Clinical value of 68 Ga-DOTA-SSTR PET/CT in the diagnosis and detection of neuroendocrine tumors of unknown primary origin: a systematic review and meta-analysis

Abstract

Background

The ability of ⁶⁸Ga-DOTA-SSTR to detect the primary sites of neuroendocrine tumors (NETs) remains undetermined, and the clinical benefit of this imaging agent is not clear.

Purpose

To evaluate the diagnostic accuracy of ⁶⁸Ga-DOTA-SSTR for carcinoma unknown primary (CUP) neuroendocrine tumors and to further analyze the detection rate of ⁶⁸Ga-DOTA-SSTR for primary and metastatic sites.

Material and Methods

A comprehensive literature search of PubMed/MEDLINE and ScienceDirect was performed in October 2019 in accordance with the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines. We critically reviewed all studies based on the PICOS criteria. QUADAS-2 was used to evaluate the quality of the methodology of the included studies.

Results

A total of 10 studies (484 patients, mean age = 56.6 ± 4.3 years) were included in the study. The pooled sensitivity and specificity of ⁶⁸Ga-DOTA-SSTR in identifying CUP-NETs were 82% and 55%, respectively. The area under the receiver operating characteristic curve was 69%. Regarding metastasis sites, ⁶⁸Ga-DOTA-SSTR found the most metastases in the liver (57.9%), followed by the lymph nodes (22.8%), bones (12.8%), lung (2.8%), and others (1.7%). The pooled detection rate of ⁶⁸Ga-DOTA-SSTR for CUP-NETs was 61%.

Conclusion

The present study demonstrated the high diagnostic sensitivity of ⁶⁸Ga-DOTA-SSTR for CUP-NETs. ⁶⁸Ga-DOTA-SSTR PET/CT was highly effective in locating the primary and metastatic sites of CUP-NETs.

Keywords

Meta-analysis neuroendocrine tumors carcinoma unknown primary 68Ga-DOTA-somatostatin receptor positron emission tomography computed tomography

Introduction

Carcinoma of unknown primary (CUP) is defined as histologically confirmed metastatic disease without an identifiable primary site after a comprehensive standard diagnostic work-up (1). CUP accounts for 3%–5% of all malignancies and is further divided into the following groups based on histological subtype: adenocarcinoma (80%–85%); squamous cell carcinoma (5%–10%); and neuroendocrine tumors (NETs) (2%–4%) (2). NETs usually present as functional syndromes and/or compressive symptoms or are incidentally discovered when primary or metastatic sites are found by imaging for unrelated symptoms. Neuroendocrine tumors of unknown primary origin (CUP-NETs) are defined as primary tumors with an origin that cannot be determined among metastatic NETs and account for 11%–22% of NETs (3,4). Based on the results of surgical exploration, the primary tumors are most commonly localized in the small bowel (70%), pancreas (3%), appendix (3%), colon or rectum (2%), ovary (1%), or unknown (21%) (5)

Early localization of the primary site is a fundamental prerequisite for changing the patient’s management and prolonging survival (6), especially for patients with well-differentiated NETs (WDNETs; including G1 and G2). Identification of the primary site of advanced WDNETs may change the surgical treatment management plan and be associated with a favorable outcome. However, conventional morphological imaging modalities, including ultrasound, X-ray, computed tomography (CT), and magnetic resonance imaging (MRI), are frequently limited in localizing occult primary lesions, especially pancreatic or small bowel neuroendocrine tumors (7). Routine use of capsule endoscopy and endoscopic ultrasonography is unnecessary, as these modalities will not change the management strategy and will delay treatment for the unknown primary site of NET (8). Currently, the localization of primary tumors relies on a combination diagnosis, including biochemical testing, radiological, endoscopic, and functional imaging and pathological evaluation (9).

¹¹¹In-pentetreotide-somatostatin receptor scintigraphy (SRS) has been used for the initial staging of NETs. However, the sensitivity and specificity of SRS may be unsatisfactory, especially in localizing origins in the midgut. NETs originate from the neural crest and express somatostatin receptors, while fluorodeoxyglucose (FDG) positron emission tomography (PET) has lower diagnostic performance in WDNETs. Recently, somatostatin receptor imaging with PET/CT has been developed, and the most widely used imaging agents are ⁶⁸Ga-DOTATATE, ⁶⁸Ga-DOTANOC, and ⁶⁸Ga-DOTATOC. These tracers have a high affinity for SSTR2 but a varied affinity for other SSTR subtypes (10). However, SSTR2 is the main receptor subtype that is predominantly expressed in NETs (11,12). Directly compared with ^99mTc-HYNIC-octreotide/111In-pentetreotide SPECT, ⁶⁸Ga-DOTA-SSTR exhibits a higher diagnostic performance (13).

Previously published meta-analyses emphasized the diagnostic performance of ¹⁸F-FDG for CUP (14 –16) and ⁶⁸Ga-DOTA-SSTR in patients with NETs (17 –20). These studies have demonstrated the excellent imaging ability of ¹⁸F-FDG for CUP and ⁶⁸Ga-DOTA-SSTR for NETs. Currently, the ability of ⁶⁸Ga-DOTA-SSTR to detect undiagnosed primary sites remain undetermined (8), and the clinical benefit is not clear (21). The present study analyzed the impact of ⁶⁸Ga-DOTA-SSTR on the management of patients with CUP-NETs and further analyzed the frequencies of the most common primary and metastatic sites. The aim of the present study was to quantify the contribution of ⁶⁸Ga-DOTA-SSTR PET/CT in the diagnostic assessment of CUP-NETs and further evaluate the incidence rate of key therapeutic factors (localization of the primary tumor, tumor histology, and metastatic sites), which may provide the theoretical basis for a standard work-up with ⁶⁸Ga-DOTA-SSTR in the localization and diagnosis of CUP-NETs.

Material and Methods

Search strategy

A comprehensive online literature search was performed according to the Preferred Reporting Item for Systematic Review and Meta-analysis (PRISMA) guidelines. The search algorithm was performed in literature databases (PubMed/MEDLINE and ScienceDirect) in October 2019 using the terms “neuroendocrine tumor” in combination with “⁶⁸Ga-DOTA-SSTR PET” to identify relevant published articles, as follows: (neuroendocrine tumor OR neuroendocrine neoplasm) AND (Gallium OR Ga) AND (DOTA OR somatostatin) AND (PET/CT OR PET-CT). The beginning date was January 2010. There were no language restrictions. To expand our search, the references of the retrieved articles were also screened for additional studies.

Selection criteria and quality assessment

We critically reviewed studies on ⁶⁸Ga-DOTA-SSTR for the diagnosis of CUP-NETs focusing on the PICOS criteria, which refers to participants, interventions, comparisons, outcomes, and study designs. The participants had CUP-NETs. The interventions indicated ⁶⁸Ga-DOTA-SSTR imaging. The histological and clinical follow-up data were compared. The outcome was diagnostic performance, including sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). Two authors independently screened the eligible titles and abstracts. Full articles were obtained when the title and abstract indicated potential eligibility. Any disagreements were resolved by discussion between the two authors.

Two independent reviewers evaluated the methodology of the selected studies using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool (22), which is the Cochrane Collaboration’s tool for assessing the risk of bias of randomized controlled trials, and the results were displayed in Review Manager (Version 5.3). The QUADAS-2 tool primarily assesses risk of bias in four domains: patient selection; index test; reference standard; and timing of the reference test. Each paper was scored by the above two evaluators, and any discrepancies were resolved by discussion. The summary figures show the risk of bias and applicability concerns. Publication bias was assessed by Deek’s asymmetry test and is shown as a funnel plot.

Data extraction and statistical analysis

Two reviewers independently assessed the included data. The following information was collected from each included study: author; country; year; study design; patient characteristics (number of patients, sex, mean age); radiopharmaceutical applied for imaging; primary and metastatic sites; histopathology grade of the primary NET; diagnosis based on the gold standard; and mean time of follow-up.

In some studies, some lesions were not identified as the primary tumor, and some studies with ⁶⁸Ga-DOTA-SSTR did not show areas of abnormal tracer uptake. These studies could not obtain false positives (FPs) or true negatives (TNs).

The detection rate in each study was based on the proportions reported in the study or calculated by the number of TP patients detected by PET/CT divided by the total number of patients. Seven studies reported the detection rate on a per-patient basis, and three studies did not report the detection rate. Analyses were performed in R software (version 2.5.3 https://www.r-project.org/). The “metafor” package was used to calculate the detection rate with a log transformation.

All extracted data were recorded in Excel 2013 and the analysis was performed using STATA (v.12.0 SE, College Station, TX, USA). We calculated the pooled diagnostic performance, including sensitivity, specificity, PLR, NLR, and DOR, with corresponding 95% confidence intervals (CIs) using a random effect model (DerSimonian and Laird). Heterogeneity within groups and between subgroups was assessed using the I² statistic. Sources of heterogeneity were further identified by subgroup analyses based on radiopharmaceutical (⁶⁸Ga-DOTATATE, ⁶⁸Ga-DOTATOC, and ⁶⁸Ga-DOTANOC), study design (retrospective and prospective), and country (Europe and America, Asia). A P value <0.05 was considered statistically significant. Publication bias was visually assessed using Deeks’ funnel plot asymmetry test.

Results

Literature search and characteristics of the included studies

A total of 184 references were found, 149 from PubMed/MEDLINE and 35 from Science Direct. After removing 26 duplicated references, 158 references remained. Among them, 26 records were considered reviews; editorials and commentary were excluded. Nine studies were meta-analyses and guidelines. Nineteen studies were case reports. Sixty-five studies were not directly related to the field of interest and 39 full-text articles were assessed for eligibility. Of these studies, three records did not use PET/CT scanners, seven studies had no data on the diagnosis of CUP, five studies were related to animals, and 14 studies did not have sufficient data to calculate the diagnostic performance. Thus, 10 full-text articles were retained for the meta-analysis (23 –32). The details of the selected studies are shown in Fig. 1.

Fig. 1.

Flow algorithm of search for eligible studies.

These 10 studies included 484 patients (252 men, 232 women; mean age = 56.6 ± 4.3 years). All studies used histology and clinical follow-up as the reference standards. Regarding study design, two studies were prospective (24,25) and eight studies were retrospective. In terms of radionuclides, three studies used ⁶⁸Ga-DOTATATE (23,25,29), four studies used ⁶⁸Ga-DOTATOC (24,26,28,32), and three studies used ⁶⁸Ga-DOTANOC (27,30,31). The results are shown in Table 1. The mean follow-up time was 15.1 ± 9.0 months.

Table 1.

The basic characteristic of included studies.

Author	Year	Country	Patients	Study design	M/F	Mean age	Radiopharmaceutical	Dose (MBq)	Golden standard	Mean time interval	Detection rate
Kazmierczak	2017	Germany	38	Retrospective	27/11	62	⁶⁸Ga-DOTATATE	127–302	Histology	NR	NR
Menda Y	2017	USA	40	Prospective	23/17	55	⁶⁸Ga-DOTATOC	148–185	Histology and follow-up	1–178mons	0.38
Nakamoto Y	2015	Japan	14	Retrospective	5/9	55.8	⁶⁸Ga-DOTATOC	130	Histology and follow-up	NR	NR
Naswa N	2012	India	20	Retrospective	10/10	55	⁶⁸Ga-DOTANOC	132–222	Histology and follow-up	6 months	0.6
Frilling A	2010	Germany	52	Retrospective	27/25	52	⁶⁸Ga-DOTATOC	120–250	Histology	NR	NR
Alonso O	2014	Uruguay	29	Retrospective	12/17	59.5	⁶⁸Ga-DOTATATE	85–123	Histology and follow-up	8 months	0.59
Pradsad V	2010	Germany	59	Retrospective	33/26	65	⁶⁸Ga-DOTANOC	185	Histology and follow-up	29 months	0.59
Pruthi A	2016	India	68	Retrospective	45/23	54.9	⁶⁸Ga-DOTANOC	111–148	Histology and follow-up	13.3 months	0.59
Schreiter NF	2014	Germany	33	Retrospective	13/20	56.3	⁶⁸Ga-DOTATOC	106	Histology and follow-up	21.4mons	0.46
Sadowski SM	2016	America	131	Prospective	57/74	51	⁶⁸Ga-DOTATATE	185	Histology and follow-up	6–12 mons	0.65

NR, not reported.

Quality assessment and risk of bias

The QUADAS-2 assessments of the studies are listed in Fig. 2. The assessment included seven domains and two parts (risk of bias and applicability). The overall quality of the included studies was good. In the patient selection domain, most studies were performed retrospectively and three studies may have selection bias. All studies used histology and follow-up as diagnostic reference standards, and there was no risk of bias. In the flow and timing domain, some studies only reported the duration of follow-up, not divided into specific months.

Fig. 2.

Quality assessment of included studies with Cochrane risk of bias assessment tool. (a) Overall and (b) study-level risk of bias.

Fig. 3.

Pooled sensitivity and specificity of ⁶⁸Ga-DOTA-SSTR in CUP-NET.

We used Deeks’ funnel plot to evaluate publication bias. The funnel plots for publication bias showed symmetry for all included studies, and the P value was 0.21.

Pooled diagnostic performance and diagnostic yield

The diagnostic performance of ⁶⁸Ga-DOTA-SSTR for CUP-NET was 82% (95% CI = 63–92), specificity was 55% (95% CI = 31–77), PLR was 1.9 (95% CI = 1.1–3.1), NLR was 0.32 (95% CI = 0.12–0.86), and DOR was 6 (95% CI = 1,25) (Fig. 3). The area under the receiver operating characteristic curve was 69% (95% CI = 65–73%), as shown in Fig. 4.

Fig. 4.

Summary ROC curves of the diagnostic accuracy of ⁶⁸Ga-DOTA-SSTR in CUP-NET. The area under the ROC is 0.69. ROC, receiver operating characteristic.

Subgroup and meta-regression analyses

On the basis of the I² statistics (I² = 88%), there was significant heterogeneity. We further examined the heterogeneity to explain the differences. The included studies were stratified by study design, radiopharmaceutical applied, and country (Table 2). In the radiopharmaceutical subgroup, the heterogeneity was significantly reduced. The results showed that different radiopharmaceuticals were the source of heterogeneity. There was no significant difference in the DOR of 68Ga-DOTA-SSTR for CUP-NETs among the subgroups stratified by study design, country, disease state, and diagnostic criteria. In meta-regression analyses, there were no significant differences in variables such as number of patients, mean age, SUV_max of primary sites, and mean time interval (Table 3).

Table 2.

Subgroup analyses for diagnostic accuracy of ⁶⁸Ga-DOTA-SSTR in CUP-NET.

Variable	No. of studies	DOR (%)	95% CI	Heterogeneity I² (%)	P value
Study design
Retrospective	8	17.1	6.75–43.3	0	0.873
Prospective	2	19.7	0.9–422.1	83.7	0.013
Radiopharmaceuticals
⁶⁸Ga-DOTATATE	3	27.2	6.1–122.1	28.2	0.048
⁶⁸Ga-DOTATOC	4	5.4	1.6–18.1	0	0.014
⁶⁸Ga-DOTANOC	3	15.7	7.2–92.9	0	0.032
Country
Europe and America	7	17.5	5.5–56.1	42.5	0.138
Asia	3	15.7	7.2–34.1	0	0.343
State of disease
Primary staging	7	1.21	1.05–1.4	76.0	0.000
Primary staging + restaging	3	1.26	1.13–1.53	97.0	0.000
Diagnostic criteria
Histology	2	6.09	2.01–18.44	75.8	0.042
Histology + follow-up	8	1.26	1.13–1.39	61.0	0.012

CI, confidence interval; CUP-NET, neuroendocrine tumors of unknown primary origin; DOR, diagnostic odds ratio.

Table 3.

Results of meta-regression analyses.

Variable	Regression coefficient	95% CI	P value
Patients (n)	–0.109	–0.108–0.865	0.390
Mean age (years)	–0.548	–4.894–3.797	0.355
SUV_max of primary site	0.237	–3.289–3.765	0.549
Mean time interval	0.191	–1.441–1.823	0.377

CI, confidence interval; SUV_max, maximum standard uptake value.

Frequency of the key therapeutic factors

The key therapeutic factors of NETs include localization of the primary tumor site, histological grade of the NET, and distant metastasis sites. Furthermore, we calculated the rate of ⁶⁸Ga-DOTA-SSTR in localizing and detecting primary and metastatic sites.

Localization and frequency of the primary tumor site of NETs

All of the included studies reported the primary site of NETs (Table 2). ⁶⁸Ga-DOTA peptides identified 37% (95% CI = 19.4–52.6) of the primary tumors in the small intestine, 26.5% (95% CI = 15.8–36.8) in the pancreas, 19% (95% CI = 10.4–25.9) with an occult primary origin, 4% (95% CI = 2.7–5.2) in the rectum and colon, 2% (95% CI = 0.7–3.3) in the lungs, 2% (95% CI = 0.6–3.3) in the stomach, 2% (95% CI = 0.2–2.4) of insulinomas, 1.2% (95% CI = 0.2–2.3) of vipomas, 1.1% (95% CI = 0.1–2.1) in the thyroid, 1% (95% CI = 0–2.0) in the kidney, 1% (95% CI = 0.1–0) in the prostate, 1% (95% CI = 0.1–2.0) in the biliary system, 1% (95% CI = 0–1.9) of paragangliomas, and 0.9% (95% CI = 0–1.9) in the lesser pelvis (Table 4 and Fig. 5a).

Table 4.

The localization and number of primary lesions of CUP-NET.

Author	Year	Small intestine (ileum/jejunum)	Pancreas	Rectum/Colon	Lung	Stomach	Kidney	Prostate	Biliary system	Paraganglioma	Medullary thyroid carcinoma	Insulinoma	Vipoma	Small pelvis	Unknown primary	Total
Kazmierczak	2017	19	12	0	2	0	0	0	0	0	0	0	0	1	4	38
Menda Y	2017	8	6	1	0	0	0	0	0	0	0	0	0	0	0	15
Nakamoto Y	2015	6	1	0	0	0	0	1	0	0	0	0	0	0	6	14
Naswa N	2012	8	1	1	1	1	0	0	0	0	0	0	0	0	8	20
Frilling A	2010	19	27	0	2	0	0	0	3	0	0	0	0	0	1	52
Alonso O	2014	8	7	1	0	1	0	0	0	0	0	0	0	0	12	29
Pradsad V	2010	14	16	2	2	0	0	0	0	1	0	0	0	0	24	59
Pruthi A	2016	19	7	8	1	4	1	1	0	0	0	0	0	0	27	68
Schreiter NF	2014	16	8	0	0	0	0	0	0	0	0	0	0	0	0	24
Sadowski SM	2016	31	36	4	1	7	0	0	0	0	1	7	2	0	0	89

CUP-NET, neuroendocrine tumors of unknown primary origin.

Fig. 5.

Pie chart of CUP-NET: (a) the localization and frequency of primary tumor (b) the pathological classification of primary lesions (c) the common site of distant metastasis.

Histological grade of the primary tumor

Seven studies reported the histological grade of the primary NET (Table 3). According to the 2017 AJNCC guidelines (33), ⁶⁸Ga-DOTA-SSTR identified the pathology of and localized the primary NETs as follows: G1 = 56.5% (95% CI = 42.2–67.8); G2 = 27.6% (95% CI = 12–41.9); G3 = 9.8% (95% CI = 3.7–15); undifferentiated = 2.0% (95% CI = 0.3–3.8); and unknown = 3.2% (95% CI = 0.3–6.0) (Table 5 and Fig. 5b).

Table 5.

The pathological histopathological of primary lesions of CUP-NET.*

Author	Year	Grade 1	Grade 2	Grade3	Undifferentiated	Unknown	Total
Kazmierczak	2017	18	20	0	0	0	38
Menda Y	2017	13	17	8	2	0	40
Nakamoto Y	2015	NR	NR	NR	NR	NR	NR
Naswa N	2012	NR	NR	NR	NR	NR	NR
Frilling A	2010	NR	NR	NR	NR	NR	NR
Alonso O	2014	21	3	5	0	0	29
Pradsad V	2010	45	2	2	2	8	59
Pruthi A	2016	16	10	5	0	0	31
Schreiter NF	2014	16	5	6	0	6	33
Sadowski SM	2016	11	8	1	0	0	20

*According to AJNCC 2017 guideline,

CUP-NET, neuroendocrine tumors of unknown primary origin; NR, not reported.

Localization and incidence rate of common metastatic sites of NETs detected by ⁶⁸Ga-DOTA-SSTR

Ten studies reported the metastatic sites of NETs (Table 4). ⁶⁸Ga-DOTA peptides were the most commonly found metastatic sites in the liver (57.9%, 95% CI = 46–63.8), followed by lymph nodes (22.8%, 95% CI = 15.9–27.6), bones (12.8%, 95% CI = 5.6–17.9), lung (2.8%, 95% CI = 1.2–4.3), others (1.7%, 95% CI = 0.2–3.3]), mesentery (0.9%, 95% CI = 0.1–1.9), and peritoneum (0.1%, 95% CI = 0.1–0.3) (Table 6 and Fig. 5c).

Table 6.

The common site and number of distant metastasis of CUP-NET.

Author	Year	Liver	Bones	Lymph nodes	Lung	Peritoneum	Mesentery	Other	Total
Kazmierczak	2017	23	0	5	2	0	0	8	38
Menda Y	2017	18	6	8	5	2	0	1	40
Nakamoto Y	2015	9	2	3	0	0	0	0	14
Naswa N	2012	19	6	3	0	0	0	2	30
Frilling A	2010	33	7	10	2	0	0	0	52
Alonso O	2014	17	1	6	1	0	3	1	29
Pradsad V	2010	16	17	30	0	0	0	0	63
Pruthi A	2016	50	1	10	0	0	6	1	68
Schreiter NF	2014	23	7	19	2	0	0	3	54
Sadowski SM	2016	396	123	144	30	0	0	0	693

CUP-NET, neuroendocrine tumors of unknown primary origin.

Pooled detection rate of ⁶⁸Ga-DOTA-SSTR for CUP-NETs

Seven studies (24,25,27,29 –32) reported the detection rate of ⁶⁸Ga-DOTA-SSTR for CUP-NETs. The reported proportions were calculated by dividing the number of TP patients detected on PET/CT by the total number of patients. To ensure consistency in the results, we recalculated this variable in the remaining three studies and further assessed the pooled detection rate. The pooled detection rate of ⁶⁸Ga-DOTA-SSTR for CUP-NETs was 61% (95% CI = 53–69) (Fig. 6).

Fig. 6.

The pooled detection rate of ⁶⁸Ga-DOTA-SSTR in CUP-NET.

Discussion

We examined 10 studies involving 484 patients with CUP-NETs to evaluate the clinical value of ⁶⁸Ga-DOTA-SSTR for localizing the primary and metastatic sites. Our meta-analysis showed that ⁶⁸Ga-somatostatin receptor PET/CT had a high sensitivity but low specificity in the diagnosis of CUP-NETs. The ⁶⁸Ga-somatostatin receptor was highly effective in locating the primary and metastatic sites of CUP-NETs. The pooled detection rate of ⁶⁸Ga-DOTA-SSTR for CUP-NETs was 61%.

NETs generally originate from neuroendocrine cells in multiple organ systems, such as the gastrointestinal tract, pancreaticobiliary tract, and respiratory system. Based on their property of secreting hormones, these tumors are divided into functional or non-functional NETs. The prevalence of CUP-NETs is approximately 11%–22% (3,34). The multimodal diagnostic methods typically include a detailed history, physical examination, laboratory tests for serum biomarkers, diagnostic imaging, and pathology (4). Approximately 10%–14% of NETs and the primary sites remain unknown after the standard diagnostic work-up. Unlike NETs, CUP-NETs may present as non-functional, advanced, and poorly differentiated tumors, and these patients have a poorer prognosis than those with other NETs. The early and accurate identification of NET subtypes is pivotal for targeted treatment plans.

NETs are characterized by the overexpression of somatostatin receptors (SSTRs). First-generation imaging, such as SRS, has a spatial resolution that limits this method to the clinical management of tumors >1 cm (13,35). As a relatively new imaging modality, ⁶⁸Ga-DOTA-SSTR PET/CT has become a standard diagnostic tool for NETs. Similar to SRS, ⁶⁸Ga-labeled somatostatin analogs also bind to SSTRs in NET cells. Currently, the major peptides for ⁶⁸Ga-somatostatin imaging include ⁶⁸Ga-DOTATATE, ⁶⁸Ga-DOTATOC, and ⁶⁸Ga-DOTANOC. These tracers have various affinities for SSTR subtypes. ⁶⁸Ga-DOTATATE predominantly binds to SSTR2, ⁶⁸Ga-DOTATOC binds to SSTR2 and SSTR5, and ⁶⁸Ga-DOTANOC additionally binds to SSTR3 and SSTR5 (11). Studies have indicated the high impact of ⁶⁸Ga-DOTA-SSTR on the diagnostic management of NETs compared to that of traditional SSTR imaging (¹¹¹In-octreotide) (36). ⁶⁸Ga-SSTRs have demonstrated a higher sensitivity in detecting primary sites than SSTRs, with sensitivities of 100% and 85%, respectively (37). The resolution of PET/CT has increased the detection rate of tumors <1 cm and has an improved diagnostic performance.

The present study reported the pooled diagnostic performance and detection rate of ⁶⁸Ga-DOTA-SSTR for CUP-NETs and further located the primary and metastatic sites. Our results were similar to previous surgical exploration results obtained by Massimino et al. (5) and Pruthi et al. (31). These studies reported that the primary sites of CUP-NETs were in the small bowel and duodenum (47.5%), rectum (20%), pancreas (17.5%), stomach (10%), lung (2.5%), kidney (2.5%), and prostate (2.5%). Regarding pathological classification, our results further confirmed the lower detection rate (15%) for poorly differentiated tumors, which are assumed to have low SSTR expression. This could be explained by moderately or poorly differentiated metastatic lesions and SSTR downregulation. In this subgroup, ¹⁸F-FDG PET/CT may be useful in the localization of undetected lesions. Our results showed the lower specificity and higher false-negative rate of ⁶⁸Ga-DOTA-SSTR PET/CT for CUP than for NETs. The reasons are as follows: (i) the high uptake of ⁶⁸Ga-DOTA in the normal foregut and pancreatic tissues limits the detection of lesions; and (ii) poorly differentiated tumors do not express SSTRs (38). The pooled proportion of contribution of ⁶⁸Ga-SSTR imaging in the diagnosis of CUP-NETs was 61%, which demonstrated its clinical value.

The present study has some limitations. First, the sample sizes of the included studies were small. Few studies have reported the detailed sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for CUP-NETs. However, 10 was a sufficient number of studies to calculate the pooled diagnostic performance. Second, the included studies are heterogeneous. We analyzed the sources of heterogeneity in the study design, which were the radiopharmaceuticals and year of publication. However, the results of the subgroup analyses showed that the above reasons are not the main reasons for heterogeneity. These heterogeneities are inevitable in meta-analyses.

In conclusion, our studies demonstrated the high diagnostic sensitivity of ⁶⁸Ga-DOTA-SSTR for CUP-NETs. The ⁶⁸Ga-somatostatin receptor was highly effective in locating the primary and metastatic sites of CUP-NETs and further changed the clinical management of 61% of patients. Our studies may provide the theoretical foundation for the use of ⁶⁸Ga-DOTA in routine clinical management.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Ying Kan was partically supported by Beijing Excellent Cultivation Grant (2018000021469G205) and President Fund from Capital Medical University (PYZ19150).

ORCID iD

Ji-gang Yang

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Clinical value of 68 Ga-DOTA-SSTR PET/CT in the diagnosis and detection of neuroendocrine tumors of unknown primary origin: a systematic review and meta-analysis

Abstract

Background

Purpose

Material and Methods

Results

Conclusion

Keywords

Introduction

Material and Methods

Search strategy

Selection criteria and quality assessment

Data extraction and statistical analysis

Results

Literature search and characteristics of the included studies

Quality assessment and risk of bias

Pooled diagnostic performance and diagnostic yield

Subgroup and meta-regression analyses

Frequency of the key therapeutic factors

Localization and frequency of the primary tumor site of NETs

Histological grade of the primary tumor

Localization and incidence rate of common metastatic sites of NETs detected by 68Ga-DOTA-SSTR

Pooled detection rate of 68Ga-DOTA-SSTR for CUP-NETs

Discussion

Footnotes

Declaration of conflicting interests

Funding

ORCID iD

References

Localization and incidence rate of common metastatic sites of NETs detected by ⁶⁸Ga-DOTA-SSTR

Pooled detection rate of ⁶⁸Ga-DOTA-SSTR for CUP-NETs