Heterogeneous Tumor-Immune Microenvironments among Differentially Growing Metastases in an Ovarian Cancer Patient.

We present an exceptional case of a patient with high-grade serous ovarian cancer, treated with multiple chemotherapy regimens, who exhibited regression of some metastatic lesions with concomitant progression of other lesions during a treatment-free period. Using immunogenomic approaches, we found that progressing metastases were characterized by immune cell exclusion, whereas regressing and stable metastases were infiltrated by CD8+ and CD4+ T cells and exhibited oligoclonal expansion of specific T cell subsets. We also detected CD8+ T cell reactivity against predicted neoepitopes after isolation of cells from a blood sample taken almost 3 years after the tumors were resected. These findings suggest that multiple distinct tumor immune microenvironments co-exist within a single individual and may explain in part the heterogeneous fates of metastatic lesions often observed in the clinic post-therapy. VIDEO ABSTRACT.

ESR Essentials: characterisation and staging of adnexal masses with MRI and CT-practice recommendations by ESUR.

Ovarian masses encompass various conditions, from benign to highly malignant, and imaging plays a vital role in their diagnosis and management. Ultrasound, particularly transvaginal ultrasound, is the foremost diagnostic method for adnexal masses. Magnetic Resonance Imaging (MRI) is advised for more precise characterisation if ultrasound results are inconclusive. The ovarian-adnexal reporting and data system (O-RADS) MRI lexicon and scoring system provides a standardised method for describing, assessing, and categorising the risk of each ovarian mass. Determining a histological differential diagnosis of the mass may influence treatment decision-making and treatment planning. When ultrasound or MRI suggests the possibility of cancer, computed tomography (CT) is the preferred imaging technique for staging. It is essential to outline the extent of the malignancy, guide treatment decisions, and evaluate the feasibility of cytoreductive surgery. This article provides a comprehensive overview of the key imaging processes in evaluating and managing ovarian masses, from initial diagnosis to initial treatment. It also includes pertinent recommendations for properly performing and interpreting various imaging modalities. KEY POINTS: MRI is the modality of choice for indeterminate ovarian masses at ultrasound, and the O-RADS MRI lexicon and score enable unequivocal communication with clinicians. CT is the recommended modality for suspected ovarian masses to tailor treatment and surgery. Multidisciplinary meetings integrate information and help decide the most appropriate treatment for each patient.

Evaluating the quality of radiomics-based studies for endometrial cancer using RQS and METRICS tools.

OBJECTIVE: To assess the methodological quality of radiomics-based models in endometrial cancer using the radiomics quality score (RQS) and METhodological radiomICs score (METRICS). METHODS: We systematically reviewed studies published by October 30th, 2023. Inclusion criteria were original radiomics studies on endometrial cancer using CT, MRI, PET, or ultrasound. Articles underwent a quality assessment by novice and expert radiologists using RQS and METRICS. The inter-rater reliability for RQS and METRICS among radiologists with varying expertise was determined. Subgroup analyses were performed to assess whether scores varied according to study topic, imaging technique, publication year, and journal quartile. RESULTS: Sixty-eight studies were analysed, with a median RQS of 11 (IQR, 9-14) and METRICS score of 67.6% (IQR, 58.8-76.0); two different articles reached maximum RQS of 19 and METRICS of 90.7%, respectively. Most studies utilised MRI (82.3%) and machine learning methods (88.2%). Characterisation and recurrence risk stratification were the most explored outcomes, featured in 35.3% and 19.1% of articles, respectively. High inter-rater reliability was observed for both RQS (ICC: 0.897; 95% CI: 0.821, 0.946) and METRICS (ICC: 0.959; 95% CI: 0.928, 0.979). Methodological limitations such as lack of external validation suggest areas for improvement. At subgroup analyses, no statistically significant difference was noted. CONCLUSIONS: Whilst using RQS, the quality of endometrial cancer radiomics research was apparently unsatisfactory, METRICS depicts a good overall quality. Our study highlights the need for strict compliance with quality metrics. Adhering to these quality measures can increase the consistency of radiomics towards clinical application in the pre-operative management of endometrial cancer. CLINICAL RELEVANCE STATEMENT: Both the RQS and METRICS can function as instrumental tools for identifying different methodological deficiencies in endometrial cancer radiomics research. However, METRICS also reflected a focus on the practical applicability and clarity of documentation. KEY POINTS: The topic of radiomics currently lacks standardisation, limiting clinical implementation. METRICS scores were generally higher than the RQS, reflecting differences in the development process and methodological content. A positive trend in METRICS score may suggest growing attention to methodological aspects in radiomics research.

Perceptions of radiologists on structured reporting for cancer imaging-a survey by the European Society of Oncologic Imaging (ESOI).

OBJECTIVES: To assess radiologists' current use of, and opinions on, structured reporting (SR) in oncologic imaging, and to provide recommendations for a structured report template. MATERIALS AND METHODS: An online survey with 28 questions was sent to European Society of Oncologic Imaging (ESOI) members. The questionnaire had four main parts: (1) participant information, e.g., country, workplace, experience, and current SR use; (2) SR design, e.g., numbers of sections and fields, and template use; (3) clinical impact of SR, e.g., on report quality and length, workload, and communication with clinicians; and (4) preferences for an oncology-focused structured CT report. Data analysis comprised descriptive statistics, chi-square tests, and Spearman correlation coefficients. RESULTS: A total of 200 radiologists from 51 countries completed the survey: 57.0% currently utilized SR (57%), with a lower proportion within than outside of Europe (51.0 vs. 72.7%; p = 0.006). Among SR users, the majority observed markedly increased report quality (62.3%) and easier comparison to previous exams (53.5%), a slightly lower error rate (50.9%), and fewer calls/emails by clinicians (78.9%) due to SR. The perceived impact of SR on communication with clinicians (i.e., frequency of calls/emails) differed with radiologists' experience (p < 0.001), and experience also showed low but significant correlations with communication with clinicians (r = - 0.27, p = 0.003), report quality (r = 0.19, p = 0.043), and error rate (r = - 0.22, p = 0.016). Template use also affected the perceived impact of SR on report quality (p = 0.036). CONCLUSION: Radiologists regard SR in oncologic imaging favorably, with perceived positive effects on report quality, error rate, comparison of serial exams, and communication with clinicians. CLINICAL RELEVANCE STATEMENT: Radiologists believe that structured reporting in oncologic imaging improves report quality, decreases the error rate, and enables better communication with clinicians. Implementation of structured reporting in Europe is currently below the international level and needs society endorsement. KEY POINTS: • The majority of oncologic imaging specialists (57% overall; 51% in Europe) use structured reporting in clinical practice. • The vast majority of oncologic imaging specialists use templates (92.1%), which are typically cancer-specific (76.2%). • Structured reporting is perceived to markedly improve report quality, communication with clinicians, and comparison to prior scans.

RadioGraphics Update: 2023 FIGO Staging System for Endometrial Cancer.

Editor's Note.-RadioGraphics Update articles supplement or update information found in full-length articles previously published in RadioGraphics. These updates, written by at least one author of the previous article, provide a brief synopsis that emphasizes important new information such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes.

TRImodal DEfinitive invasive vagiNal carcinoma Treatment (TRIDENT protocol): how a standardized approach may change prognostic outcomes.

OBJECTIVE: Vaginal carcinoma is a rare malignancy accounting for 1-2% of all gynecological cancers. Surgery has a limited role, while definitive radiotherapy-chemotherapy followed by interventional radiotherapy is considered a valid alternative. The aim of the TRIDENT (TRImodal DEfinitive invasive vagiNal carcinoma Treatment) pilot study was to report the results of a modern standardized trimodal protocol treatment consisting of image guided definitive radiotherapy-chemotherapy followed by image guided interventional radiotherapy in terms of safety and efficacy. METHODS: Between January 2019 and December 2021, we analyzed 21 consecutive patients with primary vaginal cancer who had received radiotherapy-chemotherapy followed by interventional radiotherapy. The primary study endpoint was local control, and secondary endpoints were metastasis free survival, overall survival, and rate and severity of acute and late toxicities. RESULTS: 14 patients had FIGO (International Federation of Gynecology and Obstetrics) stage II, five patients had stage III, and two had stage IVB disease. Median total external beam radiotherapy dose for the tumor was 45 Gy. Median total dose on positive nodes was 60 Gy. Median total dose for interventional radiotherapy was 28 Gy over four high dose rate fractions to achieve between 85 and 95 Gy equivalent dose, in 2 Gy fractions (EQD2)α/ß10, to the high risk clinical target volume, and 60 Gy EQD2α/ß10 to the intermediate risk clinical target volume. All patients received weekly platinum based chemotherapy. Median follow-up was 20 months (range 10-56 months). Two year actuarial local control, metastasis free survival, and overall survival rate were 79.4%, 90.5%, and 79.4%, respectively. In terms of acute toxicity, there were no grade 4 events and only one acute grade (G) 3 toxicity (skin). Only vaginal stenosis (G3) was documented 12 months after therapy due to late toxicity. CONCLUSIONS: In this study, definitive radiotherapy-chemotherapy followed by interventional radiotherapy was a safe and effective treatment modality for primary vaginal cancer.

Hug sign in intraprocedural cone-beam-CT to predict short-term response to combined treatment of hepatocellular carcinoma.

OBJECTIVES: Combined treatment of ablation and chemoembolization for hepatocellular carcinoma represents a promising therapy to increase treatment efficacy and improve patient survival. The "hug sign" is a recently introduced radiological sign consisting in deposition of beads/contrast agent during transarterial chemoembolization in the hyperemic area surrounding the post-ablation volume, seen during intraprocedural unenhanced cone-beam CT, that may indicate intraprocedural success. Aim of our retrospective study was to analyze the usefulness of the "hug sign" at the intraprocedural unenhanced cone-beam CT as an early predictor of response to combined treatment, based on the hug sign angle. MATERIALS AND METHODS: Between January 2017 and September 2021 all patients with hepatocellular carcinoma which underwent a combined treatment of thermal ablation followed by chemoembolization were enrolled. All treated patients underwent immediate post-procedural unenhanced cone-beam CT to evaluate the deposition of contrast agent, lipiodol or radiopaque beads and to assess the percentage of coverage of the ablated area with the contrast agent (hug sign angle). Patients with missing pre-procedural, intra-procedural and/or post-procedural data/imaging, or with poor-quality post-procedural cone-beam CT images were excluded. RESULTS: 128 patients (mean age, 69.3 years ± 1.1 [standard deviation]; 87 men) were evaluated. Our study evidenced that 84.4% (81/85) of patients with a hug sign angle of 360° had no residual tumor at the first 1-/3-months follow-up examination. A hug sign angle of 360° also showed to be an independent protective factor against residual tumor at multivariate analysis. CONCLUSION: Unenhanced cone-beam CT performed at the end of a combined treatment with ablation plus chemoembolization can effectively predict an early treatment response on radiological images, when a hug sign angle of 360° was detected.

The multispeciality approach to the management of localised kidney cancer.

Historically, kidney cancer was approached in a siloed single-speciality way, with urological surgeons managing the localised stages of the disease and medical oncologists caring for patients if metastases developed. However, improvements in the management of localised kidney cancer have occurred rapidly over the past two decades with greater understanding of the disease biology, diagnostic options, and innovations in curative treatments. These developments are favourable for patients but provide a substantially more complex landscape for patients and clinicians to navigate, with associated challenging decisions about who to treat, how, and when. As such, the skill sets needed to manage the various aspects of the disease and guide patients appropriately outstrips the capabilities of one particular specialist, and the evolution of a multispeciality approach to the management of kidney cancer is now essential. In this Review, we summarise the current best multispeciality practice for the management of localised kidney cancer and the areas in need of further research and development.

Lung cancer multi-omics digital human avatars for integrating precision medicine into clinical practice: the LANTERN study.

BACKGROUND: The current management of lung cancer patients has reached a high level of complexity. Indeed, besides the traditional clinical variables (e.g., age, sex, TNM stage), new omics data have recently been introduced in clinical practice, thereby making more complex the decision-making process. With the advent of Artificial intelligence (AI) techniques, various omics datasets may be used to create more accurate predictive models paving the way for a better care in lung cancer patients. METHODS: The LANTERN study is a multi-center observational clinical trial involving a multidisciplinary consortium of five institutions from different European countries. The aim of this trial is to develop accurate several predictive models for lung cancer patients, through the creation of Digital Human Avatars (DHA), defined as digital representations of patients using various omics-based variables and integrating well-established clinical factors with genomic data, quantitative imaging data etc. A total of 600 lung cancer patients will be prospectively enrolled by the recruiting centers and multi-omics data will be collected. Data will then be modelled and parameterized in an experimental context of cutting-edge big data analysis. All data variables will be recorded according to a shared common ontology based on variable-specific domains in order to enhance their direct actionability. An exploratory analysis will then initiate the biomarker identification process. The second phase of the project will focus on creating multiple multivariate models trained though advanced machine learning (ML) and AI techniques for the specific areas of interest. Finally, the developed models will be validated in order to test their robustness, transferability and generalizability, leading to the development of the DHA. All the potential clinical and scientific stakeholders will be involved in the DHA development process. The main goals aim of LANTERN project are: i) To develop predictive models for lung cancer diagnosis and histological characterization; (ii) to set up personalized predictive models for individual-specific treatments; iii) to enable feedback data loops for preventive healthcare strategies and quality of life management. DISCUSSION: The LANTERN project will develop a predictive platform based on integration of multi-omics data. This will enhance the generation of important and valuable information assets, in order to identify new biomarkers that can be used for early detection, improved tumor diagnosis and personalization of treatment protocols. ETHICS COMMITTEE APPROVAL NUMBER: 5420 - 0002485/23 from Fondazione Policlinico Universitario Agostino Gemelli IRCCS - Università Cattolica del Sacro Cuore Ethics Committee. TRIAL REGISTRATION: clinicaltrial.gov - NCT05802771.

Time series radiomics for the prediction of prostate cancer progression in patients on active surveillance.

Serial MRI is an essential assessment tool in prostate cancer (PCa) patients enrolled on active surveillance (AS). However, it has only moderate sensitivity for predicting histopathological tumour progression at follow-up, which is in part due to the subjective nature of its clinical reporting and variation among centres and readers. In this study, we used a long short-term memory (LSTM) recurrent neural network (RNN) to develop a time series radiomics (TSR) predictive model that analysed longitudinal changes in tumour-derived radiomic features across 297 scans from 76 AS patients, 28 with histopathological PCa progression and 48 with stable disease. Using leave-one-out cross-validation (LOOCV), we found that an LSTM-based model combining TSR and serial PSA density (AUC 0.86 [95% CI: 0.78-0.94]) significantly outperformed a model combining conventional delta-radiomics and delta-PSA density (0.75 [0.64-0.87]; p = 0.048) and achieved comparable performance to expert-performed serial MRI analysis using the Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation (PRECISE) scoring system (0.84 [0.76-0.93]; p = 0.710). The proposed TSR framework, therefore, offers a feasible quantitative tool for standardising serial MRI assessment in PCa AS. It also presents a novel methodological approach to serial image analysis that can be used to support clinical decision-making in multiple scenarios, from continuous disease monitoring to treatment response evaluation. KEY POINTS: •LSTM RNN can be used to predict the outcome of PCa AS using time series changes in tumour-derived radiomic features and PSA density. •Using all available TSR features and serial PSA density yields a significantly better predictive performance compared to using just two time points within the delta-radiomics framework. •The concept of TSR can be applied to other clinical scenarios involving serial imaging, setting out a new field in AI-driven radiology research.

The value of MRI in quantification of parametrial invasion and association with prognosis in locally advanced cervical cancer: the "PLACE" study.

OBJECTIVE: This retrospective observational study aims to evaluate the association between the extent of parametrial invasion (PMI) and disease-free survival (DFS) and cancer-specific survival (CSS) in patients with locally advanced cervical cancer (LACC). MATERIALS AND METHODS: This study included patients with LACC showing parametrial invasion at Magnetic Resonance Imaging (MRI). They were treated with neoadjuvant chemo-radiotherapy (CT/RT) before undergoing radical hysterectomy. The staging MRIs were reviewed retrospectively. Measurements of maximum PMI (PMImax) and parametrial length were taken bilaterally. After that, PMIratio was calculated by dividing PMImax by parametrial length. Analysis was conducted on homogeneous subsets of patients, grouped based on their pathological lymph nodal evaluation (N- and N+). Correlations between PMImax and PMIratio with DFS and CSS were evaluated in both the N- and N+ groups, employing univariable Cox regression analysis. RESULTS: Out of 221 patients, 126 (57%) had non-metastatic lymph nodes (N-), while 95 (43%) had metastatic lymph nodes (N+). The median observation period for all these patients was 73 months (95% confidence interval [CI]: 66-77). The 5-year DFS and CSS probability rates were 75% and 85.7%, respectively, for the N- group and 54.3% and 73.6%, respectively, for the N+ group. A higher PMImax (hazard ratio [HR] = 1.09) and PMIratio (HR = 1.04) correlated with worse overall survival in patients in the N- group (p = 0.025 and p = 0.042). These parameters did not show a significant statistical association in the N+ group. CONCLUSIONS: The degree of PMI evaluated on MRI affects outcome in N- patients with LACC. CLINICAL RELEVANCE STATEMENT: The degree of MRI parametrial invasion affects disease-free survival and cancer-specific survival in patients with the International Federation of Gynecology and Obstetrics (FIGO) stage IIB cervical cancer. This MRI finding can be easily incorporated into routine clinical practice. KEY POINTS: • Visual assessment of parametrial invasion on MRI was not significantly associated with prognosis in locally advanced cervical cancer (LACC). • A greater degree of parametrial invasion is associated with poorer disease-free survival and cancer-specific survival in patients with LACC without metastatic lymph node involvement. • The degree of parametrial invasion at MRI has no correlation with prognosis in LACC with metastatic lymph nodes.

Attitudes and perceptions of radiologists towards online (virtual) oncologic multidisciplinary team meetings during the COVID-19 pandemic-a survey of the European Society of Oncologic Imaging (ESOI).

OBJECTIVES: To explore radiologists' opinions regarding the shift from in-person oncologic multidisciplinary team meetings (MDTMs) to online MDTMs. To assess the perceived impact of online MDTMs, and to evaluate clinical and technical aspects of online meetings. METHODS: An online questionnaire including 24 questions was e-mailed to all European Society of Oncologic Imaging (ESOI) members. Questions targeted the structure and efficacy of online MDTMs, including benefits and limitations. RESULTS: A total of 204 radiologists responded to the survey. Responses were evaluated using descriptive statistical analysis. The majority (157/204; 77%) reported a shift to online MDTMs at the start of the pandemic. For the most part, this transition had a positive effect on maintaining and improving attendance. The majority of participants reported that online MDTMs provide the same clinical standard as in-person meetings, and that interdisciplinary discussion and review of imaging data were not hindered. Seventy three of 204 (35.8%) participants favour reverting to in-person MDTs, once safe to do so, while 7/204 (3.4%) prefer a continuation of online MDTMs. The majority (124/204, 60.8%) prefer a combination of physical and online MDTMs. CONCLUSIONS: Online MDTMs are a viable alternative to in-person meetings enabling continued timely high-quality provision of care with maintained coordination between specialties. They were accepted by the majority of surveyed radiologists who also favoured their continuation after the pandemic, preferably in combination with in-person meetings. An awareness of communication issues particular to online meetings is important. Training, improved software, and availability of support are essential to overcome technical and IT difficulties reported by participants. KEY POINTS: • Majority of surveyed radiologists reported shift from in-person to online oncologic MDT meetings during the COVID-19 pandemic. • The shift to online MDTMs was feasible and generally accepted by the radiologists surveyed with the majority reporting that online MDTMs provide the same clinical standard as in-person meetings. • Most would favour the return to in-person MDTMs but would also accept the continued use of online MDTMs following the end of the current pandemic.

Radiomics systematic review in cervical cancer: gynecological oncologists' perspective.

OBJECTIVE: Radiomics is the process of extracting quantitative features from radiological images, and represents a relatively new field in gynecological cancers. Cervical cancer has been the most studied gynecological tumor for what concerns radiomics analysis. The aim of this study was to report on the clinical applications of radiomics combined and/or compared with clinical-pathological variables in patients with cervical cancer. METHODS: A systematic review of the literature from inception to February 2023 was performed, including studies on cervical cancer analysing a predictive/prognostic radiomics model, which was combined and/or compared with a radiological or a clinical-pathological model. RESULTS: A total of 57 of 334 (17.1%) screened studies met inclusion criteria. The majority of studies used magnetic resonance imaging (MRI), but positron emission tomography (PET)/computed tomography (CT) scan, CT scan, and ultrasound scan also underwent radiomics analysis. In apparent early-stage disease, the majority of studies (16/27, 59.3%) analysed the role of radiomics signature in predicting lymph node metastasis; six (22.2%) investigated the prediction of radiomics to detect lymphovascular space involvement, one (3.7%) investigated depth of stromal infiltration, and one investigated (3.7%) parametrial infiltration. Survival prediction was evaluated both in early-stage and locally advanced settings. No study focused on the application of radiomics in metastatic or recurrent disease. CONCLUSION: Radiomics signatures were predictive of pathological and oncological outcomes, particularly if combined with clinical variables. These may be integrated in a model using different clinical-pathological and translational characteristics, with the aim to tailor and personalize the treatment of each patient with cervical cancer.

Application of multi-spectral CT imaging in Crohn's disease: a systematic review.

BACKGROUND: No quantitative computed tomography (CT) biomarker is actually sufficiently accurate to assess Crohn's disease (CD) lesion activity, with adequate precision to guide clinical decisions. PURPOSE: To assess the available literature on the use of iodine concentration (IC), from multi-spectral CT acquisition, as a quantitative parameter able to distinguish healthy from affected bowel and assess CD bowel activity and heterogeneity of activity along the involved segments. MATERIAL AND METHODS: A literature search was conducted to identify original research studies published up to February 2022. The inclusion criteria were original research papers (>10 human participants), English language publications, focus on dual-energy CT (DECT) of CD with iodine quantification (IQ) as an outcome measure. The exclusion criteria were animal-only studies, languages other than English, review articles, case reports, correspondence, and study populations <10 patients. RESULTS: Nine studies were included in this review; all of which showed a strong correlation between IC measurements and CD activity markers, such as CD activity index (CDAI), endoscopy findings and simple endoscopic score for Crohn's disease (SES-CD), and routine CT enterography (CTE) signs and histopathologic score. Statistically significant differences in IC were reported between affected bowel segments and healthy ones (higher P value was P < 0.001), normal segments and those with active inflammation (P < 0.0001) as well as between patients with active disease and those in remission (P < 0.001). CONCLUSION: The mean normalized IC at DECTE could be a reliable tool in assisting radiologists in the diagnosis, classification and grading of CD activity.

Imaging breast cancer using hyperpolarized carbon-13 MRI.

Our purpose is to investigate the feasibility of imaging tumor metabolism in breast cancer patients using 13C magnetic resonance spectroscopic imaging (MRSI) of hyperpolarized 13C label exchange between injected [1-13C]pyruvate and the endogenous tumor lactate pool. Treatment-naïve breast cancer patients were recruited: four triple-negative grade 3 cancers; two invasive ductal carcinomas that were estrogen and progesterone receptor-positive (ER/PR+) and HER2/neu-negative (HER2-), one grade 2 and one grade 3; and one grade 2 ER/PR+ HER2- invasive lobular carcinoma (ILC). Dynamic 13C MRSI was performed following injection of hyperpolarized [1-13C]pyruvate. Expression of lactate dehydrogenase A (LDHA), which catalyzes 13C label exchange between pyruvate and lactate, hypoxia-inducible factor-1 (HIF1α), and the monocarboxylate transporters MCT1 and MCT4 were quantified using immunohistochemistry and RNA sequencing. We have demonstrated the feasibility and safety of hyperpolarized 13C MRI in early breast cancer. Both intertumoral and intratumoral heterogeneity of the hyperpolarized pyruvate and lactate signals were observed. The lactate-to-pyruvate signal ratio (LAC/PYR) ranged from 0.021 to 0.473 across the tumor subtypes (mean ± SD: 0.145 ± 0.164), and a lactate signal was observed in all of the grade 3 tumors. The LAC/PYR was significantly correlated with tumor volume (R = 0.903, P = 0.005) and MCT 1 (R = 0.85, P = 0.032) and HIF1α expression (R = 0.83, P = 0.043). Imaging of hyperpolarized [1-13C]pyruvate metabolism in breast cancer is feasible and demonstrated significant intertumoral and intratumoral metabolic heterogeneity, where lactate labeling correlated with MCT1 expression and hypoxia.

Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation.

The Dice similarity coefficient (DSC) is both a widely used metric and loss function for biomedical image segmentation due to its robustness to class imbalance. However, it is well known that the DSC loss is poorly calibrated, resulting in overconfident predictions that cannot be usefully interpreted in biomedical and clinical practice. Performance is often the only metric used to evaluate segmentations produced by deep neural networks, and calibration is often neglected. However, calibration is important for translation into biomedical and clinical practice, providing crucial contextual information to model predictions for interpretation by scientists and clinicians. In this study, we provide a simple yet effective extension of the DSC loss, named the DSC++ loss, that selectively modulates the penalty associated with overconfident, incorrect predictions. As a standalone loss function, the DSC++ loss achieves significantly improved calibration over the conventional DSC loss across six well-validated open-source biomedical imaging datasets, including both 2D binary and 3D multi-class segmentation tasks. Similarly, we observe significantly improved calibration when integrating the DSC++ loss into four DSC-based loss functions. Finally, we use softmax thresholding to illustrate that well calibrated outputs enable tailoring of recall-precision bias, which is an important post-processing technique to adapt the model predictions to suit the biomedical or clinical task. The DSC++ loss overcomes the major limitation of the DSC loss, providing a suitable loss function for training deep learning segmentation models for use in biomedical and clinical practice. Source code is available at https://github.com/mlyg/DicePlusPlus .

Interventional Oncology and Immuno-Oncology: Current Challenges and Future Trends.

Personalized cancer treatments help to deliver tailored and biologically driven therapies for cancer patients. Interventional oncology techniques are able to treat malignancies in a locoregional fashion, with a variety of mechanisms of action leading to tumor necrosis. Tumor destruction determines a great availability of tumor antigens that can be recognized by the immune system, potentially triggering an immune response. The advent of immunotherapy in cancer care, with the introduction of specific immune checkpoint inhibitors, has led to the investigation of the synergy of these drugs when used in combination with interventional oncology treatments. The aim of this paper is to review the most recent advances in the field of interventional oncology locoregional treatments and their interactions with immunotherapy.

Local Extent of Prostate Cancer at MRI versus Prostatectomy Histopathology: Associations with Long-term Oncologic Outcomes.

Background It is unknown how the imperfect accuracy of MRI for local staging of prostate cancer relates to oncologic outcomes. Purpose To analyze how staging discordances between MRI and histopathologic evaluation relate to recurrence and survival after radical prostatectomy. Materials and Methods Health Insurance Portability and Accountability Act-compliant retrospective analysis of preprostatectomy T2-weighted prostate MRI (January 2001 to December 2006). Extraprostatic extension and seminal vesicle invasion were assessed by using five-point Likert scales; scores of 4 or higher were classified as positive. Biochemical recurrence (BCR), metastases, and prostate cancer-specific mortality rates were estimated with Kaplan-Meier and Cox models. Results A total of 2160 patients (median age, 60 years; interquartile range, 55-64 years) were evaluated. Among patients with histopathologic extraprostatic (pT3) disease (683 of 2160; 32%), those with organ-confined disease at MRI (384 of 683; 56%) experienced better outcomes than those with concordant extraprostatic disease at MRI and pathologic analysis: 15-year risk for BCR, 30% (95% CI: 22, 40) versus 68% (95% CI: 60, 75); risk for metastases, 14% (95% CI: 8.4, 24) versus 32% (95% CI: 26, 39); risk for prostate cancer-specific mortality, 3% (95% CI: 1, 6) versus 15% (95% CI: 9.5, 23) (P < .001 for all comparisons). Among patients with histopathologic organ-confined disease (pT2) (1477 of 2160; 68%), those with extraprostatic disease at MRI (102 of 1477; 7%) were at higher risk for BCR (27% [95% CI: 19, 37] vs 10% [95% CI: 8, 14]; P < .001), metastases (19% [95% CI: 6, 48] vs 3% [95% CI: 1, 6]; P < .001), and prostate cancer-specific mortality (2% [95% CI: 1, 9] vs 1% [95% CI: 0, 5]; P = .009) than those with concordant organ-confined disease at MRI and pathologic analysis. At multivariable analyses, tumor extent at MRI (hazard ratio range, 4.1-5.2) and histopathologic evaluation (hazard ratio range, 3.6-6.7) was associated with the risk for BCR, metastases, and prostate cancer-specific mortality (P < .001 for all analyses). Conclusion The local extent of prostate cancer at MRI is associated with oncologic outcomes after prostatectomy, independent of pathologic tumor stage. This might inform a strategy on how to integrate MRI into a clinical staging algorithm. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Gottlieb in this issue.

Comparative performance of MRI-derived PRECISE scores and delta-radiomics models for the prediction of prostate cancer progression in patients on active surveillance.

OBJECTIVES: To compare the performance of the PRECISE scoring system against several MRI-derived delta-radiomics models for predicting histopathological prostate cancer (PCa) progression in patients on active surveillance (AS). METHODS: The study included AS patients with biopsy-proven PCa with a minimum follow-up of 2 years and at least one repeat targeted biopsy. Histopathological progression was defined as grade group progression from diagnostic biopsy. The control group included patients with both radiologically and histopathologically stable disease. PRECISE scores were applied prospectively by four uro-radiologists with 5-16 years' experience. T2WI- and ADC-derived delta-radiomics features were computed using baseline and latest available MRI scans, with the predictive modelling performed using the parenclitic networks (PN), least absolute shrinkage and selection operator (LASSO) logistic regression, and random forests (RF) algorithms. Standard measures of discrimination and areas under the ROC curve (AUCs) were calculated, with AUCs compared using DeLong's test. RESULTS: The study included 64 patients (27 progressors and 37 non-progressors) with a median follow-up of 46 months. PRECISE scores had the highest specificity (94.7%) and positive predictive value (90.9%), whilst RF had the highest sensitivity (92.6%) and negative predictive value (92.6%) for predicting disease progression. The AUC for PRECISE (84.4%) was non-significantly higher than AUCs of 81.5%, 78.0%, and 80.9% for PN, LASSO regression, and RF, respectively (p = 0.64, 0.43, and 0.57, respectively). No significant differences were observed between AUCs of the three delta-radiomics models (p-value range 0.34-0.77). CONCLUSIONS: PRECISE and delta-radiomics models achieved comparably good performance for predicting PCa progression in AS patients. KEY POINTS: • The observed high specificity and PPV of PRECISE are complemented by the high sensitivity and NPV of delta-radiomics, suggesting a possible synergy between the two image assessment approaches. • The comparable performance of delta-radiomics to PRECISE scores applied by expert readers highlights the prospective use of the former as an objective and standardisable quantitative tool for MRI-guided AS follow-up. • The marginally superior performance of parenclitic networks compared to conventional machine learning algorithms warrants its further use in radiomics research.

Ovarian cancer reporting lexicon for computed tomography (CT) and magnetic resonance (MR) imaging developed by the SAR Uterine and Ovarian Cancer Disease-Focused Panel and the ESUR Female Pelvic Imaging Working Group.

OBJECTIVES: Imaging evaluation is an essential part of treatment planning for patients with ovarian cancer. Variation in the terminology used for describing ovarian cancer on computed tomography (CT) and magnetic resonance (MR) imaging can lead to ambiguity and inconsistency in clinical radiology reports. The aim of this collaborative project between Society of Abdominal Radiology (SAR) Uterine and Ovarian Cancer (UOC) Disease-focused Panel (DFP) and the European Society of Uroradiology (ESUR) Female Pelvic Imaging (FPI) Working Group was to develop an ovarian cancer reporting lexicon for CT and MR imaging. METHODS: Twenty-one members of the SAR UOC DFP and ESUR FPI working group, one radiology clinical fellow, and two gynecologic oncology surgeons formed the Ovarian Cancer Reporting Lexicon Committee. Two attending radiologist members of the committee prepared a preliminary list of imaging terms that was sent as an online survey to 173 radiologists and gynecologic oncologic physicians, of whom 67 responded to the survey. The committee reviewed these responses to create a final consensus list of lexicon terms. RESULTS: An ovarian cancer reporting lexicon was created for CT and MR Imaging. This consensus-based lexicon has 6 major categories of terms: general, adnexal lesion-specific, peritoneal carcinomatosis-specific, lymph node-specific, metastatic disease -specific, and fluid-specific. CONCLUSIONS: This lexicon for CT and MR imaging evaluation of ovarian cancer patients has the capacity to improve the clarity and consistency of reporting disease sites seen on imaging. KEY POINTS: • This reporting lexicon for CT and MR imaging provides a list of consensus-based, standardized terms and definitions for reporting sites of ovarian cancer on imaging at initial diagnosis or follow-up. • Use of standardized terms and morphologic imaging descriptors can help improve interdisciplinary communication of disease extent and facilitate optimal patient management. • The radiologists should identify and communicate areas of disease, including difficult to resect or potentially unresectable disease that may limit the ability to achieve optimal resection.