection and segmentation of lymphoma lesions, despite slight underestimation of TMTV. The fully automatic and open-source features of this CNN will allow to increase both dissemination in routine practice and reproducibility of TMTV assessment in lymphoma patients.

Post-operative volumes following endoscopic surgery for non-functioning pituitary macroadenomas are predictive of further intervention, but not endocrine outcomes.

BACKGROUND: Transsphenoidal surgery (TSS) remains the treatment of choice for non-functioning pituitary macroadenomas (NFPMA). The value of measuring tumour volumes before and after surgery, and its influence on endocrine outcomes and further treatment of the residual or recurrent tumour are unknown. METHODS: Data from patients who underwent endoscopic TSS for a NFPMA (2009-2018) in a UK tertiary centre were analysed for pre- and post-operative endocrine and surgical outcomes. RESULTS: Of 173 patients with NFPMA, 159 (61% male) were treatment naïve. At presentation, 76.2% (77/101) had ≥1 pituitary axis deficit. Older age (p = 0.002) was an independent predictor for multiple hormonal deficiencies. Preoperative tumour volume did not correlate with degree of hypopituitarism. Postoperative tumour volume and extent of tumour resection were not predictive of new onset hypopituitarism. Hormonal recovery was observed in 16 patients (20.8%) with impaired pituitary function, with the greatest recovery in the hypothalamic-pituitary-adrenal axis (21.2%, 7/33). A larger residual tumour volume was predictive of adjuvant radiotherapy (3.40 vs. 1.24 cm3, p = 0.005) and likelihood for repeat surgery (5.40 vs. 1.67cm3, p = 0.004). CONCLUSION: Pre- and post-operative NFPMA volumes fail to predict the number of pituitary hormone deficits, however, greater post-operative residual volumes increase the likelihood of further intervention to control tumour growth.

Pre-treatment metabolic tumour volume and total lesion glycolysis are superior to conventional positron-emission tomography/computed tomography variables for outcome prediction in patients with newly diagnosed multiple myeloma in clinical practice.

Metabolic tumour volume (MTV) and total lesion glycolysis (TLG) are positron-emission tomography/computed tomography (PET/CT) variables for predicting multiple myeloma's (MM) outcome. We retrospectively investigated and compared the predictive value of MTV, TLG and high-risk PET/CT variables in clinical practice in 185 patients with newly diagnosed symptomatic MM. High-risk PET/CT findings were defined as the presence of at least one of the following: more than three focal lesions, maximum standardised uptake value (SUVmax ) >4·2 and extramedullary disease. MTV was defined as the volume of myeloma lesions visualised on PET/CT with SUV ≥ 2·5. TLG was calculated as the sum of the product of the average SUV and MTV of all lesions. The mortality prediction optimal cut-off values for MTV and TLG were 56·4 cm3 and 166·4 g, respectively. High-burden MTV (≥56·4 cm3 ), TLG (≥166·4 g) and high-risk PET/CT findings differed significantly in progression-free survival (PFS) and overall survival (OS). High-burden MTV and TLG findings also predicted survival outcomes in young patients (age <75 years) and patients with high-risk chromosomal abnormalities. High-burden MTV and TLG independently predicted both worse PFS and OS. Pre-treatment MTV and TLG independently predicted survival outcomes in clinical practice and may be more useful than high-risk PET/CT variables.

Three-dimensional (3D) magnetic resonance volume assessment and loco-regional failure in anal cancer: early evaluation case-control study.

BACKGROUND: The primary aim was to test the hypothesis that deriving pre-treatment 3D magnetic resonance tumour volume (mrTV) quantification improves performance characteristics for the prediction of loco-regional failure compared with standard maximal tumour diameter (1D) assessment in patients with squamous cell carcinoma of the anus undergoing chemoradiotherapy. METHODS: We performed an early evaluation case-control study at two UK centres (2007-2014) in 39 patients with loco-regional failure (cases), and 41 patients disease-free at 3 years (controls). mrTV was determined using the summation of areas method (Volsum). Reproducibility was assessed using intraclass concordance correlation (ICC) and Bland-Altman limits of agreements. We derived receiver operating curves using logistic regression models and expressed accuracy as area under the curve (ROCAUC). RESULTS: The median time per patient for Volsum quantification was 7.00 (inter-quartile range, IQR: 0.57-12.48) minutes. Intra and inter-observer reproducibilities were generally good (ICCs from 0.79 to 0.89) but with wide limits of agreement (intra-observer: - 28 to 31%; inter-observer: - 28 to 46%). Median mrTVs were greater for cases (32.6 IQR: 21.5-53.1 cm3) than controls (9.9 IQR: 5.7-18.1 cm3, p < 0.0001). The ROCAUC for mrT-size predicting loco-regional failure was 0.74 (95% CI: 0.63-0.85) improving to 0.82 (95% CI: 0.72-0.92) when replaced with mrTV (test for ROC differences, p = 0.024). CONCLUSION: Preliminary results suggest that the replacement of mrTV for mrT-size improves prediction of loco-regional failure after chemoradiotherapy for squamous cell carcinoma of the anus. However, mrTV calculation is time consuming and variation in its reproducibility are drawbacks with the current technology.

Baseline PET features to predict prognosis in primary mediastinal B cell lymphoma: a comparative analysis of different methods for measuring baseline metabolic tumour volume.

PURPOSE: This study assessed the performance of four different methods for the estimation of metabolic tumour volume (MTV) in primary mediastinal B cell lymphoma (PMBCL). METHOD: MTV was estimated using either a region growing automatic software program (RG) or a fixed threshold (FT) segmentation algorithm with the three most common cut-offs proposed in the literature (i.e., 25% and 41% of the SUVmax and SUV value ≥2.5). We compared these four methods using phantoms that simulated different set-ups of the main imaging characteristics of PMBCL (volume, shape, 18-FDG uptake and intra-lesion distribution) and assessed their performance in 103 PMBCL patients enrolled in the International Extranodal Lymphoma Study Group-26 (IELSG-26) study. RESULTS: There was good correlation between MTV values estimated in vitro and in vivo using the different methods. The 25% FT cut-off (FT25%) provided the most accurate MTV evaluation in the phantoms. The cut-off at SUV 2.5 (FT2.5) resulted in MTV overestimation that particularly increased with high SUV values. The 41% cut-off (FT41%) showed MTV underestimation that was more evident when there were high levels of heterogeneity in tracer distribution. Shape of the lesion did not affect MTV computation. The RG algorithm provided a systematic slight MTV underestimation without significant changes due to lesion characteristics. We observed analogous trends for the MTV estimation in patients, with very different derived thresholds for the four methods. Optimal cut-offs for predicting progression-free survival (PFS) ranged from 213 to 831 ml. All methods predicted PFS with similar negative predictive values (94-95%) but different positive predictive values (23-45%). CONCLUSIONS: The different methods result in significantly different MTV cut-off values. All allow risk stratification in PMBCL, but FT25% showed the best capacity to predict disease progression in the patient cohort and provided the best accuracy in the phantom model.

Prognostic value of metabolic tumour volume on baseline 18F-FDG PET/CT in addition to NCCN-IPI in patients with diffuse large B-cell lymphoma: further stratification of the group with a high-risk NCCN-IPI.

PURPOSE: The purpose of this study was to determine the prognostic value of metabolic volumetric parameters as a quantitative index on pre-treatment 18F-FDG PET/CT in addition to the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) in patients with diffuse large B-cell lymphoma (DLBCL). METHODS: A total of 103 consecutive patients with DLBCL and baseline FDG PET/CT were retrospectively evaluated. Quantitative metabolic parameters, including total metabolic tumour volume (TMTV) using a standardized uptake value (SUV) of ≥2.5 as the threshold, were estimated. Receiver operating characteristic curve analysis was used to determine the optimal cut-off values for the metabolic parameters. The relationships between study variables and patient survival were tested using Cox regression analysis. Patient survival rates were derived from Kaplan-Meier curves and compared using the log-rank test. RESULTS: Median follow-up was 34 months. In patients with a low TMTV (<249 cm3), the 3-year progression free survival (PFS) rate was 83% and the overall survival (OS) rate was 92%, in contrast to 41% and 57%, respectively, in those with a high TMTV (≥249 cm3). In univariate analysis, a high TMTV and NCCN-IPI ≥4 were associated with inferior PFS and OS (P < 0.0001 for all), as was a high total lesion glycolysis (P = 0.004 and P = 0.005, respectively). In multivariate analysis, TMTV and NCCN-IPI were independent predictors of PFS (hazard ratio, HR, 3.11, 95% confidence interval, CI, 1.37-7.07, P = 0.007, and HR 3.42, 95% CI 1.36-8.59, P = 0.009, respectively) and OS (HR 3.41, 95% CI 1.24-9.38, P = 0.017, and HR 5.06, 95% CI 1.46-17.60, P = 0.014, respectively). TMTV was able to separate patients with a high-risk NCCN-IPI of ≥4 (n = 62) into two groups with significantly different outcomes; patients with low TMTV (n = 16) had a 3-year PFS rate of 75% and an OS rate of 88%, while those with a high TMTV had a 3-year PFS rate of 32% and an OS rate of 47% (χ2 = 7.92, P = 0.005, and χ2 = 8.26, P = 0.004, respectively). However, regardless of TMTV, patients with a low-risk NCCN-IPI of <4 (n = 41) had excellent outcomes (3-year PFS and OS rates of 85% and 95%, respectively). CONCLUSION: Pretreatment TMTV was an independent predictor of survival in patients with DLBCL. Importantly, TMTV had an additive prognostic value in patients with a high-risk NCCN-IPI. Thus, the combination of baseline TMTV with NCCN-IPI may improve the prognostication and may be helpful guide the decision for intensive therapy and clinical trials, especially in DLBCL patients with a high-risk NCCN-IPI.

FET PET reveals considerable spatial differences in tumour burden compared to conventional MRI in newly diagnosed glioblastoma.

PURPOSE: Areas of contrast enhancement (CE) on MRI are usually the target for resection or radiotherapy target volume definition in glioblastomas. However, the solid tumour mass may extend beyond areas of CE. Amino acid PET can detect parts of the tumour that show no CE. We systematically investigated tumour volumes delineated by amino acid PET and MRI in patients with newly diagnosed, untreated glioblastoma. METHODS: Preoperatively, 50 patients with neuropathologically confirmed glioblastoma underwent O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET, and fluid-attenuated inversion recovery (FLAIR) and contrast-enhanced MRI. Areas of CE were manually segmented. FET PET tumour volumes were segmented using a tumour-to-brain ratio of ≥1.6. The percentage overlap volumes, and Dice and Jaccard spatial similarity coefficients (DSC, JSC) were calculated. FLAIR images were evaluated visually. RESULTS: In 43 patients (86%), the FET tumour volume was significantly larger than the CE volume (21.5 ± 14.3 mL vs. 9.4 ± 11.3 mL; P < 0.001). Forty patients (80%) showed both increased uptake of FET and CE. In these 40 patients, the spatial similarity between FET uptake and CE was low (mean DSC 0.39 ± 0.21, mean JSC 0.26 ± 0.16). Ten patients (20%) showed no CE, and one of these patients showed no FET uptake. In five patients (10%), increased FET uptake was present outside areas of FLAIR hyperintensity. CONCLUSION: Our results show that the metabolically active tumour volume delineated by FET PET is significantly larger than tumour volume delineated by CE. Furthermore, the results strongly suggest that the information derived from both imaging modalities should be integrated into the management of patients with newly diagnosed glioblastoma.

Cancer core length from targeted biopsy: an index of prostate cancer volume and pathological stage.

OBJECTIVE: To study the relationship of maximum cancer core length (MCCL), on targeted biopsy (TB) of magnetic resonance imaging (MRI)-visible index lesions, to volume of that tumour found at radical prostatectomy (RP). PATIENTS AND METHODS: In all, 205 men undergoing fusion biopsy and RP were divided into two groups: 136 in whom the MCCL came from an index MRI-visible lesion (TB) and 69 in whom MCCL came from a non-targeted lesion (non-targeted biopsy [NTB]). MRI was 3-T multi-parametric and biopsy was via MRI-ultrasonography fusion. RESULTS: In the TB group, MCCL correlated with volume of clinically significant index tumours (ρ = 0.44-0.60, P < 0.01). The correlation was similar for first and repeat biopsy and for transition and peripheral zone lesions (ρ = 0.42-0.49, P < 0.01). No correlations were found in the NTB group. TB MCCL (6-10 and >10 mm) and MRI lesion diameter (>20 mm) were independently associated with tumour volume. TB MCCLs >10 mm and Gleason scores >7 were each associated with pathological T3 disease (odds ratios 5.73 and 5.04, respectively), but MRI lesion diameter lesion was not. CONCLUSIONS: MCCL on a TB from an MRI-visible lesion is an independent predictor of both cancer volume and pathological stage. This relationship does not exist for MCCL from a NTB core. Quantifying CCL on MRI-TBs may have a value, not previously described, to risk-stratify patients with prostate cancer before treatment.

Nonlinear pharmacokinetics of rituximab in non-Hodgkin lymphomas: A pilot study.

AIMS: Rituximab is an anti-CD20 monoclonal antibody approved in non-Hodgkin lymphoma (NHL). This study aimed to assess the relationship between antigen mass and nonlinear pharmacokinetics of rituximab in NHL patients. METHODS: In a retrospective cohort of 25 NHL patients treated with rituximab, antigen mass was assessed at baseline by measuring metabolic tumour volume (MTV) by positron emission tomography. Rituximab pharmacokinetics was described using a semimechanistic 2-compartment model including a latent target antigen. Rituximab target-mediated elimination was described as irreversible binding between rituximab and it target. Histology (follicular or diffuse large B-cell lymphomas), initial MTV and body weight were tested as covariates on pharmacokinetic parameters. RESULTS: The model allowed a satisfactory description of rituximab serum concentrations. Target-mediated elimination was maximum at the beginning of treatment and became negligible towards the end of follow-up. The second-order elimination of rituximab due to target binding and complex elimination increased with baseline MTV. Central volume of distribution increased with body weight (P = .022) and baseline MTV (P = .005). CONCLUSIONS: This study quantified for the first time the target-mediated elimination of rituximab in NHL patients and confirmed rituximab retention by antigen mass.

Comparative Analyses of Tumour Volume Doubling Times for Periocular and Non-periocular Head and Neck Basal Cell Carcinomas.

Basal cell carcinomas are the commonest solid malignancy in humans and thought to grow faster in the periocular region. We measured growth rates between periocular and non-periocular nodular basal cell carcinomas in the head and neck region from high-resolution digital photos and operative notes. The non-periocular basal cell carcinomas (head and neck) showed a mean tumour volume doubling time of 129.8 ± 21.74 (n = 79) days, and the periocular basal cell carcinoma a mean of 177.5 ± 37.21 (n = 47) days. The unpaired t-test with Welch correction showed that this difference was not significant (p = 0.2719). The mean tumour volume doubling time was 147.59 ± 37.75 days for head and neck basal cell carcinomas overall. For the first time, tumour volume doubling times for nodular basal cell carcinomas in the periocular versus non-periocular regions for the head and neck area were analysed, with no significant differences demonstrated. Further, comparison of basal cell carcinoma growth rates with other common solid tumours confirmed that basal cell carcinomas are slow growing malignancies.