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Radiotheranostics, injectable radiopharmaceuticals with antitumour effects, have seen rapid development over the past decade. Although some formulations are already approved for human use, more radiopharmaceuticals will enter clinical practice in the next 5 years, potentially introducing new therapeutic choices for patients. Despite these advances, several challenges remain, including logistics, supply chain, regulatory issues, and education and training. By highlighting active developments in the field, this Review aims to alert practitioners to the value of radiotheranostics and to outline a roadmap for future development. Multidisciplinary approaches in clinical trial design and therapeutic administration will become essential to the continued progress of this evolving therapeutic approach.

The diagnosis and treatment of patients with cancer requires access to imaging to ensure accurate management decisions and optimal outcomes. Our global assessment of imaging and nuclear medicine resources identified substantial shortages in equipment and workforce, particularly in low-income and middle-income countries (LMICs). A microsimulation model of 11 cancers showed that the scale-up of imaging would avert 3·2% (2·46 million) of all 76·0 million deaths caused by the modelled cancers worldwide between 2020 and 2030, saving 54·92 million life-years. A comprehensive scale-up of imaging, treatment, and care quality would avert 9·55 million (12·5%) of all cancer deaths caused by the modelled cancers worldwide, saving 232·30 million life-years. Scale-up of imaging would cost US$6·84 billion in 2020–30 but yield lifetime productivity gains of $1·23 trillion worldwide, a net return of $179·19 per $1 invested. Combining the scale-up of imaging, treatment, and quality of care would provide a net benefit of $2·66 trillion and a net return of $12·43 per $1 invested. With the use of a conservative approach regarding human capital, the scale-up of imaging alone would provide a net benefit of $209·46 billion and net return of $31·61 per $1 invested. With comprehensive scale-up, the worldwide net benefit using the human capital approach is $340·42 billion and the return per dollar invested is $2·46. These improved health and economic outcomes hold true across all geographical regions. We propose actions and investments that would enhance access to imaging equipment, workforce capacity, digital technology, radiopharmaceuticals, and research and training programmes in LMICs, to produce massive health and economic benefits and reduce the burden of cancer globally.

ObjectivesTo review the diagnostic performance of contemporary imaging modalities for determining local disease extent and nodal metastasis in patients with newly diagnosed cervical cancer.MethodsPubmed and Embase databases were searched for studies published from 2000 to 2019 that used ultrasound (US), CT, MRI, and/or PET for evaluating various aspects of local extent and nodal metastasis in patients with newly diagnosed cervical cancer. Sensitivities and specificities from the studies were meta-analytically pooled using bivariate and hierarchical modeling.ResultsOf 1311 studies identified in the search, 115 studies with 13,999 patients were included. MRI was the most extensively studied modality (MRI, CT, US, and PET were evaluated in 78, 12, 9, and 43 studies, respectively). Pooled sensitivities and specificities of MRI for assessing all aspects of local extent ranged between 0.71–0.88 and 0.86–0.95, respectively. In assessing parametrial invasion (PMI), US demonstrated pooled sensitivity and specificity of 0.67 and 0.94, respectively—performance levels comparable with those found for MRI. MRI, CT, and PET performed comparably for assessing nodal metastasis, with low sensitivity (0.29–0.69) but high specificity (0.88–0.98), even when stratified to anatomical location (pelvic or paraaortic) and level of analysis (per patient vs. per site).ConclusionsMRI is the method of choice for assessing any aspect of local extent, but where not available, US could be of value, particularly for assessing PMI. CT, MRI, and PET all have high specificity but poor sensitivity for the detection of lymph node metastases.Key Points• Magnetic resonance imaging is the method of choice for assessing local extent.• Ultrasound may be helpful in determining parametrial invasion, especially in lower-resourced countries.• Computed tomography, magnetic resonance imaging, and positron emission tomography perform similarly for assessing lymph node metastasis, with high specificity but low sensitivity.

Noninvasive, radiological image-based detection and stratification of Gleason patterns can impact clinical outcomes, treatment selection, and the determination of disease status at diagnosis without subjecting patients to surgical biopsies. We present machine learning-based automatic classification of prostate cancer aggressiveness by combining apparent diffusion coefficient (ADC) and T2-weighted (T2-w) MRI-based texture features. Our approach achieved reasonably accurate classification of Gleason scores (GS) 6(3 + 3) vs. ≥7 and 7(3 + 4) vs. 7(4 + 3) despite the presence of highly unbalanced samples by using two different sample augmentation techniques followed by feature selection-based classification. Our method distinguished between GS 6(3 + 3) and ≥7 cancers with 93% accuracy for cancers occurring in both peripheral (PZ) and transition (TZ) zones and 92% for cancers occurring in the PZ alone. Our approach distinguished the GS 7(3 + 4) from GS 7(4 + 3) with 92% accuracy for cancers occurring in both the PZ and TZ and with 93% for cancers occurring in the PZ alone. In comparison, a classifier using only the ADC mean achieved a top accuracy of 58% for distinguishing GS 6(3 + 3) vs. GS ≥7 for cancers occurring in PZ and TZ and 63% for cancers occurring in PZ alone. The same classifier achieved an accuracy of 59% for distinguishing GS 7(3 + 4) from GS 7(4 + 3) occurring in the PZ and TZ and 60% for cancers occurring in PZ alone. Separate analysis of the cancers occurring in TZ alone was not performed owing to the limited number of samples. Our results suggest that texture features derived from ADC and T2-w MRI together with sample augmentation can help to obtain reasonably accurate classification of Gleason patterns.

In addition to increased availability of treatment modalities, advanced imaging modalities are increasingly recommended to improve global cancer care. However, estimates of the costs and benefits of investments to improve cancer survival are scarce, especially for low-income and middle-income countries (LMICs). In this analysis, we aimed to estimate the costs and lifetime health and economic benefits of scaling up imaging and treatment modality packages on cancer survival, both globally and by country income group. Using a previously developed model of global cancer survival, we estimated stage-specific cancer survival and life-years gained (accounting for competing mortality) in 200 countries and territories for patients diagnosed with one of 11 cancers (oesophagus, stomach, colon, rectum, anus, liver, pancreas, lung, breast, cervix uteri, and prostate) representing 60% of all cancer diagnoses between 2020 and 2030 (inclusive of full years). We evaluated the costs and health and economic benefits of scaling up packages of treatment (chemotherapy, surgery, radiotherapy, and targeted therapy), imaging modalities (ultrasound, x-ray, CT, MRI, PET, single-photon emission CT), and quality of care to the mean level of high-income countries, separately and in combination, compared with no scale-up. Costs and benefits are presented in 2018 US$ and discounted at 3% annually. For the 11 cancers studied, we estimated that without scale-up (ie, with current availability of treatment, imaging, and quality of care) there will be 76·0 million cancer deaths (95% UI 73·9–78·6) globally for patients diagnosed between 2020 and 2030, with more than 70% of these deaths occurring in LMICs. Comprehensive scale-up of treatment, imaging, and quality of care could avert 12·5% (95% UI 9·0–16·3) of these deaths globally, ranging from 2·8% (1·8–4·3) in high-income countries to 38·2% (32·6–44·5) in low-income countries. Globally, we estimate that comprehensive scale-up would cost an additional $232·9 billion (95% UI 85·9–422·0) between 2020 and 2030 (representing a 6·9% increase in cancer treatment costs), but produce $2·9 trillion (1·8–4·0) in lifetime economic benefits, yielding a return of $12·43 (6·47–33·23) per dollar invested. Scaling up treatment and quality of care without imaging would yield a return of $6·15 (2·66–16·71) per dollar invested and avert 7·0% (3·9–10·3) of cancer deaths worldwide. Simultaneous investment in cancer treatment, imaging, and quality of care could yield substantial health and economic benefits, especially in LMICs. These results provide a compelling rationale for the value of investing in the global scale-up of cancer care. Harvard TH Chan School of Public Health and National Cancer Institute.

Women in Focus: Be Inspired was a unique programme held at the 2019 European Congress of Radiology that was structured to address a range of topics related to gender and healthcare, including leadership, mentoring and the generational progression of women in medicine. In most countries, women constitute substantially fewer than half of radiologists in academia or private practice despite frequently accounting for at least half of medical school enrolees. Furthermore, the proportion of women decreases at higher academic ranks and levels of leadership, a phenomenon which has been referred to as a “leaky pipeline”. Gender diversity in the radiologic workplace, including in academic and leadership positions, is important for the present and future success of the field. It is a tool for excellence that helps to optimize patient care and research; moreover, it is essential to overcome the current shortage of radiologists. This article reviews the current state of gender diversity in academic and leadership positions in radiology internationally and explores a wide range of potential reasons for gender disparities, including the lack of role models and mentorship, unconscious bias and generational changes in attitudes about the desirability of leadership positions. Strategies for both individuals and institutions to proactively increase the representation of women in academic and leadership positions are suggested.Key Points• Gender-diverse teams perform better. Thus, gender diversity throughout the radiologic workplace, including in leadership positions, is important for the current and future success of the field.• Though women now make up roughly half of medical students, they remain underrepresented among radiology trainees, faculty and leaders.• Factors leading to the gender gap in academia and leadership positions in Radiology include a lack of role models and mentors, unconscious biases, other societal barriers and generational changes.

Technological innovations in genomics and related fields have facilitated large sequencing efforts, supported new biological discoveries in cancer, and spawned an era of liquid biopsy biomarkers. Despite these advances, precision oncology has practical constraints, partly related to cancer's biological diversity and spatial and temporal complexity. Advanced imaging technologies are being developed to address some of the current limitations in early detection, treatment selection and planning, drug delivery, and therapeutic response, as well as difficulties posed by drug resistance, drug toxicity, disease monitoring, and metastatic evolution. We discuss key areas of advanced imaging for improving cancer outcomes and survival. Finally, we discuss practical challenges to the broader adoption of precision imaging in the clinic and the need for a robust translational infrastructure.

This Editorial Comment refers to the article by Bernard C. et al, Gender gap in articles published in European Radiology and CardioVascular and Interventional Radiology: evolution between 2002 and 2016, European Radiology, doi: 10.1007/s00330-019-06390-7.

Purpose To investigate whether qualitative magnetic resonance (MR) features can distinguish leiomyosarcoma (LMS) from atypical leiomyoma (ALM) and assess the feasibility of texture analysis (TA). Methods This retrospective study included 41 women (ALM = 22, LMS = 19) imaged with MRI prior to surgery. Two readers (R1, R2) evaluated each lesion for qualitative MR features. Associations between MR features and LMS were evaluated with Fisher’s exact test. Accuracy measures were calculated for the four most significant features. TA was performed for 24 patients (ALM = 14, LMS = 10) with uniform imaging following lesion segmentation on axial T2-weighted images. Texture features were pre-selected using Wilcoxon signed-rank test with Bonferroni correction and analyzed with unsupervised clustering to separate LMS from ALM. Results Four qualitative MR features most strongly associated with LMS were nodular borders, haemorrhage, “T2 dark” area(s), and central unenhanced area(s) (p ≤ 0.0001 each feature/reader). The highest sensitivity [1.00 (95%CI:0.82-1.00)/0.95 (95%CI: 0.74-1.00)] and specificity [0.95 (95%CI:0.77-1.00)/1.00 (95%CI:0.85-1.00)] were achieved for R1/R2, respectively, when a lesion had ≥3 of these four features. Sixteen texture features differed significantly between LMS and ALM (p-values: <0.001-0.036). Unsupervised clustering achieved accuracy of 0.75 (sensitivity: 0.70; specificity: 0.79). Conclusions Combination of ≥3 qualitative MR features accurately distinguished LMS from ALM. TA was feasible. Key Points • Four qualitative MR features demonstrated the strongest statistical association with LMS . • Combination of ≥3 these features could accurately differentiate LMS from ALM . • Texture analysis was a feasible semi-automated approach for lesion categorization .

Accurate survival estimates are important for cancer control planning. Although observed survival estimates are unavailable for many countries, where they are available, wide variations are reported. Understanding the impact of specific treatment and imaging modalities can help decision makers to effectively allocate resources to improve cancer survival in their local context. We developed a microsimulation model of stage-specific cancer survival in 200 countries and territories for 11 cancers (oesophagus, stomach, colon, rectum, anus, liver, pancreas, lung, breast, cervix uteri, and prostate) comprising 60% of global diagnosed cancer cases. The model accounts for country-specific availability of treatment (chemotherapy, surgery, radiotherapy, and targeted therapy) and imaging modalities (ultrasound, x-ray, CT, MRI, PET, single-photon emission CT), as well as quality of care. We calibrated the model to reported survival estimates from CONCORD-3 (which reports global trends in cancer survival in 2000–14). We estimated 5-year net survival for diagnosed cancers in each country or territory and estimated potential survival gains from increasing the availability of individual treatment and imaging modalities, and more comprehensive packages of scale-up of these interventions. We report the mean and 95% uncertainty intervals (UIs) for all outcomes, calculated as the 2·5 and 97·5 percentiles of the simulation results. The estimated global 5-year net survival for all 11 cancers combined is 42·6% (95% uncertainty interval 40·3–44·3), with survival in high-income countries being an average of 12 times (range 4–17) higher than that in low-income countries. Expanding availability of surgery or radiotherapy or improving quality of care would yield the largest survival gains in low-income (2·5–3·4 percentage point increase in survival) and lower-middle-income countries (2·4–6·1 percentage point increase), whereas upper-middle-income and high-income countries are more likely to benefit from improved availability of targeted therapy (0·7 percentage point increase for upper-middle income and 0·4 percentage point increase for high income). Investing in medical imaging will also be necessary to achieve substantial survival gains, with traditional modalities estimated to provide the largest gains in low-income settings, while MRI and PET would yield the largest gains in higher-income countries. Simultaneous expansion of treatment, imaging, and quality of care could improve 5-year net survival by more than ten times in low-income countries (3·8% [95% UI 0·5–9·2] to 45·2% [40·2–52·1]) and could more than double 5-year net survival in lower-middle-income countries (20·1% [7·2–31·7] to 47·1% [42·8–50·8]). Scaling up both treatment and imaging availability could yield synergistic survival gains for patients with cancer. Expanding traditional modalities in lower-income settings might be a feasible pathway to improve survival before scaling up more modern technologies. Harvard T H Chan School of Public Health.