Repotrectinib's Clinical Benefit and Its Brain Penetration in a Patient with Meningeal Carcinomatosis from G2032R-Mutated ROS-1 Positive Non-Small Cell Lung Cancer.

In this work, we report on a clinically significant response of meningeal carcinomatosis to repotrectinib in a woman with a heavily pretreated ROS1-rearranged non-small cell lung cancer (NSCLC) that harbored the concomitant solvent front G2032R mutation. Meningeal carcinomatosis has a higher incidence in oncogene addicted NSCLC due to increased life expectancy, yet no report has ever documented the activity of repotrectinib in this context. In line with its activity, we documented the presence of the drug at potentially active concentrations in the cerebrospinal fluid. Nevertheless, the short-lived response reported by our patient highlights the importance for novel ROS1-tyrosine kinase inhibitors (TKIs) to be specifically developed to be able to penetrate the blood-brain barrier.

Performance Analysis of Six Semi-Automated Tumour Delineation Methods on [18F] Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG PET/CT) in Patients with Head and Neck Cancer.

Background. Head and neck cancer (HNC) is the seventh most common neoplastic disorder at the global level. Contouring HNC lesions on [18F] Fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) scans plays a fundamental role for diagnosis, risk assessment, radiotherapy planning and post-treatment evaluation. However, manual contouring is a lengthy and tedious procedure which requires significant effort from the clinician. Methods. We evaluated the performance of six hand-crafted, training-free methods (four threshold-based, two algorithm-based) for the semi-automated delineation of HNC lesions on FDG PET/CT. This study was carried out on a single-centre population of n=103 subjects, and the standard of reference was manual segmentation generated by nuclear medicine specialists. Figures of merit were the Sørensen-Dice coefficient (DSC) and relative volume difference (RVD). Results. Median DSC ranged between 0.595 and 0.792, median RVD between -22.0% and 87.4%. Click and draw and Nestle's methods achieved the best segmentation accuracy (median DSC, respectively, 0.792 ± 0.178 and 0.762 ± 0.107; median RVD, respectively, -21.6% ± 1270.8% and -32.7% ± 40.0%) and outperformed the other methods by a significant margin. Nestle's method also resulted in a lower dispersion of the data, hence showing stronger inter-patient stability. The accuracy of the two best methods was in agreement with the most recent state-of-the art results. Conclusions. Semi-automated PET delineation methods show potential to assist clinicians in the segmentation of HNC lesions on FDG PET/CT images, although manual refinement may sometimes be needed to obtain clinically acceptable ROIs.

PET Radiomics and Response to Immunotherapy in Lung Cancer: A Systematic Review of the Literature.

The aim of this review is to provide a comprehensive overview of the existing literature concerning the applications of positron emission tomography (PET) radiomics in lung cancer patient candidates or those undergoing immunotherapy. MATERIALS AND METHODS: A systematic review was conducted on databases and web sources. English-language original articles were considered. The title and abstract were independently reviewed to evaluate study inclusion. Duplicate, out-of-topic, and review papers, or editorials, articles, and letters to editors were excluded. For each study, the radiomics analysis was assessed based on the radiomics quality score (RQS 2.0). The review was registered on the PROSPERO database with the number CRD42023402302. RESULTS: Fifteen papers were included, thirteen were qualified as using conventional radiomics approaches, and two used deep learning radiomics. The content of each study was different; indeed, seven papers investigated the potential ability of radiomics to predict PD-L1 expression and tumor microenvironment before starting immunotherapy. Moreover, two evaluated the prediction of response, and four investigated the utility of radiomics to predict the response to immunotherapy. Finally, two papers investigated the prediction of adverse events due to immunotherapy. CONCLUSIONS: Radiomics is promising for the evaluation of TME and for the prediction of response to immunotherapy, but some limitations should be overcome.

Size measurement of lung nodules on CT: which diameter is most stable to inter-observer variability?

Indeterminate lung nodules detected on CT are common findings in the clinical practice, and the correct assessment of their size is critical for patient evaluation and management. We compared the stability of three definitions of nodule diameter (Feret's mean diameter, Martin's mean diameter and area-equivalent diameter) to inter-observer variability on a population of 336 solid nodules from 207 subjects. We found that inter-observer agreement was highest with Martin's mean diameter (intra-class correlation coefficient = 0.977, 95% Confidence interval = 0.977-0.978), followed by area-equivalent diameter (0.972, 0.971-0.973) and Feret's mean diameter (0.965, 0.964-0.966). The differences were statistically significant. In conclusion, although all the three diameter definitions achieved very good inter-observer agreement (ICC > 0.96), Martin's mean diameter was significantly better than the others. Future guidelines may consider adopting Martin's mean diameter as an alternative to the currently used Feret's (caliper) diameter for assessing the size of lung nodules on CT.

Radiomics and theranostics with molecular and metabolic probes in prostate cancer: toward a personalized approach.

INTRODUCTION: In the last decade, two new radionuclide-based therapies, 223Radichloride and radioligand therapy (RLT) targeting prostate-specific membrane antigen (PSMA), have been approved by the regulatory authorities for the management of castrate-resistant prostate cancer (PCa). AREAS COVERED: The basic principles of PCa molecular imaging are illustrated, with a particular attention to the combined use of diagnosis and therapy in a unique approach (the so-called theranostics) for response prediction and assessment in patients submitted to 223Radichloride or PSMA targeted therapies. In this perspective, the potential of radiomics, an emerging discipline based on the extraction of quantitative features from medical images, is covered. EXPERT OPINION: Theranostic metabolic and molecular probes have been successfully applied to predict and monitor response to radionuclide-based therapies. In particular, both 99mTc-MDP and 18F-NaF resulted useful tools for personalized dosimetry and prognostic stratification before 223Ra-therapy, while PSMA-ligands, alone or in combination with 18F-FDG, provided valuable information to select patients who are more likely to benefit from RLT and getting information on PCa grade of differentiation and aggressiveness. In spite of its high potential, PET-radiomics for PCa is still at an embryonic phase and needs further validation.

Prostate-specific membrane antigen-directed imaging and radioguided surgery with single-photon emission computed tomography: state of the art and future outlook.

INTRODUCTION: Prostate-specific membrane antigen (PSMA) has emerged as a highly relevant target for prostate cancer (PC) diagnosis and therapy. PSMA inhibitors targeting PSMA-enzymatic domain have been successfully labeled with radionuclides emitting positrons or gamma-photons, thus obtaining tracers suitable for imaging with positron emission computed tomography (PET/CT) or single-photon emission tomography (SPECT). AREAS COVERED: The different approaches for obtaining PSMA-ligands labeled with gamma-emitting nuclides (99mTc or111In) are reviewed. Furthermore, the applications of 99mTc/111In-PSMA SPECT for the imaging of PC patients in different clinical settings (staging or biochemical recurrence) are covered. Lastly, the employment of PSMA-targeted SPECT tracers for radioguided surgery (RGS) during primary or salvage lymphadenectomy is discussed. EXPERT OPINION: RGS provided satisfying preliminary results in both primary and salvage lymphadenectomy, allowing to discriminate between pathological and non-pathological nodes with high accuracy, although prospective studies with larger cohorts are needed to further validate this surgical approach. The potential of PSMA-targeted SPECT/CT has not been fully explored yet, but it might represent a relatively cost-effective alternative to PSMA PET/CT in limited resource environments. In this perspective, the implementation of novel SPECT technologies or algorithms, such as semiconductor-ionization detectors or resolution recovery reconstruction, will be topic of future investigation.

Imaging Findings of 18F-Choline and 18F-DOPA PET/MRI in a Case of Glioblastoma Multiforme Pseudoprogression: Correlation with Clinical Outcome.

We describe the case of 74-year-old-male, previously treated with fronto-parietal craniotomy due to primary glioblastoma multiforme (GBM), followed by concurrent radiation therapy (RT) and temozolomide (TMZ) chemotherapy. Magnetic resonance imaging (MRI) of the brain, at 1 month after completing RT + TMZ, depicted partial response. Three months later, the patient was submitted to a further brain MRI, that resulted doubtful for therapy induced changes (i.e., pseudoprogression). The patient, who had been previously treated with prostatectomy for prostate cancer (PC), underwent a positron emission tomography/computed tomography (PET/CT) scan with 18F-choline for PC biochemical recurrence. 18F-choline whole body PET/CT resulted negative for PC relapse, while segmental brain PET, co-registered with MRI, demonstrated increased tracer uptake corresponding to tumor boundaries. In order to solve differential diagnosis between pseudoprogression and GBM recurrence, brain PET/CT with 18F-L-dihydroxy-phenil-alanine (18F-DOPA) was subsequently performed: fused axial PET/MRI images showed increased 18F-DOPA incorporation in the peri-tumoral edema, but not in tumor boundaries, consistent with the suspicion of GBM pseudoprogression, as then confirmed by clinical and radiological follow-up.

Somatostatin Receptor Targeted PET-Imaging for Diagnosis, Radiotherapy Planning and Theranostics of Meningiomas: A Systematic Review of the Literature.

The aims of the present systematic review are to: (1) assess the diagnostic performance of somatostatin receptor (SSR)targeted positron emission tomography (PET) with different tracers and devices in patients affected by meningiomas; and (2) to evaluate the theranostic applications of peptide receptor radionuclide therapy (PRRT) in meningiomas. A systematic literature search according to PRISMA criteria was made by using two main databases. Only studies published from 2011 up to March 2022 in the English language with ≥10 enrolled patients were selected. Following our research strategy, 17 studies were included for the assessment. Fourteen studies encompassed 534 patients, harboring 733 meningiomas, submitted to SSR-targeted PET/CT (n = 10) or PET/MRI (n = 4) for de novo diagnosis, recurrence detection, or radiation therapy (RT) planning (endpoint 1), while 3 studies included 69 patients with therapy-refractory meningiomas submitted to PRRT (endpoint 2). A relevant variation in methodology was registered among diagnostic studies, since only a minority of them reported histopathology as a reference standard. PET, especially when performed through PET/MRI, resulted particularly useful for the detection of meningiomas located in the skull base (SB) or next to the falx cerebri, significantly influencing RT planning. As far as it concerns PRRT studies, stable disease was obtained in the 66.6% of the treated patients, being grade 1-2 hematological toxicity the most common side effect. Of note, the wide range of the administered activities, the various utilized radiopharmaceuticals (90Y-DOTATOC and/or 177Lu-DOTATATE), the lack of dosimetric studies hamper a clear definition of PRRT potential on meningiomas' management.

Form Factors as Potential Imaging Biomarkers to Differentiate Benign vs. Malignant Lung Lesions on CT Scans.

Indeterminate lung nodules detected on CT scans are common findings in clinical practice. Their correct assessment is critical, as early diagnosis of malignancy is crucial to maximise the treatment outcome. In this work, we evaluated the role of form factors as imaging biomarkers to differentiate benign vs. malignant lung lesions on CT scans. We tested a total of three conventional imaging features, six form factors, and two shape features for significant differences between benign and malignant lung lesions on CT scans. The study population consisted of 192 lung nodules from two independent datasets, containing 109 (38 benign, 71 malignant) and 83 (42 benign, 41 malignant) lung lesions, respectively. The standard of reference was either histological evaluation or stability on radiological followup. The statistical significance was determined via the Mann-Whitney U nonparametric test, and the ability of the form factors to discriminate a benign vs. a malignant lesion was assessed through multivariate prediction models based on Support Vector Machines. The univariate analysis returned four form factors (Angelidakis compactness and flatness, Kong flatness, and maximum projection sphericity) that were significantly different between the benign and malignant group in both datasets. In particular, we found that the benign lesions were on average flatter than the malignant ones; conversely, the malignant ones were on average more compact (isotropic) than the benign ones. The multivariate prediction models showed that adding form factors to conventional imaging features improved the prediction accuracy by up to 14.5 pp. We conclude that form factors evaluated on lung nodules on CT scans can improve the differential diagnosis between benign and malignant lesions.

The Role and Potential of 18F-FDG PET/CT in Malignant Melanoma: Prognostication, Monitoring Response to Targeted and Immunotherapy, and Radiomics.

Novel therapeutic approaches, consisting of immune check-point inhibitors (ICIs) and molecularly targeted therapy, have thoroughly changed the clinical management of malignant melanoma (MM), the most frequent and deadly skin cancer. Since only 30-40% of MM patients respond to ICIs, imaging biomarkers suitable for the pre-therapeutic stratification and response assessment are warmly welcome. In this scenario, positron emission computed tomography (PET/CT) with 18F-fluorodeoxyglucose (18F-FDG) has been successfully utilized for advanced MM staging and therapy response evaluation. Furthermore, several PET-derived parameters (SUVmax, MTV, TLG) were particularly impactful for the prognostic evaluation of patients submitted to targeted and immunotherapy. In this review, we performed a web-based and desktop research on the clinical applications of 18F-FDG PET/CT in MM, with a particular emphasis on the various metabolic criteria developed for interpreting PET/CT scan in patients undergoing immunotherapy or targeted therapy or a combination of both. Furthermore, the emerging role of radiomics, a quantitative approach to medical imaging applying analysis methodology derived by the field of artificial intelligence, was examined in the peculiar context, putting a particular emphasis on the potential of this discipline to support clinicians in the delicate process of building patient-tailored pathways of care.

DNA Damage Repair Defects and Targeted Radionuclide Therapies for Prostate Cancer: Does Mutation Really Matter? A Systematic Review.

The aim of the present review was to assess the impact of DNA damage repair (DDR) mutations on response and outcome of patients (pts) affected by advanced prostate cancer (PCa) submitted to radionuclide therapies with [223Ra]RaCl2 (223Ra-therapy) or prostate specific membrane antigen (PSMA) ligands. A systematic literature search according to PRISMA criteria was made by using two main databases. Only studies published up until to October 2022 in the English language with ≥10 enrolled patients were selected. Seven studies including 326 pts, of whom 201 (61.6%) harboring DDR defects, were selected. The majority of selected papers were retrospective and four out of seven (57.1%) had small sample size (<50 pts). Three out of seven (42.8%) studies reported a more favorable outcome (overall or progression free survival) after therapy with alpha emitters (223Ra-therapy or [225Ac]Ac-PSMA-617) in subjects with DDR defects with respect to those without mutations. In two studies employing alpha or beta emitters ([177Lu]/[225Ac]-PMSA), no significant benefit was registered in pts harboring DDR defects. In all but one paper, no significant difference in response rate was reported among pts with or without DDR mutations. Although preliminary and biased by the retrospective design, preliminary data suggest a trend towards a longer survival in PCa pts harboring DDR defects submitted to radionuclide targeted therapy with alpha emitters.

Impact of Lesion Delineation and Intensity Quantisation on the Stability of Texture Features from Lung Nodules on CT: A Reproducible Study.

Computer-assisted analysis of three-dimensional imaging data (radiomics) has received a lot of research attention as a possible means to improve the management of patients with lung cancer. Building robust predictive models for clinical decision making requires the imaging features to be stable enough to changes in the acquisition and extraction settings. Experimenting on 517 lung lesions from a cohort of 207 patients, we assessed the stability of 88 texture features from the following classes: first-order (13 features), Grey-level Co-Occurrence Matrix (24), Grey-level Difference Matrix (14), Grey-level Run-length Matrix (16), Grey-level Size Zone Matrix (16) and Neighbouring Grey-tone Difference Matrix (five). The analysis was based on a public dataset of lung nodules and open-access routines for feature extraction, which makes the study fully reproducible. Our results identified 30 features that had good or excellent stability relative to lesion delineation, 28 to intensity quantisation and 18 to both. We conclude that selecting the right set of imaging features is critical for building clinical predictive models, particularly when changes in lesion delineation and/or intensity quantisation are involved.

Comparative evaluation of conventional and deep learning methods for semi-automated segmentation of pulmonary nodules on CT.

BACKGROUND: Accurate segmentation of pulmonary nodules on computed tomography (CT) scans plays a crucial role in the evaluation and management of patients with suspicion of lung cancer (LC). When performed manually, not only the process requires highly skilled operators, but is also tiresome and time-consuming. To assist the physician in this task several automated and semi-automated methods have been proposed in the literature. In recent years, in particular, the appearance of deep learning has brought about major advances in the field. METHODS: Twenty-four (12 conventional and 12 based on deep learning) semi-automated-'one-click'-methods for segmenting pulmonary nodules on CT were evaluated in this study. The experiments were carried out on two datasets: a proprietary one (383 images from a cohort of 111 patients) and a public one (259 images from a cohort of 100). All the patients had a positive transcript for suspect pulmonary nodules. RESULTS: The methods based on deep learning clearly outperformed the conventional ones. The best performance [Sørensen-Dice coefficient (DSC)] in the two datasets was, respectively, 0.853 and 0.763 for the deep learning methods, and 0.761 and 0.704 for the traditional ones. CONCLUSIONS: Deep learning is a viable approach for semi-automated segmentation of pulmonary nodules on CT scans.

Prevalence of interstitial pneumonia suggestive of COVID-19 at 18F-FDG PET/CT in oncological asymptomatic patients in a high prevalence country during pandemic period: a national multi-centric retrospective study.

PURPOSE: To assess the presence and pattern of incidental interstitial lung alterations suspicious of COVID-19 on fluorine-18-fluorodeoxyglucose positron emission tomography (PET)/computed tomography (CT) ([18F]FDG PET/CT) in asymptomatic oncological patients during the period of active COVID-19 in a country with high prevalence of the virus. METHODS: This is a multi-center retrospective observational study involving 59 Italian centers. We retrospectively reviewed the prevalence of interstitial pneumonia detected during the COVID period (between March 16 and 27, 2020) and compared to a pre-COVID period (January-February 2020) and a control time (in 2019). The diagnosis of interstitial pneumonia was done considering lung alterations of CT of PET. RESULTS: Overall, [18F]FDG PET/CT was performed on 4008 patients in the COVID period, 19,267 in the pre-COVID period, and 5513 in the control period. The rate of interstitial pneumonia suspicious for COVID-19 was significantly higher during the COVID period (7.1%) compared with that found in the pre-COVID (5.35%) and control periods (5.15%) (p < 0.001). Instead, no significant difference among pre-COVID and control periods was present. The prevalence of interstitial pneumonia detected at PET/CT was directly associated with geographic virus diffusion, with the higher rate in Northern Italy. Among 284 interstitial pneumonia detected during COVID period, 169 (59%) were FDG-avid (average SUVmax of 4.1). CONCLUSIONS: A significant increase of interstitial pneumonia incidentally detected with [18F]FDG PET/CT has been demonstrated during the COVID-19 pandemic. A majority of interstitial pneumonia were FDG-avid. Our results underlined the importance of paying attention to incidental CT findings of pneumonia detected at PET/CT, and these reports might help to recognize early COVID-19 cases guiding the subsequent management.

Value of Shape and Texture Features from 18F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental Evaluation.

In this paper, we investigate the role of shape and texture features from 18F-FDG PET/CT to discriminate between benign and malignant solitary pulmonary nodules. To this end, we retrospectively evaluated cross-sectional data from 111 patients (64 males, 47 females, age = 67.5 ± 11.0) all with histologically confirmed benign (n=39) or malignant (n=72) solitary pulmonary nodules. Eighteen three-dimensional imaging features, including conventional, texture, and shape features from PET and CT were tested for significant differences (Wilcoxon-Mann-Withney) between the benign and malignant groups. Prediction models based on different feature sets and three classification strategies (Classification Tree, k-Nearest Neighbours, and Naïve Bayes) were also evaluated to assess the potential benefit of shape and texture features compared with conventional imaging features alone. Eight features from CT and 15 from PET were significantly different between the benign and malignant groups. Adding shape and texture features increased the performance of both the CT-based and PET-based prediction models with overall accuracy gain being 3.4-11.2 pp and 2.2-10.2 pp, respectively. In conclusion, we found that shape and texture features from 18F-FDG PET/CT can lead to a better discrimination between benign and malignant lung nodules by increasing the accuracy of the prediction models by an appreciable margin.

Classification Model to Estimate MIB-1 (Ki 67) Proliferation Index in NSCLC Patients Evaluated With 18F-FDG-PET/CT.

BACKGROUND/AIM: Proliferation biomarkers such as MIB-1 are strong predictors of clinical outcome and response to therapy in patients with non-small-cell lung cancer, but they require histological examination. In this work, we present a classification model to predict MIB-1 expression based on clinical parameters from positron emission tomography. PATIENTS AND METHODS: We retrospectively evaluated 78 patients with histology-proven non-small-cell lung cancer (NSCLC) who underwent 18F-FDG-PET/CT for clinical examination. We stratified the population into a low and high proliferation group using MIB-1=25% as cut-off value. We built a predictive model based on binary classification trees to estimate the group label from the maximum standardized uptake value (SUVmax) and lesion diameter. RESULTS: The proposed model showed ability to predict the correct proliferation group with overall accuracy >82% (78% and 86% for the low- and high-proliferation group, respectively). CONCLUSION: Our results indicate that radiotracer activity evaluated via SUVmax and lesion diameter are correlated with tumour proliferation index MIB-1.

Texture Analysis on [18F]FDG PET/CT in Non-Small-Cell Lung Cancer: Correlations Between PET Features, CT Features, and Histological Types.

PURPOSE: The study aims to investigate the correlations between positron emission tomography (PET) texture features, X-ray computed tomography (CT) texture features, and histological subtypes in non-small-cell lung cancer evaluated with 2-deoxy-2-[18F]fluoro-D-glucose PET/CT. PROCEDURES: We retrospectively evaluated the baseline PET/CT scans of 81 patients with histologically proven non-small-cell lung cancer. Feature extraction and statistical analysis were carried out on the Matlab platform (MathWorks, Natick, USA). RESULTS: Intra-CT correlation analysis revealed a strong positive correlation between volume of the lesion (CTvol) and maximum density (CTmax), and between kurtosis (CTkrt) and maximum density (CTmax). A moderate positive correlation was found between volume (CTvol) and average density (CTmean), and between kurtosis (CTkrt) and average density (CTmean). Intra-PET analysis identified a strong positive correlation between the radiotracer uptake (SUVmax, SUVmean) and its degree of variability/disorder throughout the lesion (SUVstd, SUVent). Conversely, there was a strong negative correlation between the uptake (SUVmax, SUVmean) and its degree of uniformity (SUVuni). There was a positive moderate correlation between the metabolic tumor volume (MTV) and radiotracer uptake (SUVmax, SUVmean). Inter (PET-CT) correlation analysis identified a very strong positive correlation between the volume of the lesion at CT (CTvol) and the metabolic volume (MTV), a moderate positive correlation between average tissue density (CTmean) and radiotracer uptake (SUVmax, SUVmean), and between kurtosis at CT (CTkrt) and metabolic tumor volume (MTV). Squamous cell carcinomas had larger volume higher uptake, stronger PET variability and lower uniformity than the other subtypes. By contrast, adenocarcinomas exhibited significantly lower uptake, lower variability and higher uniformity than the other subtypes. CONCLUSIONS: Significant associations emerged between PET features, CT features, and histological type in NSCLC. Texture analysis on PET/CT shows potential to differentiate between histological types in patients with non-small-cell lung cancer.